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Fintech and banking","💻 Tech","✈️ Travel \u0026 E-Commerce","🌐 Social platforms","🛒 E-commerce and retail","🚗 Delivery and mobility","📺 Media and streaming","🎓 Education","🎮 Gaming","🏭 Manufacturing","📊 Repo Stats","🙌 Support"],"sub_categories":["🏢 Stripe","🏢 Dropbox","🏢 Airbnb","🏢 Pinterest","🏢 Datto","🏢 Shopify","🏢 Meta","🏢 Yelp","🏢 Honeycomb","🏢 Glassdoor","🏢 Walmart","🏢 Doordash","🏢 Twitter","🏢 Netflix","🏢 Picnic","🏢 Manus","🏢 Linkedin","🏢 Lyft","🏢 Booking","🏢 Coinbase","🏢 Figma","🏢 LinkedIn","🏢 PayPal","🏢 Quora","🏢 Slack","🏢 Snap","🏢 Uber","🏢 Canva","🏢 Swiggy","🏢 Instacart","🏢 Github","🏢 Spotify","🏢 BlaBlaCar","🏢 Careem","🏢 Delivery Hero","🏢 DoorDash","🏢 Foodpanda","🏢 Gojek","🏢 Gousto","🏢 Grab","🏢 Grubhub","🏢 Mercado Libre","🏢 Oda","🏢 iFood","🏢 Amazon","🏢 Asos","🏢 Autotrader","🏢 Cars24","🏢 Cherrypick","🏢 Coches.net","🏢 Cookidoo","🏢 Coupang","🏢 Ebay","🏢 Etsy","🏢 Faire","🏢 Flipkart","🏢 Kingfisher Technology","🏢 Leboncoin","🏢 ManoMano","🏢 Nordstrom","🏢 OLX","🏢 Ocado","🏢 Stitch 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companies\n\n![License](https://img.shields.io/badge/license-Apache%202.0-blue?style=for-the-badge)\n![Stars](https://img.shields.io/github/stars/hackThacker/awesome-ml-llm-case-studies?style=for-the-badge\u0026color=yellow)\n![Forks](https://img.shields.io/github/forks/hackThacker/awesome-ml-llm-case-studies?style=for-the-badge\u0026color=green)\n![Issues](https://img.shields.io/github/issues/hackThacker/awesome-ml-llm-case-studies?style=for-the-badge\u0026color=red)\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n[📖 What is This](#-what-is-this) • [💡 Why This Repo](#-why-this-repo) • [📂 Topics Covered](#-topics-covered) • [🗂️ Case Studies](#️-case-studies-by-industry) • [👥 Who Is This For](#-who-is-this-for) • [📜 License](#-license)\n\n\u003c/div\u003e\n\n---\n\n## 📖 What is This\n\nThis repository is a **hand-curated database of 800+ ML and LLM system design case studies** published by engineering teams at leading companies worldwide. Every entry is a real blog post, paper, or talk — no fluff, no theory, only production-grade engineering stories that show how top companies actually build and ship AI systems.\n\n\u003e **Span:** 2017 – 2025 | **Companies:** 150+ | **Industries:** 10 | **Technologies:** AI Agents, LLMs, RAG, Predictive ML, CV, NLP\n\n---\n\n## 💡 Why This Repo\n\n| Reason | Description |\n|--------|-------------|\n| 🏗️ **Real System Design** | Every case study is a production engineering blog, paper, or recorded talk — not tutorials |\n| 🏢 **150+ Companies** | Covers Google, Meta, Netflix, Uber, DoorDash, Airbnb, LinkedIn, Spotify, and 140+ more |\n| 📅 **2017–2025 Timeline** | Tracks the evolution from classical ML to modern LLM and agentic systems |\n| 🔬 **6 Core Technologies** | AI Agents · Generative AI \u0026 LLM · RAG · Predictive ML · Computer Vision · NLP |\n| 🌍 **10 Industries** | Delivery · E-Commerce · Fintech · Tech · Media · Social · Travel · Gaming · Manufacturing · Education |\n| 🗂️ **Organized \u0026 Searchable** | Structured by industry → company → year for fast navigation |\n\n---\n\n## 📂 Topics Covered\n\n| # | 🏷️ Technology | 📝 Description |\n|---|--------------|----------------|\n| 1 | 🤖 **AI Agents** | Autonomous multi-agent systems, agentic workflows, tool-use, planning |\n| 2 | 🧠 **Generative AI \u0026 LLM** | LLM fine-tuning, prompt engineering, code generation, text-to-SQL, multimodal |\n| 3 | 🔍 **RAG** | Retrieval-Augmented Generation, vector search, knowledge bases, hybrid retrieval |\n| 4 | 📊 **Predictive ML** | Recommendation systems, fraud detection, forecasting, ranking, causal inference |\n| 5 | 👁️ **Computer Vision** | Image classification, object detection, document processing, visual search |\n| 6 | 💬 **NLP** | Text classification, entity extraction, content moderation, embeddings |\n\n---\n\n## 🗂️ Case Studies by Industry\n\n### 📑 Quick Navigation\n\n- [🚗 Delivery and mobility](#delivery-and-mobility) — **181 case studies** · **18 companies**\n- [🛒 E-commerce and retail](#e-commerce-and-retail) — **152 case studies** · **29 companies**\n- [🎓 Education](#education) — **1 case studies** · **1 companies**\n- [🏦 Fintech and banking](#fintech-and-banking) — **63 case studies** · **22 companies**\n- [🎮 Gaming](#gaming) — **8 case studies** · **4 companies**\n- [🏭 Manufacturing](#manufacturing) — **5 case studies** · **1 companies**\n- [📺 Media and streaming](#media-and-streaming) — **57 case studies** · **10 companies**\n- [🌐 Social platforms](#social-platforms) — **99 case studies** · **14 companies**\n- [💻 Tech](#tech) — **192 case studies** · **86 companies**\n- [✈️ Travel \u0026 E-Commerce](#travel-and-e-commerce) — **47 case studies** · **7 companies**\n\n---\n\n\u003ca id=\"delivery-and-mobility\"\u003e\u003c/a\u003e\n\n## 🚗 Delivery and mobility\n\n\u003e **181 case studies** from **18 companies**\n\n### 🏢 BlaBlaCar\n\n- 🧠 **[2025]** [Why We Built “BlaBlaCar Data Copilot”: Shifting Data Analysis Left](https://medium.com/blablacar/why-we-built-blablacar-data-copilot-shifting-data-analysis-left-b4cc246faf52) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [How BlaBlaCar leverages machine learning to match passengers and drivers - Part 2](https://medium.com/blablacar/how-blablacar-leverages-machine-learning-to-match-passengers-and-drivers-part-2-5c69c7dd5105) `Predictive ML`\n- 📊 **[2023]** [How BlaBlaCar leverages machine learning to match passengers and drivers - Part 1](https://medium.com/blablacar/how-blablacar-matches-passengers-and-drivers-with-machine-learning-1cf151451f) `Predictive ML`\n- 📊 **[2023]** [How we used machine learning to fight fraud at BlaBlaCar — Part 1](https://medium.com/blablacar/how-we-used-machine-learning-to-fight-fraud-at-blablacar-part-1-3b976c9dcdf6) `Predictive ML`\n- 📊 **[2023]** [How we built our machine learning pipeline to fight fraud at BlaBlaCar — Part 2](https://medium.com/blablacar/how-we-built-our-machine-learning-pipeline-to-fight-fraud-at-blablacar-part-2-476335f459b4) `Predictive ML`\n\n### 🏢 Careem\n\n- 📊 **[2024]** [Temporary holds: Leveraging machine learning models to reduce fraud](https://engineering.careem.com/tech/posts/temporary-holds-leveraging-machine-learning-models-to-reduce-fraud-while-improving-customer-experience) `Predictive ML`\n- 👁️ **[2024]** [Facial recognition to detect duplicate Captain accounts](https://engineering.careem.com/tech/posts/using-facial-recognition-technology-fraud-detection) `CV`\n\n### 🏢 Delivery Hero\n\n- 🤖 **[2025]** [How Delivery Hero Uses Agentic AI for Building a Product Knowledge Base](https://tech.deliveryhero.com/blog/how-delivery-hero-uses-agentic-ai-for-building-a-product-knowledge-base/) `AI agents`\n- 🧠 **[2024]** [How we improved multilingual search with few-shot LLM translations](https://tech.deliveryhero.com/blog/how-we-improved-multilingual-search-with-few-shot-llm-translations/) `Generative AI \u0026 LLM`\n- 🤖 **[2024]** [Introducing the AI Data Analyst “QueryAnswerBird” – Part 1. Utilization of RAG and Text-to-SQL](https://tech.deliveryhero.com/blog/introducing-the-ai-data-analyst-queryanswerbird-part-1-utilization-of-rag-and-text-to-sql/) `AI agents`\n- 🤖 **[2024]** [Introducing the AI Data Analyst “QueryAnswerBird” – Part 2: Data Discovery](https://tech.deliveryhero.com/blog/introducing-the-ai-data-analyst-queryanswerbird-part-2-data-discovery/) `AI agents`\n- 🧠 **[2023]** [Semantic Product Matching](https://tech.deliveryhero.com/semantic-product-matching/) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Don’t Worry, We Got You: Personalised Model](https://tech.deliveryhero.com/dont-worry-we-got-you-personalised-model-2/) `Predictive ML`\n- 📊 **[2023]** [Personalisation @ Delivery Hero: Ranking restaurants for new users](https://tech.deliveryhero.com/personalisation-delivery-hero-ranking-restaurants-for-new-users/) `Predictive ML`\n- 📊 **[2023]** [Personalisation @ Delivery Hero: Understanding Customers](https://tech.deliveryhero.com/personalisation-at-delivery-hero-understanding-customers/) `Predictive ML`\n\n### 🏢 DoorDash\n\n- 📊 **[2023]** [Lifecycle of a Successful ML Product: Reducing Dasher Wait Times](https://doordash.engineering/2023/02/15/lifecycle-of-a-successful-ml-product-reducing-dasher-wait-times/) `Predictive ML`\n- 📊 **[2023]** [How DoorDash Upgraded a Heuristic with ML to Save Thousands of Canceled Orders](https://doordash.engineering/2023/01/10/how-doordash-upgraded-a-heuristic-with-ml-to-save-thousands-of-canceled-orders/) `Predictive ML`\n\n### 🏢 Doordash\n\n- 🧠 **[2025]** [Profile Generation with LLMs: Understanding consumers, merchants, and items](https://careersatdoordash.com/blog/doordash-profile-generation-llms-understanding-consumers-merchants-and-items/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Advancing Menu Content with AI: How DoorDash uses AI to generate menu descriptions](https://careersatdoordash.com/blog/doordash-ai-menu-descriptions/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Using LLM to transcribe restaurant menu photos](https://careersatdoordash.com/blog/doordash-llm-transcribe-menu/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [How DoorDash leverages LLMs to evaluate search result pages](https://careersatdoordash.com/blog/doordash-llms-to-evaluate-search-result-pages) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Mind the Gap: Using LLMs to bridge behavioral silos in multi-vertical recommendations](https://careersatdoordash.com/blog/doordash-llms-bridge-behavioral-silos-in-multi-vertical-recommendations/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [SafeChat: DoorDash’s AI-powered safety feature](https://careersatdoordash.com/blog/doordash-safechat-ai-safety-feature/) `Generative AI \u0026 LLM`\n- 🤖 **[2025]** [Beyond Single Agents: How DoorDash is building a collaborative AI ecosystem](https://careersatdoordash.com/blog/beyond-single-agents-doordash-building-collaborative-ai-ecosystem/) `AI agents`\n- 🔍 **[2025]** [A scalable LLM approach to enhancing chatbot knowledge with user-generated content](https://careersatdoordash.com/blog/doordash-llm-chatbot-knowledge-with-ugc/) `RAG`\n- 🧠 **[2025]** [Using LLMs to infer grocery preferences from DoorDash restaurant orders](https://careersatdoordash.com/blog/doordash-llms-for-grocery-preferences-from-restaurant-orders/) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [Building an anomaly detection platform at DoorDash to catch fraud trends early](https://careersatdoordash.com/blog/doordash-anomaly-detection-platform-to-catch-fraud-trends/) `Predictive ML`\n- 🧠 **[2025]** [When GenAI Meets Personalization: Powering DoorDash’s next-generation homepage experience](https://careersatdoordash.com/blog/doordashs-next-generation-homepage-genai/) `Generative AI \u0026 LLM`\n- 🔍 **[2024]** [Path to high-quality LLM-based Dasher support automation](https://careers.doordash.com/blog/large-language-modules-based-dasher-support-automation/) `RAG`\n- 📊 **[2024]** [Beyond the Click: Elevating DoorDash’s personalized notification experience with GNN recommendation](https://careersatdoordash.com/blog/doordash-customize-notifications-how-gnn-work/) `Predictive ML`\n- 📊 **[2024]** [Improving ETAs with Multi-Task Models, Deep Learning, and Probabilistic Forecasts](https://doordash.engineering/2024/03/12/improving-etas-with-multi-task-models-deep-learning-and-probabilistic-forecasts/) `Predictive ML`\n- 🧠 **[2024]** [Building DoorDash’s Product Knowledge Graph with Large Language Models](https://doordash.engineering/2024/04/23/building-doordashs-product-knowledge-graph-with-large-language-models/) `Generative AI \u0026 LLM`\n- 🔍 **[2024]** [How DoorDash leverages LLMs for better search retrieval](https://careersatdoordash.com/blog/how-doordash-leverages-llms-for-better-search-retrieval/) `RAG`\n- 📊 **[2024]** [Precision in Motion: Deep learning for smarter ETA predictions](https://careersatdoordash.com/blog/deep-learning-for-smarter-eta-predictions/) `Predictive ML`\n- 📊 **[2023]** [Personalizing the DoorDash Retail Store Page Experience](https://doordash.engineering/2023/12/12/personalizing-the-doordash-retail-store-page-experience/) `Predictive ML`\n- 📊 **[2023]** [How DoorDash Improves Holiday Predictions via Cascade ML Approach](https://doordash.engineering/2023/08/31/how-doordash-improves-holiday-predictions-via-cascade-ml-approach/) `Predictive ML`\n- 📊 **[2023]** [How DoorDash Built an Ensemble Learning Model for Time Series Forecasting](https://doordash.engineering/2023/06/20/how-doordash-built-an-ensemble-learning-model-for-time-series-forecasting/) `Predictive ML`\n- 🧠 **[2023]** [DoorDash identifies Five big areas for using Generative AI](https://doordash.engineering/2023/04/26/doordash-identifies-five-big-areas-for-using-generative-ai/) `Generative AI \u0026 LLM`\n- 📊 **[2022]** [Building the Model Behind DoorDash’s Expansive Merchant Selection](https://doordash.engineering/2022/04/19/building-merchant-selection/) `Predictive ML`\n- 📊 **[2022]** [3 Changes to Expand DoorDash’s Product Search Beyond Delivery](https://doordash.engineering/2022/05/10/3-changes-to-expand-doordashs-product-search/) `Predictive ML`\n- 📊 **[2022]** [Evolving DoorDash’s Substitution Recommendations Algorithm](https://doordash.engineering/2022/09/08/evolving-doordashs-substitution-recommendations-algorithm/) `Predictive ML`\n- 📊 **[2022]** [Homepage Recommendation with Exploitation and Exploration](https://doordash.engineering/2022/10/05/homepage-recommendation-with-exploitation-and-exploration/) `Predictive ML`\n- 📊 **[2021]** [Using ML and Optimization to Solve DoorDash’s Dispatch Problem](https://doordash.engineering/2021/08/17/using-ml-and-optimization-to-solve-doordashs-dispatch-problem/) `Predictive ML`\n- 👁️ **[2021]** [How DoorDash Quickly Spins Up Multiple Image Recognition Use Cases](https://doordash.engineering/2021/11/03/how-doordash-quickly-spins-up-multiple-image-recognition-use-cases/) `CV`\n- 📊 **[2020]** [Optimizing DoorDash’s Marketing Spend with Machine Learning](https://doordash.engineering/2020/07/31/optimizing-marketing-spend-with-ml/) `Predictive ML`\n- 📊 **[2020]** [Things Not Strings: Understanding Search Intent with Better Recall](https://doordash.engineering/2020/12/15/understanding-search-intent-with-better-recall/) `Predictive ML`\n\n### 🏢 Foodpanda\n\n- 📊 **[2024]** [Introduction: Optimising Budget through Machine Learning](https://medium.com/foodpanda-data/introduction-optimising-budget-through-data-analysis-030b2f39ad0c) `Predictive ML`\n- 📊 **[2024]** [The Making: Optimising Budget through Machine Learning](https://medium.com/foodpanda-data/the-making-optimising-budget-through-data-analysis-3ca4d97a6d1a) `Predictive ML`\n- 📊 **[2024]** [Sculpturing: Optimising Budget through Machine Learning](https://medium.com/foodpanda-data/sculpturing-optimising-budget-through-data-analysis-bd1c1872a36b) `Predictive ML`\n- 📊 **[2023]** [Menu Ranking](https://medium.com/foodpanda-data/menu-ranking-422ad21f381e) `Predictive ML`\n- 📊 **[2022]** [Classifying restaurant cuisines with subjective labels](https://medium.com/foodpanda-data/classifying-restaurant-cuisines-with-subjective-labels-fa10012d18a9) `Predictive ML`\n\n### 🏢 Gojek\n\n- 📊 **[2024]** [How Gojek Allocates Personalised Vouchers At Scale](https://www.gojek.io/blog/how-gojek-allocates-personalised-vouchers-at-scale) `Predictive ML`\n- 📊 **[2022]** [How We Estimate Food Debarkation Time With ‘Tensoba’](https://medium.com/gojekengineering/how-we-estimate-food-debarkation-time-with-tensoba-da05674cb758) `Predictive ML`\n- 📊 **[2022]** [How We Estimate Food Debarkation Time With 'Tensoba'](https://www.gojek.io/blog/food-debarkation-tensoba) `Predictive ML`\n- 💬 **[2020]** [How Gojek Uses NLP to Name Pickup Locations at Scale](https://www.gojek.io/blog/nlp-cartobert) `NLP`\n- 📊 **[2020]** [How We Built a Matchmaking Algorithm to Cross-Sell Products](https://www.gojek.io/blog/how-we-built-a-matchmaking-algorithm-to-cross-sell-products) `Predictive ML`\n- 📊 **[2019]** [Under the Hood of Gojek’s Automated Forecasting Tool](https://www.gojek.io/blog/under-the-hood-of-gojeks-automated-forecasting-tool) `Predictive ML`\n- 📊 **[2019]** [Is This What You Were Looking For?](https://www.gojek.io/blog/is-this-what-you-were-looking-for) `Predictive ML`\n- 📊 **[2019]** [The Secret Sauce Behind Search Personalisation](https://www.gojek.io/blog/the-secret-sauce-behind-search-personalisation) `Predictive ML`\n\n### 🏢 Gousto\n\n- 📊 **[2022]** [Gousto R-series Vol 2: Tackling the Cold-Start Problem in Recipe Recommendation Engine](https://medium.com/gousto-engineering-techbrunch/gousto-r-series-vol-2-tackling-the-cold-start-problem-in-recipe-recommendation-engine-af92a434805f) `Predictive ML`\n- 📊 **[2022]** [Using Data Science to Retain Customers](https://medium.com/gousto-engineering-techbrunch/using-data-science-to-retain-customers-63f19a03a0b6) `Predictive ML`\n- 📊 **[2021]** [Gousto R-series vol 1: Three tales of the Rouxcommender family](https://medium.com/gousto-engineering-techbrunch/gousto-r-series-vol-1-three-tales-of-the-rouxcommender-family-a3555a93edea) `Predictive ML`\n\n### 🏢 Grab\n\n- 🧠 **[2025]** [From failure to success: The birth of GrabGPT, Grab’s internal ChatGPT](https://engineering.grab.com/the-birth-of-grab-gpt) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [User foundation models for Grab](https://engineering.grab.com/user-foundation-models-for-grab) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [How we built a custom vision LLM to improve document processing at Grab](https://engineering.grab.com/custom-vision-llm-at-grab) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [From failure to success: The birth of GrabGPT, Grab’s internal ChatGPT](https://engineering.grab.com/the-birth-of-grab-gpt) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [SpellVault’s evolution: Beyond LLM apps, towards the agentic future](https://engineering.grab.com/spellvault-evolution-beyond-llm) `Generative AI \u0026 LLM`\n- 🔍 **[2024]** [Leveraging RAG-powered LLMs for Analytical Tasks](https://engineering.grab.com/transforming-the-analytics-landscape-with-RAG-powered-LLM) `RAG`\n- 🧠 **[2024]** [Enabling conversational data discovery with LLMs at Grab](https://engineering.grab.com/hubble-data-discovery) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [LLM-assisted vector similarity search](https://engineering.grab.com/llm-assisted-vector-similarity-search) `Generative AI \u0026 LLM`\n- 🧠 **[2023]** [LLM-powered data classification for data entities at scale](https://engineering.grab.com/llm-powered-data-classification) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Unsupervised graph anomaly detection - Catching new fraudulent behaviours](https://engineering.grab.com/graph-anomaly-model) `Predictive ML`\n- 📊 **[2023]** [Scaling marketing for merchants with targeted and intelligent promos](https://engineering.grab.com/scaling-marketing-for-merchants) `Predictive ML`\n- 📊 **[2023]** [Stepping up marketing for advertisers: Scalable lookalike audience](https://engineering.grab.com/scalable-lookalike-audiences) `Predictive ML`\n- 📊 **[2022]** [Graph for fraud detection](https://engineering.grab.com/graph-for-fraud-detection) `Predictive ML`\n\n### 🏢 Grubhub\n\n- 📊 **[2022]** [Forecasting Grubhub Order Volume At Scale](https://bytes.grubhub.com/forecasting-grubhub-order-volume-at-scale-a966c2f901d2) `Predictive ML`\n- 📊 **[2021]** [“I See Tacos In Your Future”: Order Volume Forecasting at Grubhub](https://bytes.grubhub.com/i-see-tacos-in-your-future-order-volume-forecasting-at-grubhub-44d47ad08d5b) `Predictive ML`\n\n### 🏢 Instacart\n\n- 🧠 **[2025]** [Scaling Catalog Attribute Extraction with Multi-modal LLMs](https://tech.instacart.com/multi-modal-catalog-attribute-extraction-platform-at-instacart-b9228754a527) `Generative AI \u0026 LLM`\n- 👁️ **[2025]** [Introducing PIXEL: Instacart’s Unified Image Generation Platform](https://tech.instacart.com/introducing-pixel-instacarts-unified-image-generation-platform-6d7dd0efe4c1) `CV`\n- 🧠 **[2025]** [Turbocharging Customer Support Chatbot Development with LLM-Based Automated Evaluation](https://tech.instacart.com/turbocharging-customer-support-chatbot-development-with-llm-based-automated-evaluation-6a269aae56b2) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Building The Intent Engine: How Instacart is Revamping Query Understanding with LLMs](https://tech.instacart.com/building-the-intent-engine-how-instacart-is-revamping-query-understanding-with-llms-3ac8051ae7ac) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Enhancing FoodStorm with AI Image Generation](https://tech.instacart.com/enhancing-foodstorm-with-ai-image-generation-d76a74867fa4) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Bandits for Marketing Optimization](https://tech.instacart.com/bandits-for-marketing-optimization-f5a63b9bfaa7) `Predictive ML`\n- 📊 **[2024]** [Optimizing search relevance at Instacart using hybrid retrieval](https://tech.instacart.com/optimizing-search-relevance-at-instacart-using-hybrid-retrieval-88cb579b959c) `Predictive ML`\n- 🧠 **[2024]** [Supercharging Discovery in Search with LLMs](https://tech.instacart.com/supercharging-discovery-in-search-with-llms-556c585d4720) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Sequence models for Contextual Recommendations at Instacart](https://tech.instacart.com/sequence-models-for-contextual-recommendations-at-instacart-93414a28e70c) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Real-time Fraud Detection with Yoda and ClickHouse](https://tech.instacart.com/real-time-fraud-detection-with-yoda-and-clickhouse-bd08e9dbe3f4) `Predictive ML`\n- 📊 **[2024]** [Optimizing at the Edge: Using Regression Discontinuity Designs to Power Decision-Making](https://tech.instacart.com/optimizing-at-the-edge-using-regression-discontinuity-designs-to-power-decision-making-51e296615046) `Predictive ML`\n- 📊 **[2024]** [How Instacart Uses Machine Learning to Suggest Replacements for Out-of-Stock Products](https://tech.instacart.com/how-instacart-uses-machine-learning-to-suggest-replacements-for-out-of-stock-products-8f80d03bb5af) `Predictive ML`\n- 📊 **[2023]** [How Instacart Modernized the Prediction of Real Time Availability for Hundreds of Millions of Items While Saving Costs](https://tech.instacart.com/how-instacart-modernized-the-prediction-of-real-time-availability-for-hundreds-of-millions-of-items-59b2a82c89fe) `Predictive ML`\n- 📊 **[2023]** [Instacart’s Item Availability Architecture: Solving for scale and consistency](https://tech.instacart.com/instacarts-item-availability-architecture-solving-for-scale-and-consistency-f5661acb20a6) `Predictive ML`\n- 🧠 **[2023]** [Monte Carlo, Puppetry and Laughter: The Unexpected Joys of Prompt Engineering](https://tech.instacart.com/monte-carlo-puppetry-and-laughter-the-unexpected-joys-of-prompt-engineering-4b9272e0c4eb) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [One model to serve them all](https://tech.instacart.com/one-model-to-serve-them-all-0eb6bf60b00d) `Predictive ML`\n- 📊 **[2023]** [How Instacart’s Item Availability Evolved Over the Pandemic](https://www.instacart.com/company/how-its-made/how-instacarts-item-availability-evolved-over-the-pandemic/) `Predictive ML`\n- 🧠 **[2023]** [Scaling Productivity with Ava — Instacart’s Internal AI Assistant](https://tech.instacart.com/scaling-productivity-with-ava-instacarts-internal-ai-assistant-ed7f02558d84) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Using Contextual Bandit models in large action spaces at Instacart](https://tech.instacart.com/using-contextual-bandit-models-in-large-action-spaces-at-instacart-cb7ab4d8fa4f) `Predictive ML`\n- 💬 **[2022]** [How Instacart Uses Machine Learning-Driven Autocomplete to Help People Fill Their Carts](https://tech.instacart.com/how-instacart-uses-machine-learning-driven-autocomplete-to-help-people-fill-their-carts-9bc56d22bafb) `NLP`\n- 📊 **[2022]** [How Instacart Uses Embeddings to Improve Search Relevance](https://tech.instacart.com/how-instacart-uses-embeddings-to-improve-search-relevance-e569839c3c36) `Predictive ML`\n- 📊 **[2022]** [Personalizing Recommendations for a Learning User](https://www.instacart.com/company/how-its-made/personalizing-recommendations-for-a-learning-user/) `Predictive ML`\n- 📊 **[2019]** [Modeling the unseen](https://tech.instacart.com/modeling-the-unseen-6a51c9a02430) `Predictive ML`\n- 📊 **[2018]** [Predicting the real-time availability of 200 million grocery items](https://tech.instacart.com/predicting-real-time-availability-of-200-million-grocery-items-in-us-canada-stores-61f43a16eafe) `Predictive ML`\n- 📊 **[2017]** [Space, Time and Groceries](https://tech.instacart.com/space-time-and-groceries-a315925acf3a) `Predictive ML`\n\n### 🏢 Lyft\n\n- 📊 **[2025]** [Real-Time Spatial Temporal Forecasting @ Lyft](https://eng.lyft.com/real-time-spatial-temporal-forecasting-lyft-fa90b3f3ec24) `Predictive ML`\n- 📊 **[2024]** [ETA (Estimated Time of Arrival) Reliability at Lyft](https://eng.lyft.com/eta-estimated-time-of-arrival-reliability-at-lyft-d4ca2720bda8) `Predictive ML`\n- 📊 **[2023]** [The Recommendation System at Lyft](https://eng.lyft.com/the-recommendation-system-at-lyft-67bc9dcc1793) `Predictive ML`\n- 📊 **[2022]** [Pricing at Lyft](https://eng.lyft.com/pricing-at-lyft-8a4022065f8b) `Predictive ML`\n- 📊 **[2022]** [Causal Forecasting at Lyft (Part 1)](https://eng.lyft.com/causal-forecasting-at-lyft-part-1-14cca6ff3d6d) `Predictive ML`\n- 📊 **[2022]** [Causal Forecasting at Lyft (Part 2)](https://eng.lyft.com/causal-forecasting-at-lyft-part-2-418f1febca5a) `Predictive ML`\n- 📊 **[2020]** [How Lyft predicts a rider’s destination for better in-app experience](https://eng.lyft.com/how-lyft-predicts-your-destination-with-attention-791146b0a439) `Predictive ML`\n- 📊 **[2019]** [Detecting Stop Signs and Traffic Signals: Deep Learning at Lyft Mapping](https://eng.lyft.com/detecting-stop-signs-and-traffic-signals-deep-learning-at-lyft-mapping-75bac609c231) `Predictive ML`\n- 📊 **[2019]** [How Lyft Creates Hyper-Accurate Maps from Open-Source Maps and Real-Time Data](https://eng.lyft.com/how-lyft-creates-hyper-accurate-maps-from-open-source-maps-and-real-time-data-8dcf9abdd46a) `Predictive ML`\n- 📊 **[2019]** [Making cohort-based long-term forecasts at Lyft](https://eng.lyft.com/making-long-term-forecasts-at-lyft-fac475b3ba52) `Predictive ML`\n- 📊 **[2019]** [Building Lyft’s Marketing Automation Platform](https://eng.lyft.com/lyft-marketing-automation-b43b7b7537cc) `Predictive ML`\n- 📊 **[2018]** [Fingerprinting fraudulent behavior](https://eng.lyft.com/fingerprinting-fraudulent-behavior-6663d0264fad) `Predictive ML`\n- 📊 **[2018]** [From shallow to deep learning in fraud](https://eng.lyft.com/from-shallow-to-deep-learning-in-fraud-9dafcbcef743?gi=6e6a315e3f92) `Predictive ML`\n- 📊 **[2018]** [Empowering personalized marketing with machine learning](https://eng.lyft.com/empowering-personalized-marketing-with-machine-learning-fd36e6bdeca6) `Predictive ML`\n\n### 🏢 Mercado Libre\n\n- 📊 **[2022]** [Predicting package dimensions based on a similarity model at Mercado Libre](https://medium.com/mercadolibre-tech/predicting-package-dimensions-based-on-a-similarity-model-at-mercado-libre-d64a9dd4351d) `Predictive ML`\n\n### 🏢 Oda\n\n- 📊 **[2022]** [How we went from zero insight to predicting service time with a machine learning model — Part 2/2](https://medium.com/oda-product-tech/how-we-went-from-zero-insight-to-predicting-service-time-with-a-machine-learning-model-part-2-2-ad8b0c3e4838) `Predictive ML`\n- 📊 **[2021]** [How we went from zero insight to predicting service time with a machine learning model — Part 1](https://medium.com/oda-product-tech/how-we-went-from-zero-insight-to-predicting-service-time-with-a-machine-learning-model-part-1-516b9545d02f) `Predictive ML`\n\n### 🏢 Picnic\n\n- 👁️ **[2025]** [Adding Eyes to Picnic’s Automated Warehouses](https://blog.picnic.nl/adding-eyes-to-picnics-automated-warehouses-8b6c70613e2f) `CV`\n- 📊 **[2025]** [Solving the weekly menu puzzle pt.2: recommendations at Picnic](https://blog.picnic.nl/solving-the-weekly-menu-puzzle-pt-2-recommendations-at-picnic-b48a4c434159) `Predictive ML`\n- 👁️ **[2025]** [Adding Eyes to Picnic’s Automated Warehouses Part 2](https://blog.picnic.nl/adding-eyes-to-picnics-automated-warehouses-part-2-b283dd7f7de6) `CV`\n- 📊 **[2024]** [Solving the weekly menu puzzle: recommendations at Picnic](https://blog.picnic.nl/solving-the-weekly-menu-puzzle-recommendations-at-picnic-42da16b281ad) `Predictive ML`\n- 📊 **[2024]** [Generating your shopping list with AI: recommendations at Picnic](https://blog.picnic.nl/generating-your-shopping-list-with-ai-recommendations-at-picnic-300e716241db) `Predictive ML`\n- 📊 **[2024]** [Under the hood of Picnic’s demand forecasting model: A Deep Dive into the Temporal Fusion Transformer](https://blog.picnic.nl/under-the-hood-of-picnics-demand-forecasting-model-a-deep-dive-into-the-temporal-fusion-e281604d65a5) `Predictive ML`\n- 🧠 **[2024]** [Enhancing Search Retrieval with Large Language Models (LLMs)](https://blog.picnic.nl/enhancing-search-retrieval-with-large-language-models-llms-7c3748b26d72) `Generative AI \u0026 LLM`\n- 💬 **[2024]** [How we broke customer support language barriers without breaking production](https://blog.picnic.nl/how-picnic-migrated-ml-architectures-without-sacrificing-operational-continuity-271c0e04014a) `NLP`\n- 📊 **[2023]** [Running demand forecasting machine learning models at scale](https://blog.picnic.nl/running-demand-forecasting-machine-learning-models-at-scale-bd058c9d4aa7) `Predictive ML`\n- 📊 **[2020]** [Optimal drop times using machine learning](https://blog.picnic.nl/the-trade-off-between-efficiency-and-being-on-time-optimizing-drop-times-using-machine-learning-d3f6fb1b0f31) `Predictive ML`\n\n### 🏢 Swiggy\n\n- 👁️ **[2025]** [Enhancing Brand Visibility and Trust with On device ML models: A Journey at Swiggy](https://bytes.swiggy.com/enhancing-brand-visibility-and-trust-with-on-device-ml-models-a-journey-at-swiggy-e3e626f96c52) `CV`\n- 🤖 **[2025]** [Hermes V3: Building Swiggy’s Conversational AI Analyst](https://bytes.swiggy.com/hermes-v3-building-swiggys-conversational-ai-analyst-a41057a2279d) `AI agents`\n- 🧠 **[2024]** [Hermes: A Text-to-SQL solution at Swiggy](https://bytes.swiggy.com/hermes-a-text-to-sql-solution-at-swiggy-81573fb4fb6e) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Reflecting on a year of generative AI at Swiggy: A brief review of achievements, learnings, and insights](https://bytes.swiggy.com/reflecting-on-a-year-of-generative-ai-at-swiggy-a-brief-review-of-achievements-learnings-and-13a9671dc624) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Improving search relevance in hyperlocal food delivery using (small) language models](https://bytes.swiggy.com/improving-search-relevance-in-hyperlocal-food-delivery-using-small-language-models-ecda2acc24e6) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Utilizing DevNet with Variational Loss for Fraud Detection in Hyperlocal Food Delivery](https://bytes.swiggy.com/utilizing-devnet-with-variational-loss-for-fraud-detection-in-hyperlocal-food-delivery-19e72999acfb) `Predictive ML`\n- 📊 **[2024]** [New-User Product Recommendations for Q-Commerce via Hierarchical Cross-Domain Learning](https://bytes.swiggy.com/new-user-product-recommendations-for-q-commerce-via-hierarchical-cross-domain-learning-0a7f97b25405) `Predictive ML`\n- 📊 **[2024]** [Address Correction for Q-Commerce Part 1: Location Inaccuracy Classifier](https://bytes.swiggy.com/address-correction-for-q-commerce-part-1-location-inaccuracy-classifier-e72b88a33d2f) `Predictive ML`\n- 📊 **[2024]** [Address Correction for Q-Commerce Part 2: Geocoder](https://bytes.swiggy.com/address-correction-for-q-commerce-part-2-geocoder-3bbd6ee828c0) `Predictive ML`\n- 🧠 **[2023]** [Swiggy’s Generative AI Journey: A Peek Into the Future](https://bytes.swiggy.com/swiggys-generative-ai-journey-a-peek-into-the-future-2193c7166d9a) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [How GenAI Codegen tools are helping us deliver convenience quicker](https://bytes.swiggy.com/how-genai-codegen-tools-are-helping-us-deliver-convenience-quicker-133248a0c714) `Predictive ML`\n- 📊 **[2023]** [Predicting Food Delivery Time at Cart](https://bytes.swiggy.com/predicting-food-delivery-time-at-cart-cda23a84ba63) `Predictive ML`\n- 📊 **[2023]** [How ML Powers — When is my order coming? — Part II](https://bytes.swiggy.com/how-ml-powers-when-is-my-order-coming-part-ii-eae83575e3a9) `Predictive ML`\n- 📊 **[2023]** [Where is my order? — Part I](https://bytes.swiggy.com/how-ml-powers-when-is-my-order-coming-part-i-4ef24eae70da) `Predictive ML`\n- 📊 **[2023]** [Building a mind reader at Swiggy using Data Science](https://bytes.swiggy.com/building-a-mind-reader-at-swiggy-using-data-science-5a5c38aa6c17) `Predictive ML`\n- 📊 **[2022]** [Using deep learning to detect dissonance between address text and location](https://bytes.swiggy.com/using-deep-learning-to-detect-dissonance-between-address-text-and-location-4b228bc2c3fb) `Predictive ML`\n- 📊 **[2021]** [DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery](https://bytes.swiggy.com/defraudnet-an-end-to-end-weak-supervision-framework-to-detect-fraud-in-online-food-delivery-22366ddce461) `Predictive ML`\n- 📊 **[2021]** [Using Deep Learning for Ranking in Dish Search](https://bytes.swiggy.com/using-deep-learning-for-ranking-in-dish-search-4df2772dddce) `Predictive ML`\n- 📊 **[2021]** [Learning To Rank Restaurants](https://bytes.swiggy.com/learning-to-rank-restaurants-c6a69ba4b330) `Predictive ML`\n- 📊 **[2021]** [Learning to Predict Two-Wheeler Travel Distance](https://bytes.swiggy.com/learning-to-predict-two-wheeler-travel-distance-752d836d741d) `Predictive ML`\n\n### 🏢 Uber\n\n- 🧠 **[2025]** [Fixrleak: Fixing Java Resource Leaks with GenAI](https://www.uber.com/en-GB/blog/fixrleak-fixing-java-resource-leaks-with-genai/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Advancing Invoice Document Processing at Uber using GenAI](https://www.uber.com/en-IN/blog/advancing-invoice-document-processing-using-genai/) `Generative AI \u0026 LLM`\n- 🤖 **[2025]** [Enhanced Agentic-RAG: What If Chatbots Could Deliver Near-Human Precision?](https://www.uber.com/en-GB/blog/enhanced-agentic-rag) `AI agents`\n- 📊 **[2025]** [Reinforcement Learning for Modeling Marketplace Balance](https://www.uber.com/en-IN/blog/reinforcement-learning-for-modeling-marketplace-balance/) `Predictive ML`\n- 🤖 **[2025]** [Unlocking Financial Insights with Finch: Uber’s Conversational AI Data Agent](https://www.uber.com/en-IN/blog/unlocking-financial-insights-with-finch/) `AI agents`\n- 🧠 **[2025]** [uReview: Scalable, Trustworthy GenAI for Code Review at Uber](https://www.uber.com/en-IN/blog/ureview/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [PerfInsights: Detecting Performance Optimization Opportunities in Go Code using Generative AI](https://www.uber.com/en-IN/blog/perfinsights/) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [Enhancing Personalized CRM Communication with Contextual Bandit Strategies](https://www.uber.com/en-IN/blog/enhancing-personalized-crm/) `Predictive ML`\n- 🧠 **[2025]** [Evolution and Scale of Uber’s Delivery Search Platform](https://www.uber.com/en-GB/blog/evolution-and-scale-of-ubers-delivery-search-platform/?uclick_id=0a73d271-32e7-4b77-9697-a587a4c8d9fe) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [PerfInsights: Detecting Performance Optimization Opportunities in Go Code using Generative AI](https://www.uber.com/en-GB/blog/perfinsights/?uclick_id=0a73d271-32e7-4b77-9697-a587a4c8d9fe) `Generative AI \u0026 LLM`\n- 🔍 **[2025]** [Enhanced Agentic-RAG: What If Chatbots Could Deliver Near-Human Precision?](https://www.uber.com/en-GB/blog/enhanced-agentic-rag/) `RAG`\n- 📊 **[2025]** [Forecasting Models to Improve Driver Availability at Airports](https://www.uber.com/en-GB/blog/forecasting-models-to-improve-availability-at-airports/) `Predictive ML`\n- 🧠 **[2025]** [Requirement Adherence: Boosting Data Labeling Quality Using LLMs](https://www.uber.com/en-GB/blog/requirement-adherence-boosting-data-labeling-quality-using-llms/?uclick_id=0a73d271-32e7-4b77-9697-a587a4c8d9fe) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [uReview: Scalable, Trustworthy GenAI for Code Review at Uber](https://www.uber.com/en-GB/blog/ureview/?uclick_id=0a73d271-32e7-4b77-9697-a587a4c8d9fe) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [Enabling Deep Model Explainability with Integrated Gradients at Uber](https://www.uber.com/en-GB/blog/enabling-deep-model-explainability-with-integrated-gradients/?uclick_id=0a73d271-32e7-4b77-9697-a587a4c8d9fe) `Predictive ML`\n- 🧠 **[2024]** [QueryGPT – Natural Language to SQL Using Generative AI](https://www.uber.com/en-IN/blog/query-gpt/) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Genie: Uber’s Gen AI On-Call Copilot](https://www.uber.com/en-HR/blog/genie-ubers-gen-ai-on-call-copilot/?uclick_id=92508acc-3a86-4fcc-bc5f-ba1799e3055e) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Personalized Marketing at Scale: Uber’s Out-of-App Recommendation System](https://www.uber.com/en-GB/blog/personalized-marketing-at-scale/) `Predictive ML`\n- 📊 **[2024]** [Stopping Uber Fraudsters Through Risk Challenges](https://www.uber.com/en-GB/blog/stopping-uber-fraudsters-through-risk-challenges/) `Predictive ML`\n- 🧠 **[2024]** [DragonCrawl: Generative AI for High-Quality Mobile Testing](https://www.uber.com/en-GB/blog/generative-ai-for-high-quality-mobile-testing/) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [DataK9: Auto-categorizing an exabyte of data at field level through AI/ML](https://www.uber.com/en-GB/blog/auto-categorizing-data-through-ai-ml/) `Predictive ML`\n- 📊 **[2023]** [uVitals – An Anomaly Detection \u0026 Alerting System](https://www.uber.com/en-GB/blog/uvitals-an-anomaly-detection-alerting-system/) `Predictive ML`\n- 📊 **[2023]** [Demand and ETR Forecasting at Airports](https://www.uber.com/en-GB/blog/demand-and-etr-forecasting-at-airports/) `Predictive ML`\n- 📊 **[2023]** [Accelerating Advertising Optimization: Unleashing the Power of Ads Simulation](https://www.uber.com/en-SG/blog/unleashing-the-power-of-ads-simulation/?uclick_id=92508acc-3a86-4fcc-bc5f-ba1799e3055e) `Predictive ML`\n- 📊 **[2023]** [Risk Entity Watch – Using Anomaly Detection to Fight Fraud](https://www.uber.com/en-IN/blog/risk-entity-watch/?uclick_id=9c4355d3-795f-4b1d-b18e-4b8b4c8ed29f) `Predictive ML`\n- 👁️ **[2022]** [Uber’s Real-Time Document Check](https://www.uber.com/en-GB/blog/ubers-real-time-document-check/) `CV`\n- 📊 **[2022]** [DeepETA: How Uber Predicts Arrival Times Using Deep Learning](https://www.uber.com/en-GB/blog/deepeta-how-uber-predicts-arrival-times/) `Predictive ML`\n- 📊 **[2022]** [How Uber Optimizes the Timing of Push Notifications using ML and Linear Programming](https://www.uber.com/en-US/blog/how-uber-optimizes-push-notifications-using-ml/) `Predictive ML`\n- 📊 **[2022]** [Project RADAR: Intelligent Early Fraud Detection System with Humans in the Loop](https://www.uber.com/en-GB/blog/project-radar-intelligent-early-fraud-detection/) `Predictive ML`\n- 📊 **[2021]** [Applying Machine Learning in Internal Audit with Sparsely Labeled Data](https://www.uber.com/en-GB/blog/ml-internal-audit/) `Predictive ML`\n\n### 🏢 iFood\n\n- 🤖 **[2025]** [From Zero to AILO](https://www.youtube.com/watch?v=uevJBcXKLlQ) `AI agents`\n- 📊 **[2021]** [Recommendation @ iFood](https://medium.com/ifood-engineering/recommendation-ifood-88d60fa8bc6a) `Predictive ML`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"e-commerce-and-retail\"\u003e\u003c/a\u003e\n\n## 🛒 E-commerce and retail\n\n\u003e **152 case studies** from **29 companies**\n\n### 🏢 Amazon\n\n- 📊 **[2021]** [Using learning-to-rank to precisely locate where to deliver packages](https://www.amazon.science/blog/using-learning-to-rank-to-precisely-locate-where-to-deliver-packages) `Predictive ML`\n\n### 🏢 Asos\n\n- 🧠 **[2025]** [Introducing Test-Driven Vibe Development](https://medium.com/asos-techblog/introducing-test-driven-vibe-development-0effe6430691) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Transforming Recommendations at ASOS](https://medium.com/asos-techblog/transforming-recommendations-at-asos-254b95c6a07a) `Predictive ML`\n- 📊 **[2022]** [Optimizing Markdown in Fashion E-Commerce with Machine Learning](https://medium.com/asos-techblog/optimizing-markdown-in-fashion-e-commerce-with-machine-learning-9f173be08ace) `Predictive ML`\n- 📊 **[2022]** [Getting personal at ASOS](https://medium.com/asos-techblog/getting-personal-at-asos-bc1599e0c2a9) `Predictive ML`\n\n### 🏢 Autotrader\n\n- 👁️ **[2024]** [So many labels, so little time; accelerating our image labelling process](https://engineering.autotrader.co.uk/2024/05/31/image-labels.html) `CV`\n- 📊 **[2023]** [Demonstrating the Value of our Packages](https://engineering.autotrader.co.uk/2023/03/24/demonstrating-the-value-of-our-advertising-packages.html) `Predictive ML`\n- 📊 **[2022]** [Real-Time Personalisation of Search Results with Auto Trader's Customer Data Platform](https://engineering.autotrader.co.uk/2022/11/23/real-time-personalisation-of-search-results-with-auto-traders-customer-data-platform.html) `Predictive ML`\n\n### 🏢 Cars24\n\n- 📊 **[2023]** [Personalized buyer listings at CARS24 — an overview](https://medium.com/cars24-data-science-blog/personalized-buyer-listings-at-cars24-an-overview-83d8428bd7d9) `Predictive ML`\n- 📊 **[2023]** [Engine assessment @CARS24 : Sound analysis using Signal Processing \u0026 CNN](https://medium.com/cars24-data-science-blog/engine-assessment-cars24-sound-analysis-using-signal-processing-cnn-c08f98d0b694) `Predictive ML`\n- 📊 **[2023]** [ML driven dynamic pricing @ CARS24 — Part 1](https://medium.com/cars24-data-science-blog/how-cars24-uses-machine-learning-for-dynamic-pricing-of-used-cars-part-1-51fee52860d1) `Predictive ML`\n- 👁️ **[2022]** [Blur Classifier: Image Quality Detector](https://medium.com/cars24-data-science-blog/blur-classifier-image-quality-detector-7c1de5ff8e59) `CV`\n\n### 🏢 Cherrypick\n\n- 🧠 **[2024]** [How to Build a Robust LLM Application](https://www.chrismdp.com/how-to-build-a-robust-llm-application/) `Generative AI \u0026 LLM`\n\n### 🏢 Coches.net\n\n- 🧠 **[2024]** [From Filters to Phrases: Our AI Revolution in Car Search](https://medium.com/adevinta-tech-blog/from-filters-to-phrases-our-ai-revolution-in-car-search-2d7c73ca4886) `Generative AI \u0026 LLM`\n\n### 🏢 Cookidoo\n\n- 📊 **[2022]** [Building A Recipe Recommender System For the Thermomix on Cookidoo – Part 1](https://www.alexanderthamm.com/de/blog/building-a-recipe-recommender-system-for-the-thermomix-on-cookidoo/) `Predictive ML`\n\n### 🏢 Coupang\n\n- 🧠 **[2024]** [Accelerating Coupang’s AI Journey with LLMs](https://medium.com/coupang-engineering/accelerating-coupangs-ai-journey-with-llms-2817d55004d3) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Optimizing the inbound process with a machine learning model](https://medium.com/coupang-engineering/optimizing-the-inbound-process-with-a-machine-learning-model-2db48bbbc304) `Predictive ML`\n- 📊 **[2022]** [Unsupervised competing neural language model for word segmentation](https://medium.com/coupang-engineering/unsupervised-competing-neural-language-model-for-word-segmentation-12becc1015bf) `Predictive ML`\n- 📊 **[2022]** [Overcoming food delivery challenges with data science](https://medium.com/coupang-engineering/overcoming-food-delivery-challenges-with-data-science-6420cac1d59) `Predictive ML`\n- 📊 **[2022]** [Matching duplicate items to improve catalog quality](https://medium.com/coupang-engineering/matching-duplicate-items-to-improve-catalog-quality-ca4abc827f94) `Predictive ML`\n\n### 🏢 Doordash\n\n- 📊 **[2021]** [Managing Supply and Demand Balance Through Machine Learning](https://doordash.engineering/2021/06/29/managing-supply-and-demand-balance-through-machine-learning/) `Predictive ML`\n\n### 🏢 Ebay\n\n- 🧠 **[2025]** [Scaling Large Language Models for e-Commerce: The Development of a Llama-Based Customized LLM](https://innovation.ebayinc.com/stories/scaling-large-language-models-for-e-commerce-the-development-of-a-llama-based-customized-llm-for-e-commerce/) `Generative AI \u0026 LLM`\n- 🤖 **[2025]** [Mercury: Agentic AI Platform for LLM Powered Recommendation Experiences at eBay](https://www.linkedin.com/pulse/mercury-agentic-ai-platform-llm-powered-experiences-ebay-chowdhury-kka8e/) `AI agents`\n- 🧠 **[2025]** [Enhancing eBay’s Visual Shopping Experience With Automated Image Generation And Optimization For Themes and Categories](https://www.linkedin.com/pulse/enhancing-ebays-visual-shopping-experience-automated-image-galsurkar-9pgle/) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Cutting Through the Noise: Three Things We've Learned About Generative AI and Developer Productivity](https://innovation.ebayinc.com/tech/features/cutting-through-the-noise-three-things-weve-learned-about-generative-ai-and-developer-productivity/) `Generative AI \u0026 LLM`\n- 📊 **[2022]** [Building a Deep Learning Based Retrieval System for Personalized Recommendations](https://tech.ebayinc.com/engineering/building-a-deep-learning-based-retrieval-system-for-personalized-recommendations/) `Predictive ML`\n\n### 🏢 Etsy\n\n- 🧠 **[2025]** [Understanding Etsy’s Vast Inventory with LLMs](https://www.etsy.com/codeascraft/understanding-etsyas-vast-inventory-with-llms) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Building Etsy Buyer Profiles with LLMs](https://www.etsy.com/codeascraft/building-etsy-buyer-profiles-with-llms) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Machine Learning in Content Moderation at Etsy](https://www.etsy.com/codeascraft/machine-learning-in-content-moderation-at-etsy?) `Predictive ML`\n- 👁️ **[2024]** [Efficient Visual Representation Learning And Evaluation](https://www.etsy.com/codeascraft/efficient-visual-representation-learning-and-evaluation) `CV`\n- 📊 **[2023]** [Leveraging Real-Time User Actions to Personalize Etsy Ads](https://www.etsy.com/uk/codeascraft/leveraging-real-time-user-actions-to-personalize-etsy-ads) `Predictive ML`\n- 📊 **[2023]** [Leveraging Real-Time User Actions to Personalize Etsy Ads](https://arxiv.org/pdf/2302.01255.pdf) `Predictive ML`\n- 👁️ **[2023]** [From Image Classification to Multitask Modeling: Building Etsy’s Search by Image Feature](https://www.etsy.com/codeascraft/from-image-classification-to-multitask-modeling-building-etsys-search-by-image-feature) `CV`\n- 📊 **[2023]** [How We Built a Multi-Task Canonical Ranker for Recommendations at Etsy](https://www.etsy.com/uk/codeascraft/how-we-built-a-multi-task-canonical-ranker-for-recommendations-at-etsy) `Predictive ML`\n- 📊 **[2022]** [Deep Learning for Search Ranking at Etsy](https://www.etsy.com/uk/codeascraft/deep-learning-for-search-ranking-at-etsy) `Predictive ML`\n- 📊 **[2020]** [Bringing Personalized Search to Etsy](https://www.etsy.com/codeascraft/bringing-personalized-search-to-etsy/) `Predictive ML`\n\n### 🏢 Faire\n\n- 🤖 **[2025]** [Swarm-coding: agentic development with multiple background agents](https://craft.faire.com/swarm-coding-agentic-development-with-multiple-background-agents-3549adc7460d) `AI agents`\n- 🤖 **[2025]** [Transforming wholesale with AI: the sequel (now with more agents)](https://craft.faire.com/transforming-wholesale-with-ai-the-sequel-now-with-more-agents-9542f257dd45) `AI agents`\n- 🧠 **[2024]** [Fine-tuning Llama3 to measure semantic relevance in search](https://craft.faire.com/fine-tuning-llama3-to-measure-semantic-relevance-in-search-86a7b13c24ea) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Embedding-Based Retrieval: Our Journey and Learnings around Semantic Search at Faire](https://craft.faire.com/embedding-based-retrieval-our-journey-and-learnings-around-semantic-search-at-faire-2aa44f969994) `Predictive ML`\n- 🧠 **[2024]** [Automated code reviews with LLMs](https://craft.faire.com/automated-code-reviews-with-llms-cf2cc51bb6d3) `Generative AI \u0026 LLM`\n- 📊 **[2022]** [Real-time ranking at Faire part 2: the feature store](https://craft.faire.com/real-time-ranking-at-faire-part-2-the-feature-store-3f1013d3fe5d) `Predictive ML`\n- 📊 **[2021]** [Building Faire’s new marketplace ranking infrastructure](https://craft.faire.com/building-faires-new-marketplace-ranking-infrastructure-a53bf938aba0) `Predictive ML`\n\n### 🏢 Flipkart\n\n- 🧠 **[2025]** [One Prompt To Rule Them All: LLMs For Opinion Summary Evaluation](https://blog.flipkart.tech/one-prompt-to-rule-them-all-llms-for-opinion-summary-evaluation-d5dd4eb6f225) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [The Science of Unified Ranking: Integrating Ads and Organic Recommendations](https://blog.flipkart.tech/the-science-of-unified-ranking-integrating-ads-and-organic-recommendations-8cc24113ef21) `Predictive ML`\n- 🧠 **[2025]** [The Future of E-commerce: How AI is Learning to Describe Products with Less Data](https://blog.flipkart.tech/the-future-of-e-commerce-how-ai-is-learning-to-describe-products-with-less-data-8dfbf05f83a1) `Generative AI \u0026 LLM`\n\n### 🏢 Kingfisher Technology\n\n- 💬 **[2023]** [Uncovering Hidden Insights in Customer Feedback](https://medium.com/kingfisher-technology/uncovering-hidden-insights-in-customer-feedback-824daa16fa37) `NLP`\n\n### 🏢 Leboncoin\n\n- 🧠 **[2025]** [From blank page to perfect pitch: how AI is transforming ads at leboncoin](https://medium.com/leboncoin-tech-blog/from-blank-page-to-perfect-pitch-how-ai-is-transforming-ads-at-leboncoin-eeff51c3bf42) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Once Upon a Chat Bot: The Ada Story at leboncoin](https://medium.com/leboncoin-tech-blog/once-upon-a-chat-bot-the-ada-story-at-leboncoin-1a4c52000d82) `Generative AI \u0026 LLM`\n- 🧠 **[2023]** [Serving Large Language Models to improve Search Relevance at leboncoin](https://medium.com/leboncoin-tech-blog/serving-large-language-models-to-improve-search-relevance-at-leboncoin-2a364e5b6f76) `Generative AI \u0026 LLM`\n\n### 🏢 ManoMano\n\n- 📊 **[2025]** [Compatibility Challenges in Recommendation System](https://medium.com/manomano-tech/compatibility-challenges-in-recommendation-system-4d233c676d35) `Predictive ML`\n\n### 🏢 Mercado Libre\n\n- 🧠 **[2025]** [The New Financial Babel: Teaching AI to Speak Money in LATAM](https://medium.com/mercadolibre-tech/la-nueva-babel-financiera-ense%C3%B1ar-a-la-ia-a-hablar-dinero-en-latinoam%C3%A9rica-4605235e3aac) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [The billion-dollar puzzle: Optimizing collateral allocation management with AI](https://medium.com/mercadolibre-tech/the-billion-dollar-puzzle-optimizing-collateral-allocation-management-with-ai-87cb5e6cf975) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Tale of a Prompt Development](https://medium.com/mercadolibre-tech/tale-of-a-prompt-development-c133081bca1e) `Generative AI \u0026 LLM`\n- 🔍 **[2025]** [How we are using AI in Mercado Libre’s accessibility team](https://medium.com/mercadolibre-tech/how-we-are-using-ai-in-mercado-libres-accessibility-team-e960b83283a9) `RAG`\n- 🔍 **[2024]** [Beyond the Hype: Real-World Lessons and Insights from Working with Large Language Models](https://medium.com/mercadolibre-tech/beyond-the-hype-real-world-lessons-and-insights-from-working-with-large-language-models-6d637e39f8f8) `RAG`\n- 📊 **[2024]** [Unlocking the Power of Lookalike Audiences: Simplifying Complexity](https://medium.com/mercadolibre-tech/unlocking-the-power-of-lookalike-audiences-simplifying-complexity-74275f537e20) `Predictive ML`\n- 📊 **[2022]** [Unsupervised feature selection with eigenvalue clipping and PCA](https://medium.com/mercadolibre-tech/unsupervised-feature-selection-with-eigenvalue-clipping-and-pca-7ce2936aed3a) `Predictive ML`\n- 📊 **[2021]** [Marketplace Forecasting: Sales or Demand? Why not both? Let’s find out!](https://medium.com/mercadolibre-tech/global-time-series-forecasting-models-for-item-level-demand-and-sales-forecasts-in-our-marketplace-aee2956957ae) `Predictive ML`\n- 📊 **[2021]** [How we design our push notifications strategy so that customers interact with our product](https://medium.com/mercadolibre-tech/how-we-design-our-push-notifications-strategy-so-that-customers-interact-with-our-product-fda8a3c4be01) `Predictive ML`\n- 📊 **[2021]** [Causal Inference — Estimating Long-term Engagement](https://medium.com/mercadolibre-tech/causal-inference-estimating-long-term-engagement-fac517929073) `Predictive ML`\n\n### 🏢 Nordstrom\n\n- 👁️ **[2021]** [AI-Created Outfits](https://medium.com/tech-at-nordstrom/ai-created-outfits-9529300a1af3) `CV`\n\n### 🏢 OLX\n\n- 📊 **[2025]** [Hybrid Search — Where Keywords Meet Vectors, Enabling Classifieds Discovery](https://tech.olx.com/hybrid-search-where-keywords-meet-vectors-enabling-classifieds-discovery-b7c383fe4fc4) `Predictive ML`\n- 🧠 **[2024]** [Extracting Job Roles in Job Ads: A Journey with Generative AI](https://tech.olx.com/extracting-job-roles-in-job-ads-a-journey-with-generative-ai-e8b8cf399659) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Machine Learning for Delivery Time Estimation](https://tech.olx.com/machine-learning-for-delivery-time-estimation-1-591c8df849a0) `Predictive ML`\n- 📊 **[2021]** [Item2Vec: Neural Item Embeddings to enhance recommendations](https://tech.olx.com/item2vec-neural-item-embeddings-to-enhance-recommendations-1fd948a6f293) `Predictive ML`\n- 👁️ **[2020]** [Fighting fraud with Triplet Loss](https://tech.olx.com/fighting-fraud-with-triplet-loss-86e5f79c7a3e) `CV`\n\n### 🏢 Ocado\n\n- 📊 **[2021]** [Finding the sweet spot](https://careers.ocadogroup.com/blogs/careers-blogs/our-technologies/finding-the-sweet-spot) `Predictive ML`\n\n### 🏢 Shopify\n\n- 📊 **[2025]** [Evolution of Product Classification at Shopify: From Categories to Comprehensive Product Understanding](https://shopify.engineering/evolution-product-classification) `Predictive ML`\n- 🧠 **[2025]** [Leveraging Multimodal LLMs for Shopify’s Global Catalogue](https://shopify.engineering/leveraging-multimodal-llms) `Generative AI \u0026 LLM`\n- 🤖 **[2025]** [Building production-ready agentic systems: Lessons from Shopify Sidekick](https://shopify.engineering/building-production-ready-agentic-systems) `AI agents`\n- 🤖 **[2025]** [Beyond classification: How AI agents are evolving Shopify's product taxonomy at scale](https://shopify.engineering/product-taxonomy-at-scale) `AI agents`\n- 📊 **[2025]** [Building world-class product search at Shopify](https://shopify.engineering/world-class-product-search) `Predictive ML`\n- 📊 **[2024]** [How Shopify improved consumer search intent with real-time ML](https://shopify.engineering/how-shopify-improved-consumer-search-intent-with-real-time-ml) `Predictive ML`\n- 📊 **[2023]** [Monte Carlo Simulations: Separating Signal from Noise in Sampled Success Metrics](https://shopify.engineering/monte-carlo-simulations-sampled-success-metrics) `Predictive ML`\n- 👁️ **[2021]** [Using Rich Image and Text Data to Categorize Products at Scale](https://shopify.engineering/machine-learning-at-shopify) `CV`\n- 📊 **[2020]** [Categorizing Products at Scale](https://shopify.engineering/categorizing-products-at-scale) `Predictive ML`\n\n### 🏢 Stitch Fix\n\n- 📊 **[2023]** [Accelerating AI: Implementing Multi-GPU Distributed Training for Personalized Recommendations](https://multithreaded.stitchfix.com/blog/2023/06/08/distributed-model-training/) `Predictive ML`\n- 🧠 **[2023]** [A New Era of Creativity: Expert-in-the-loop Generative AI at Stitch Fix](https://multithreaded.stitchfix.com/blog/2023/03/06/expert-in-the-loop-generative-ai-at-stitch-fix/) `Generative AI \u0026 LLM`\n- 🧠 **[2023]** [A New Era of Creativity: Expert-in-the-loop Generative AI at Stitch Fix](https://multithreaded.stitchfix.com/blog/2023/03/06/expert-in-the-loop-generative-ai-at-stitch-fix/) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Ariadne: building a custom observability UI for personalized search](https://multithreaded.stitchfix.com/blog/2023/06/13/ariadne-observability-ui-for-search/) `Predictive ML`\n- 📊 **[2022]** [Client Time Series Model: a Multi-Target Recommender System based on Temporally-Masked Encoders](https://multithreaded.stitchfix.com/blog/2022/10/14/client-time-series-model/) `Predictive ML`\n- 📊 **[2021]** [Algorithm-Assisted Inventory Curation](https://multithreaded.stitchfix.com/blog/2021/05/12/algorithm-assisted-inventory-curation/) `Predictive ML`\n- 👁️ **[2021]** [Stitching together spaces for query-based recommendations](https://multithreaded.stitchfix.com/blog/2021/08/13/stitching-together-spaces-for-query-based-recommendations/) `CV`\n- 💬 **[2019]** [Give Me Jeans not Shoes: How BERT Helps Us Deliver What Clients Want](https://multithreaded.stitchfix.com/blog/2019/07/15/give-me-jeans/) `NLP`\n\n### 🏢 Target\n\n- 🧠 **[2025]** [Improving Accessory Recommendations with LLMs at Target](https://tech.target.com/blog/accessory-recommendations-with-llms) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [Unlocking the Power of Synthetic Digital Orders in Retail](https://tech.target.com/blog/synthetic-digital-orders) `Predictive ML`\n- 📊 **[2024]** [Bundled Product Recommendations](https://tech.target.com/blog/bundled-product-recommendations) `Predictive ML`\n- 📊 **[2023]** [Solving for Product Availability with AI](https://tech.target.com/blog/solving-product-availability-with-ai) `Predictive ML`\n- 📊 **[2023]** [Target AutoComplete: Real Time Item Recommendations at Target](https://tech.target.com/blog/target-autocomplete) `Predictive ML`\n\n### 🏢 Vinted\n\n- 📊 **[2025]** [Dense Retrieval](https://vinted.engineering/2025/11/18/dense-retrieval/) `Predictive ML`\n- 📊 **[2023]** [Adopting the Vespa search engine for serving personalized second-hand fashion recommendations at Vinted](https://vinted.engineering/2023/10/09/adopting-vespa-for-recommendation-retrieval/) `Predictive ML`\n\n### 🏢 Walmart\n\n- 🧠 **[2024]** [Semantic Retrieval at Walmart](https://arxiv.org/abs/2412.04637) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Using Predictive and Gen AI to Improve Product Categorization at Walmart](https://medium.com/walmartglobaltech/using-predictive-and-gen-ai-to-improve-product-categorization-at-walmart-dc9821c6a481) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Extracting Product Attributes from PDFs using PAE Framework](https://medium.com/walmartglobaltech/extracting-product-attributes-from-pdfs-using-pae-framework-17889c73fdd4) `Predictive ML`\n- 📊 **[2024]** [Transforming Text Classification with Semantic Search Techniques — Faiss](https://medium.com/walmartglobaltech/transforming-text-classification-with-semantic-search-techniques-faiss-c413f133d0e2) `Predictive ML`\n- 📊 **[2024]** [Augmentation Techniques for Imbalanced text Classification](https://medium.com/walmartglobaltech/augmentation-techniques-for-imbalanced-text-classification-f0d29c0f8ce1) `Predictive ML`\n- 📊 **[2023]** [Exploring an Entity Resolution Framework Across Various Use Cases](https://medium.com/walmartglobaltech/exploring-an-entity-resolution-framework-across-various-use-cases-cb172632e4ae) `Predictive ML`\n- 👁️ **[2023]** [Personalized ‘Complete the Look’ model](https://medium.com/walmartglobaltech/personalized-complete-the-look-model-ea093aba0b73) `CV`\n- 💬 **[2022]** [A Unified Multi-task Model for Supporting Multiple Virtual Assistants in Walmart](https://medium.com/walmartglobaltech/a-unified-multi-task-model-for-supporting-multiple-virtual-assistants-in-walmart-2b077c2c96e) `NLP`\n- 📊 **[2022]** [Scaling Product Recommendations using Basket Analysis- Part 1](https://medium.com/walmartglobaltech/scaling-product-recommendations-using-basket-analysis-part-1-8434d4f8756f) `Predictive ML`\n- 📊 **[2022]** [Forecast Anomalies in Refrigeration with PySpark \u0026 Sensor-data](https://medium.com/walmartglobaltech/forecast-anomalies-in-refrigeration-with-pyspark-sensor-data-195f23ae24e2) `Predictive ML`\n- 📊 **[2022]** [Voice Reorder Experience: add Multiple Product Items to your shopping cart](https://medium.com/walmartglobaltech/voice-reorder-experience-add-multiple-product-items-to-your-shopping-cart-59d20fc61797) `Predictive ML`\n- 💬 **[2022]** [Semantic Label Representation with an Application on Multimodal Product Categorization](https://medium.com/walmartglobaltech/semantic-label-representation-with-an-application-on-multimodal-product-categorization-63d668b943b7) `NLP`\n- 📊 **[2021]** [Deep Learning: Product Categorization and Shelving](https://medium.com/walmartglobaltech/deep-learning-product-categorization-and-shelving-630571e81e96) `Predictive ML`\n- 📊 **[2021]** [Mozrt, a Deep Learning Recommendation System Empowering Walmart Store Associates with a Personalized Learning Experience](https://medium.com/walmartglobaltech/mozrt-a-deep-learning-recommendation-system-empowering-walmart-store-associates-with-a-5d42c08d88da) `Predictive ML`\n- 📊 **[2021]** [Predicting Defrost in Refrigeration Cases at Walmart using Fourier Transform](https://medium.com/walmartglobaltech/predicting-defrost-in-refrigeration-cases-at-walmart-using-fourier-transform-e64c0c59323) `Predictive ML`\n\n### 🏢 Wayfair\n\n- 🧠 **[2025]** [The Evolution of Wilma, Wayfair’s Customer Service Agent Copilot](https://www.aboutwayfair.com/careers/tech-blog/the-evolution-of-wilma-wayfairs-customer-service-agent-copilot) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Smarter Shopping Starts Here — How AI Understands What You’re Looking For](https://www.aboutwayfair.com/careers/tech-blog/smarter-shopping-starts-here-how-ai-understands-what-youre-looking-for) `Generative AI \u0026 LLM`\n- 🤖 **[2025]** [Automating Supplier Ticket Management with LLM Agents: Lessons from the Field](https://www.aboutwayfair.com/careers/tech-blog/automating-supplier-ticket-management-with-llm-agents-lessons-from-the-field) `AI agents`\n- 🧠 **[2025]** [Teaching Wayfair’s Catalog to “See” Style: An LLM-Powered Style Compatibility Labeling Pipeline](https://www.aboutwayfair.com/careers/tech-blog/teaching-wayfairs-catalog-to-see-style-an-llm-powered-style-compatibility-labeling-pipeline-on-google-cloud) `Generative AI \u0026 LLM`\n- 🤖 **[2024]** [Agent Co-Pilot: Wayfair's Gen-AI Assistant for Digital Sales Agents](https://www.aboutwayfair.com/careers/tech-blog/agent-co-pilot-wayfairs-gen-ai-assistant-for-digital-sales-agents) `AI agents`\n- 📊 **[2023]** [Preventing Policy Abuse with Graph Neural Networks](https://www.aboutwayfair.com/careers/tech-blog/preventing-policy-abuse-with-graph-neural-networks) `Predictive ML`\n- 📊 **[2023]** [Introducing Melange: A Customer Journey Embedding System for Improving Fraud and Policy Abuse Detection](https://www.aboutwayfair.com/careers/tech-blog/introducing-melange-a-customer-journey-embedding-system-for-improving-fraud-and-scam-detection) `Predictive ML`\n- 📊 **[2023]** [How Wayfair uses “Predicted Winners” Models to Accelerate Success for New Products](https://www.aboutwayfair.com/careers/tech-blog/how-wayfair-uses-predicted-winners-models-to-accelerate-success-for-new-products) `Predictive ML`\n- 📊 **[2023]** [Delivery-Date Prediction](https://www.aboutwayfair.com/careers/tech-blog/delivery-date-prediction) `Predictive ML`\n- 📊 **[2023]** [Hamlet: Wayfair's ML Approach to Identifying Business Shopper](https://www.aboutwayfair.com/careers/tech-blog/hamlet) `Predictive ML`\n- 📊 **[2023]** [Griffin: How Wayfair Leverages Reinforcement Learning to Send Customers Relevant Communications](https://www.aboutwayfair.com/careers/tech-blog/griffin-how-wayfair-leverages-reinforcement-learning-to-send-customers-relevant-communications) `Predictive ML`\n- 📊 **[2022]** [Wayfair’s New Approach to Aspect Based Sentiment Analysis Helps Customers Easily Find “Long Tail” Products](https://www.aboutwayfair.com/careers/tech-blog/wayfairs-new-approach-to-aspect-based-sentiment-analysis-helps-customers-easily-find-long-tail-products) `Predictive ML`\n- 💬 **[2022]** [Building Wayfair’s First Virtual Assistant: Automating Customer Service by Text Based Intent Prediction](https://www.aboutwayfair.com/careers/tech-blog/building-wayfairs-first-virtual-assistant-automating-customer-service-by-text-based-intent-prediction) `NLP`\n- 📊 **[2022]** [Nightingale: Scalable Daily Sales Email Sending Decision Model](https://www.aboutwayfair.com/careers/tech-blog/nightingale-scalable-daily-email-sending-decision-model) `Predictive ML`\n- 📊 **[2021]** [Evolution of Ads Bidding at Wayfair](https://www.aboutwayfair.com/careers/tech-blog/evolution-of-ads-bidding-at-wayfair) `Predictive ML`\n- 📊 **[2021]** [From RGB to Descriptive Color Names: Wayfair's in-house color algorithms to improve customer shopping experience.](https://www.aboutwayfair.com/careers/tech-blog/from-rgb-to-descriptive-color-names-wayfairs-in-house-color-algorithms-to-improve-customer-shopping-experience) `Predictive ML`\n- 📊 **[2021]** [MARS: Transformer Networks for Sequential Recommendation](https://www.aboutwayfair.com/careers/tech-blog/mars-transformer-networks-for-sequential-recommendation) `Predictive ML`\n- 📊 **[2021]** [Contextual Bandit for Marketing Treatment Optimization](https://www.aboutwayfair.com/careers/tech-blog/contextual-bandit-for-marketing-treatment-optimization) `Predictive ML`\n- 📊 **[2021]** [Share of Voice Optimization Engine](https://www.aboutwayfair.com/careers/tech-blog/share-of-voice-optimization-engine) `Predictive ML`\n- 📊 **[2021]** [Building Scalable and Performant Marketing ML Systems at Wayfair](https://www.aboutwayfair.com/careers/tech-blog/building-scalable-and-performant-marketing-ml-systems-at-wayfair) `Predictive ML`\n- 📊 **[2020]** [Explainable Fraud Detection](https://www.aboutwayfair.com/tech-innovation/explainable-fraud-detection) `Predictive ML`\n- 📊 **[2020]** [Bayesian Product Ranking at Wayfair](https://www.aboutwayfair.com/tech-innovation/bayesian-product-ranking-at-wayfair) `Predictive ML`\n- 👁️ **[2020]** [The Visual Complements Model (ViCs): Complementary Product Recommendations From Visual Cues](https://www.aboutwayfair.com/tech-innovation/the-visual-complements-model-vics-complementary-product-recommendations-from-visual-cues) `CV`\n- 📊 **[2019]** [Modeling Uplift Directly: Uplift Decision Tree with KL Divergence and Euclidean Distance as Splitting Criteria](https://www.aboutwayfair.com/tech-innovation/modeling-uplift-directly-uplift-decision-tree-with-kl-divergence-and-euclidean-distance-as-splitting-criteria) `Predictive ML`\n\n### 🏢 Whatnot\n\n- 📊 **[2025]** [Evolving Feed Ranking at Whatnot](https://medium.com/whatnot-engineering/evolving-feed-ranking-at-whatnot-25adb116aeb6) `Predictive ML`\n- 📊 **[2025]** [The New User Dilemma: Why We Killed Our Heuristics (\u0026 What We Built Instead)](https://medium.com/whatnot-engineering/the-new-user-dilemma-why-we-killed-our-heuristics-what-we-built-instead-0d7a834fda5f) `Predictive ML`\n- 🧠 **[2025]** [Eliminating GraphQL Schema Bloat with AI (So You Don’t Have To)](https://medium.com/whatnot-engineering/eliminating-graphql-schema-bloat-with-ai-so-you-dont-have-to-5f6ae84d0ee1) `Generative AI \u0026 LLM`\n- 🧠 **[2023]** [Enhancing Search Using Large Language Models](https://medium.com/whatnot-engineering/enhancing-search-using-large-language-models-f9dcb988bdb9) `Generative AI \u0026 LLM`\n- 🧠 **[2023]** [How Whatnot Utilizes Generative AI to Enhance Trust and Safety](https://medium.com/whatnot-engineering/how-whatnot-utilizes-generative-ai-to-enhance-trust-and-safety-c7968eb6315e) `Generative AI \u0026 LLM`\n\n### 🏢 Zalando\n\n- 🧠 **[2025]** [Dead Ends or Data Goldmines? Investment Insights from Two Years of AI-Powered Postmortem Analysis](https://engineering.zalando.com/posts/2025/09/dead-ends-or-data-goldmines-ai-powered-postmortem-analysis.html) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Dead Ends or Data Goldmines? Investment Insights from Two Years of AI-Powered Postmortem Analysis](https://engineering.zalando.com/posts/2025/02/llm-migration-ui-component-libraries.html) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [Deep Learning based Forecasting: a case study from the online fashion industry](https://arxiv.org/abs/2305.14406) `Predictive ML`\n\n### 🏢 Zillow\n\n- 📊 **[2025]** [Leveraging Knowledge Graphs in Real Estate Search](https://www.zillow.com/tech/leveraging-knowledge-graphs-in-real-estate-search/) `Predictive ML`\n- 🧠 **[2025]** [Revolutionizing the Real Estate Experience with LLMs: StreetEasy’s AI Journey](https://www.zillow.com/tech/revolutionizing-the-real-estate-experience-with-llms-streeteasys-ai-journey/) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Navigating Fair Housing Guardrails in LLMs](https://www.zillow.com/tech/navigating-fair-housing-guardrails-in-llms/) `Generative AI \u0026 LLM`\n- 🧠 **[2024]** [Using AI to Understand the Complexities and Pitfalls of Real Estate Data](https://www.zillow.com/tech/using-ai-to-understand-the-complexities-and-pitfalls-of-real-estate-data/) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [SpectroBrain: Detecting Phone Spam with Semi-Supervised Learning](https://www.zillow.com/tech/spectrobrain-detecting-phone-spam-with-semi-supervised-learning/) `Predictive ML`\n- 📊 **[2023]** [Imputing Data for the Zestimate](https://www.zillow.com/tech/imputing-data-for-the-zestimate/) `Predictive ML`\n- 📊 **[2023]** [Building the Neural Zestimate](https://www.zillow.com/tech/building-the-neural-zestimate/) `Predictive ML`\n- 💬 **[2022]** [Incorporating Listing Descriptions into the Zestimate](https://www.zillow.com/tech/incorporating-listing-descriptions-into-the-zestimate/) `NLP`\n- 📊 **[2022]** [Identifying High-Intent Buyers](https://www.zillow.com/tech/identifying-high-intent-buyers/) `Predictive ML`\n- 💬 **[2022]** [Helping Home Shoppers Find a Home to Love Through Home Insights](https://www.zillow.com/tech/helping-shoppers-find-a-home-using-home-insights/) `NLP`\n- 💬 **[2021]** [Improving Recommendation Quality by Tapping into Listing Text](https://www.zillow.com/tech/improve-quality-listing-text/) `NLP`\n- 📊 **[2020]** [Guided Search — Personalized Search Refinements to Help Customers Find their Dream Home](https://www.zillow.com/tech/personalized-search-refinements/) `Predictive ML`\n- 👁️ **[2020]** [Zillow Floor Plan: Training Models to Detect Windows, Doors and Openings in Panoramas](https://www.zillow.com/tech/training-models-to-detect-windows-doors-in-panos/) `CV`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"education\"\u003e\u003c/a\u003e\n\n## 🎓 Education\n\n\u003e **1 case studies** from **1 companies**\n\n### 🏢 Harvard\n\n- 🔍 **[2023]** [An AI Professor at Harvard: ChatLTV](https://www.linkedin.com/pulse/ai-professor-harvard-chatltv-jeffrey-bussgang-oiaie/) `RAG`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"fintech-and-banking\"\u003e\u003c/a\u003e\n\n## 🏦 Fintech and banking\n\n\u003e **63 case studies** from **22 companies**\n\n### 🏢 Adyen\n\n- 📊 **[2025]** [The AI behind Uplift](https://www.adyen.com/knowledge-hub/the-ai-behind-uplift) `Predictive ML`\n- 🧠 **[2024]** [Elevating Code Quality Through LLM Integration: Adyen's Venture into Augmented Unit Test Generation](https://www.adyen.com/knowledge-hub/elevating-code-quality-through-llm-integration) `Generative AI \u0026 LLM`\n- 📊 **[2020]** [Optimizing payment conversion rates with contextual multi-armed bandits](https://www.adyen.com/blog/optimizing-payment-conversion-rates-with-contextual-multi-armed-bandits) `Predictive ML`\n\n### 🏢 Binance\n\n- 📊 **[2025]** [Strategy Factory: Binance’s AI-Powered Rule Engine for Risk and Fraud Detection](https://www.binance.com/en/blog/tech/4582519158590222265) `Predictive ML`\n- 👁️ **[2024]** [Binance P2P’s Invisible Guardians: Using Computer Vision to Detect Fraud](https://www.binance.com/en/blog/tech/7256282002014933080) `CV`\n- 📊 **[2023]** [Why and How We Use Real-Time Machine Learning to Monitor Fraudulent Activity at Binance](https://www.binance.com/en/blog/tech/7972341655591522254) `Predictive ML`\n\n### 🏢 Brex\n\n- 📊 **[2021]** [How We Built a (Mostly) Automated System to Solve Credit Card Merchant Classification](https://medium.com/brexeng/how-we-built-a-mostly-automated-system-to-solve-credit-card-merchant-classification-f9108029e59b) `Predictive ML`\n\n### 🏢 Capital One\n\n- 📊 **[2021]** [Improving Virtual Card Numbers with Edge Machine Learning](https://www.capitalone.com/tech/machine-learning/edge-machine-learning-eno-virtual-card-numbers/) `Predictive ML`\n- 📊 **[2021]** [How Machine Learning Can Help Fight Money Laundering](https://www.capitalone.com/tech/machine-learning/how-machine-learning-can-help-fight-money-laundering/) `Predictive ML`\n- 📊 **[2021]** [Automated detection, diagnosis \u0026 remediation of app failure](https://www.capitalone.com/tech/machine-learning/automated-detection-diagnosis-remediation-of-application-failure/) `Predictive ML`\n\n### 🏢 Coinbase\n\n- 📊 **[2025]** [How Coinbase Builds Sequence Features for Machine Learning](https://www.coinbase.com/en-ar/blog/how-coinbase-builds-sequence-features-for-machine-learning) `Predictive ML`\n- 📊 **[2025]** [How Coinbase is Embracing AI in Recruiting](https://www.coinbase.com/en-ar/blog/how-coinbase-is-embracing-ai-in-recruiting) `Predictive ML`\n- 🤖 **[2025]** [Making Smarter Decisions, Faster with AI at Coinbase](https://www.coinbase.com/en-it/blog/making-smarter-decisions-faster-with-AI-at-Coinbase) `AI agents`\n- 🤖 **[2025]** [How we are improving product quality at Coinbase with AI agents](https://www.coinbase.com/en-it/blog/How-We-are-Improving-Product-Quality-at-Coinbase-with-AI-agents) `AI agents`\n- 🔍 **[2024]** [Behind the Scenes of the Conversational Coinbase Chatbot](https://www.coinbase.com/en-ar/blog/behind-the-scenes-of-the-conversational-coinbase-chatbot) `RAG`\n- 🧠 **[2024]** [Lessons from launching Enterprise-grade GenAI solutions at Coinbase](https://www.coinbase.com/blog/lessons-from-launching-enterprise-grade-genAI-solutions-at-Coinbase) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [How Coinbase is Using Machine Learning to Predict Traffic and Scale Databases](https://www.coinbase.com/blog/how-coinbase-is-using-machine-learning-to-predict) `Predictive ML`\n- 📊 **[2023]** [Detecting Fraudulent Transactions: Coinbase Scalable Blockchain Address Risk Scoring System](https://www.coinbase.com/blog/detecting-fraudulent-transactions-coinbase-scalable-blockchain-address-risk) `Predictive ML`\n\n### 🏢 Didact AI\n\n- 📊 **[2022]** [Didact AI: The anatomy of an ML-powered stock picking engine](https://principiamundi.com/posts/didact-anatomy) `Predictive ML`\n\n### 🏢 Digits\n\n- 🤖 **[2025]** [Agents in production: Lessons shared at MLOps World 2025](https://digits.com/blog/mlops-world-2025-slides/) `AI agents`\n- 🧠 **[2023]** [ChatGPT for Accounting: How Digits is using Generative Machine Learning to transform finance](https://digits.com/developer/posts/assisting-accountants-with-generative-machine-learning/) `Generative AI \u0026 LLM`\n- 💬 **[2023]** [Assisting Accountants with Similarity-based Machine Learning](https://digits.com/developer/posts/assisting-accountants-with-similarity-based-machine-learning/) `NLP`\n- 💬 **[2021]** [Training and Deploying State of the Art Transformer Models at Digits](https://digits.com/developer/posts/training-and-deploying-state-of-the-art-transformer-models-at-digits/) `NLP`\n\n### 🏢 Feedzai\n\n- 🧠 **[2025]** [Benchmarking LLMs in Real-World Applications: Pitfalls and Surprises](https://medium.com/feedzaitech/benchmarking-llms-in-real-world-applications-pitfalls-and-surprises-78e720d3bfa1) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Feedzai TrustScore: Enabling Network Intelligence to Fight Financial Crime](https://medium.com/feedzaitech/feedzai-trustscore-enabling-network-intelligence-to-fight-financial-crime-9ce7fcff84fb) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Building Trust in a Digital World: The Role of Machine Learning in Behavioral Biometrics](https://medium.com/feedzaitech/building-trust-in-a-digital-world-the-role-of-machine-learning-in-behavioral-biometrics-bb0da913d95a) `Predictive ML`\n\n### 🏢 Goldman Sachs\n\n- 💬 **[2024]** [Using NLP to Purposefully Articulate Software Changes](https://developer.gs.com/blog/posts/using-nlp-to-purposefully-articulate-software-changes) `NLP`\n\n### 🏢 JPMorganChase\n\n- 📊 **[2025]** [Revolutionizing Threat Modeling with AI: The Threat Modeling Co-Pilot](https://arxiv.org/pdf/2503.09586) `Predictive ML`\n\n### 🏢 Lemonade\n\n- 🔍 **[2024]** [[VIDEO] RAG pain-points and solutions](https://www.youtube.com/watch?v=XGJOU2sysjg) `RAG`\n\n### 🏢 Monzo\n\n- 💬 **[2023]** [Using topic modelling to understand customer saving goals](https://medium.com/data-monzo/using-topic-modelling-to-understand-customer-saving-goals-2bb06f00ce2d) `NLP`\n- 📊 **[2023]** [Optimising marketing messages for Monzo users](https://medium.com/data-monzo/optimising-marketing-messages-for-monzo-users-3fe805f24572) `Predictive ML`\n\n### 🏢 Nubank\n\n- 🧠 **[2025]** [Building Foundation Models into Nubank’s AI Platform](https://building.nubank.com/foundation-models-ai-nubank-transformation/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Pioneering the Future of Work: How Nubank is Transforming HR with AI](https://building.nubank.com/artificial-intelligence-human-resources/) `Generative AI \u0026 LLM`\n- 📊 **[2025]** [Optimizing User Narratives for Foundation Models](https://building.nubank.com/optimizing-user-narratives-for-foundation-models/) `Predictive ML`\n- 🔍 **[2025]** [AskNu: A RAG solution to increase Employees Productivity at Nubank](https://building.nubank.com/ai-solution-for-search/) `RAG`\n- 📊 **[2025]** [Practices to scale Machine Learning operations](https://building.nubank.com/practices-to-scale-machine-learning-operations/) `Predictive ML`\n- 🧠 **[2025]** [Fine-Tuning Transaction User Models](https://building.nubank.com/fine-tuning-transaction-user-models/) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Unlocking the potential of sequential modeling in fraud prevention: Insights from experts at Nubank](https://building.nubank.com/the-potential-of-sequential-modeling-in-fraud-prevention-insights-from-experts-at-nubank/) `Predictive ML`\n- 📊 **[2023]** [Presenting Precog, Nubank’s Real Time Event AI](https://building.nubank.com.br/presenting-precog-nubanks-real-time-event-ai/) `Predictive ML`\n- 📊 **[2021]** [Beyond prediction machines](https://building.nubank.com.br/beyond-prediction-machines/) `Predictive ML`\n\n### 🏢 PayPal\n\n- 📊 **[2022]** [Sales Pipeline Management with Machine Learning: A Lightweight Two-Layer Ensemble Classifier Framework](https://medium.com/paypal-tech/sales-pipeline-management-with-machine-learning-15398bab913b) `Predictive ML`\n- 📊 **[2021]** [Using Machine Learning to Improve Payment Authorization Rate](https://medium.com/paypal-tech/using-machine-learning-to-improve-payment-authorization-rates-bc3b2cbf4999) `Predictive ML`\n- 📊 **[2021]** [How PayPal Uses Real-time Graph Database and Graph Analysis to Fight Fraud](https://medium.com/paypal-tech/how-paypal-uses-real-time-graph-database-and-graph-analysis-to-fight-fraud-96a2b918619a) `Predictive ML`\n- 📊 **[2021]** [Deploying Large-scale Fraud Detection Machine Learning Models at PayPal](https://medium.com/paypal-tech/machine-learning-model-ci-cd-and-shadow-platform-8c4f44998c78) `Predictive ML`\n- 📊 **[2021]** [Cross-Selling Optimization Using Deep Learning](https://medium.com/paypal-tech/a-deep-learning-based-approach-to-optimizing-actions-e1ae9d1df152) `Predictive ML`\n- 📊 **[2020]** [Multi-Domain Fraud Detection While Reducing Good User Declines](https://medium.com/paypal-tech/multi-domain-fraud-detection-while-reducing-good-user-declines-part-i-e8bba5b07da8) `Predictive ML`\n\n### 🏢 Plaid\n\n- 🧠 **[2025]** [Agents in Action: Leveraging AI to improve our core product experiences](https://plaid.com/blog/ai-agents-june-2025/) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Transforming Engineers: How we grew AI coding adoption at Plaid](https://plaid.com/blog/ai-coding-adoption-plaid/) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [How we use machine learning to power accurate, real-time income verification](https://plaid.com/blog/machine-learning-income-verification/) `Predictive ML`\n\n### 🏢 Ramp\n\n- 🤖 **[2025]** [How To Build Agents Users Can Trust](https://engineering.ramp.com/post/how-to-build-agents-users-can-trust) `AI agents`\n- 🤖 **[2025]** [How Ramp Fixes Merchant Matches with AI](https://engineering.ramp.com/post/fixing-merchant-classifications-with-ai) `AI agents`\n- 🔍 **[2025]** [From RAG to Richness: How Ramp Revamped Industry Classification](https://engineering.ramp.com/industry_classification) `RAG`\n- 🤖 **[2025]** [How To Build Agents Users Can Trust](https://builders.ramp.com/post/how-to-build-agents-users-can-trust) `AI agents`\n- 🤖 **[2025]** [Meet Ramp Research: Our Agentic Data Analyst](https://engineering.ramp.com/post/meet-ramp-research) `AI agents`\n\n### 🏢 Revolut\n\n- 📊 **[2024]** [Reinventing Risk at Revolut](https://medium.com/revolut/reinventing-risk-at-revolut-77e63c552503) `Predictive ML`\n\n### 🏢 Royal Bank of Canada\n\n- 🔍 **[2024]** [[VIDEO] Arcane, an Internal RAG System to Pinpoint Investment Policies](https://www.youtube.com/watch?v=cqK42uTPUU4) `RAG`\n\n### 🏢 Square\n\n- 🧠 **[2025]** [RoBERTa Model for Merchant Categorization at Square](https://developer.squareup.com/blog/roberta-model-for-merchant-categorization-at-square/) `Generative AI \u0026 LLM`\n\n### 🏢 Stripe\n\n- 📊 **[2025]** [How we built it: Jurisdiction resolution for Stripe Tax](https://stripe.com/blog/how-we-built-it-jurisdiction-resolution-for-stripe-tax) `Predictive ML`\n- 📊 **[2023]** [How we built it: Stripe Radar](https://stripe.com/blog/how-we-built-it-stripe-radar) `Predictive ML`\n- 📊 **[2021]** [A primer on machine learning for fraud detection](https://stripe.com/en-mx/guides/primer-on-machine-learning-for-fraud-protection) `Predictive ML`\n- 📊 **[2020]** [Similarity clustering to catch fraud rings](https://stripe.com/blog/similarity-clustering) `Predictive ML`\n\n### 🏢 SumUp\n\n- 🧠 **[2023]** [Evaluating the performance of an LLM application that generates free-text narratives in the context of financial crime](https://medium.com/inside-sumup/evaluating-the-performance-of-an-llm-application-that-generates-free-text-narratives-in-the-context-c402a0136518) `Generative AI \u0026 LLM`\n\n### 🏢 Wise\n\n- 📊 **[2025]** [Wise Tech Stack (2025 update)](https://medium.com/wise-engineering/wise-tech-stack-2025-update-d0e63fe718c7) `Predictive ML`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"gaming\"\u003e\u003c/a\u003e\n\n## 🎮 Gaming\n\n\u003e **8 case studies** from **4 companies**\n\n### 🏢 Playtika\n\n- 📊 **[2024]** [Lessons learned from multi-armed bandits in real-time production](https://medium.com/@playtika-tech-ai/lessons-learned-from-multi-armed-bandits-in-real-time-production-777f2bdd4f5f) `Predictive ML`\n- 🧠 **[2024]** [Generative art at scale in Playtika](https://medium.com/@playtika-tech-ai/generative-art-at-scale-in-playtika-cf36be807fea) `Generative AI \u0026 LLM`\n\n### 🏢 Roblox\n\n- 🧠 **[2025]** [How Roblox Uses AI to Moderate Content on a Massive Scale](https://corp.roblox.com/newsroom/2025/07/roblox-ai-moderation-massive-scale) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Deploying ML for Voice Safety](https://corp.roblox.com/newsroom/2024/07/deploying-ml-for-voice-safety) `Predictive ML`\n- 🧠 **[2024]** [Breaking Down Language Barriers with a Multilingual Translation Model](https://corp.roblox.com/newsroom/2024/02/breaking-down-language-barriers-with-a-multilingual-translation-model) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [How Roblox Reduces Spark Join Query Costs With Machine Learning Optimized Bloom Filters](https://corp.roblox.com/newsroom/2023/11/roblox-reduces-spark-join-query-costs-machine-learning-optimized-bloom-filters) `Predictive ML`\n\n### 🏢 Rovio\n\n- 📊 **[2023]** [MLOps at Rovio for Personalization Self Service Reinforcement Learning in Production](https://www.youtube.com/watch?v=_Rqo6nooKKE) `Predictive ML`\n\n### 🏢 Zynga\n\n- 📊 **[2020]** [Deep Reinforcement Learning in Production Part 2: Personalizing User Notifications](https://towardsdatascience.com/deep-reinforcement-learning-in-production-part-2-personalizing-user-notifications-812a68ce2355) `Predictive ML`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"manufacturing\"\u003e\u003c/a\u003e\n\n## 🏭 Manufacturing\n\n\u003e **5 case studies** from **1 companies**\n\n### 🏢 Haleon\n\n- 📊 **[2023]** [FastDTW in Action: Optimising Manufacturing Operations](https://medium.com/trusted-data-science-haleon/fastdtw-in-action-optimizing-manufacturing-operations-c07f3cc5023c) `Predictive ML`\n- 💬 **[2023]** [Deriving insights from customer queries on Haleon brands](https://medium.com/trusted-data-science-haleon/deriving-insights-from-customer-queries-on-haleon-brands-86f7e01b912c) `NLP`\n- 📊 **[2023]** [Using Reinforcement Learning to track marketing spend](https://medium.com/trusted-data-science-haleon/using-reinforcement-learning-to-track-marketing-spend-db67e843476b) `Predictive ML`\n- 👁️ **[2023]** [Employing Computer Vision in Digital Asset Management (Part 1)](https://medium.com/trusted-data-science-haleon/employing-computer-vision-in-digital-asset-management-207d21a68d9) `CV`\n- 👁️ **[2023]** [Employing Computer Vision in Digital Asset Management (Part 2)](https://medium.com/trusted-data-science-haleon/employing-computer-vision-in-digital-asset-management-part-ii-c0f38e9df642) `CV`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"media-and-streaming\"\u003e\u003c/a\u003e\n\n## 📺 Media and streaming\n\n\u003e **57 case studies** from **10 companies**\n\n### 🏢 Amazon\n\n- 📊 **[2022]** [The Amazon Music conversational recommender is hitting the right notes](https://www.amazon.science/latest-news/how-amazon-music-uses-recommendation-system-machine-learning) `Predictive ML`\n\n### 🏢 Dailymotion\n\n- 📊 **[2023]** [Reinvent your recommender system using Vector Database and Opinion Mining](https://medium.com/dailymotion/reinvent-your-recommender-system-using-vector-database-and-opinion-mining-a4fadf97d020) `Predictive ML`\n- 📊 **[2022]** [Optimizing video feed recommendations with diversity: Machine Learning first steps](https://medium.com/dailymotion/optimizing-video-feed-recommendations-with-diversity-machine-learning-first-steps-4cf9abdbbffd) `Predictive ML`\n- 📊 **[2021]** [How Deep Learning can boost Contextual Advertising Capabilities](https://medium.com/dailymotion/how-deep-learning-can-boost-contextual-advertising-capabilities-c9ca7c8fc4e9) `Predictive ML`\n- 💬 **[2020]** [How we used Cross-Lingual Transfer Learning to categorize our content](https://medium.com/dailymotion/how-we-used-cross-lingual-transfer-learning-to-categorize-our-content-c8e0f9c1c6c3) `NLP`\n\n### 🏢 Guardian\n\n- 💬 **[2023]** [Who said what: using machine learning to correctly attribute quotes](https://www.theguardian.com/info/2023/nov/21/who-said-what-using-machine-learning-to-correctly-attribute-quotes) `NLP`\n- 💬 **[2022]** [Recognising ‘bad actors’ in data leaks with AI](https://www.theguardian.com/info/2022/dec/09/recognising-bad-actors-in-data-leaks-with-ai) `NLP`\n\n### 🏢 Netflix\n\n- 📊 **[2025]** [Accelerating Video Quality Control at Netflix with Pixel Error Detection](https://netflixtechblog.com/accelerating-video-quality-control-at-netflix-with-pixel-error-detection-47ef7af7ca2e) `Predictive ML`\n- 🧠 **[2025]** [Foundation Model for Personalized Recommendation](https://netflixtechblog.medium.com/foundation-model-for-personalized-recommendation-1a0bd8e02d39) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [FM-Intent: Predicting User Session Intent with Hierarchical Multi-Task Learning](https://netflixtechblog.com/fm-intent-predicting-user-session-intent-with-hierarchical-multi-task-learning-94c75e18f4b8) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Foundation Model for Personalized Recommendation](https://netflixtechblog.com/foundation-model-for-personalized-recommendation-1a0bd8e02d39) `Generative AI \u0026 LLM`\n- 🧠 **[2025]** [Integrating Netflix’s Foundation Model into Personalization applications](https://netflixtechblog.medium.com/integrating-netflixs-foundation-model-into-personalization-applications-cf176b5860eb) `Generative AI \u0026 LLM`\n- 📊 **[2024]** [Recommending for Long-Term Member Satisfaction at Netflix](https://netflixtechblog.com/recommending-for-long-term-member-satisfaction-at-netflix-ac15cada49ef) `Predictive ML`\n- 📊 **[2024]** [Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data Platform](https://netflixtechblog.com/evolving-from-rule-based-classifier-machine-learning-powered-auto-remediation-in-netflix-data-039d5efd115b) `Predictive ML`\n- 📊 **[2024]** [Video annotator: a framework for efficiently building video classifiers using vision-language models and active learning](https://netflixtechblog.com/video-annotator-building-video-classifiers-using-vision-language-models-and-active-learning-8ebdda0b2db4) `Predictive ML`\n- 📊 **[2024]** [Round 2: A Survey of Causal Inference Applications at Netflix](https://netflixtechblog.com/round-2-a-survey-of-causal-inference-applications-at-netflix-fd78328ee0bb) `Predictive ML`\n- 📊 **[2024]** [Reverse Searching Netflix’s Federated Graph](https://netflixtechblog.com/reverse-searching-netflixs-federated-graph-222ac5d23576) `Predictive ML`\n- 📊 **[2023]** [Detecting Speech and Music in Audio Content](https://netflixtechblog.com/detecting-speech-and-music-in-audio-content-afd64e6a5bf8) `Predictive ML`\n- 📊 **[2023]** [The Next Step in Personalization: Dynamic Sizzles](https://netflixtechblog.com/the-next-step-in-personalization-dynamic-sizzles-4dc4ce2011ef) `Predictive ML`\n- 📊 **[2023]** [Building In-Video Search](https://netflixtechblog.com/building-in-video-search-936766f0017c) `Predictive ML`\n- 📊 **[2023]** [Lessons Learnt From Consolidating ML Models in a Large Scale Recommendation System](https://netflixtechblog.medium.com/lessons-learnt-from-consolidating-ml-models-in-a-large-scale-recommendation-system-870c5ea5eb4a) `Predictive ML`\n- 📊 **[2022]** [Reinforcement Learning for Budget Constrained Recommendations](https://netflixtechblog.com/reinforcement-learning-for-budget-constrained-recommendations-6cbc5263a32a) `Predictive ML`\n- 📊 **[2022]** [Machine Learning for Fraud Detection in Streaming Services](https://netflixtechblog.medium.com/machine-learning-for-fraud-detection-in-streaming-services-b0b4ef3be3f6) `Predictive ML`\n- 📊 **[2022]** [A Survey of Causal Inference Applications at Netflix](https://netflixtechblog.com/a-survey-of-causal-inference-applications-at-netflix-b62d25175e6f) `Predictive ML`\n- 📊 **[2022]** [For your eyes only: improving Netflix video quality with neural networks](https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c) `Predictive ML`\n- 📊 **[2018]** [Using Machine Learning to Improve Streaming Quality at Netflix](https://netflixtechblog.com/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) `Predictive ML`\n\n### 🏢 New York Times\n\n- 📊 **[2025]** [Scaling Subscriptions at The New York Times with Real-Time Causal Machine Learning](https://open.nytimes.com/scaling-subscriptions-at-the-new-york-times-with-real-time-causal-machine-learning-5f23a7b24ff4) `Predictive ML`\n- 📊 **[2024]** [How The New York Times Incorporates Editorial Judgement in Algorithms to Curate Home Screen Content](https://open.nytimes.com/how-the-new-york-times-incorporates-editorial-judgement-in-algorithms-to-curate-home-screen-content-85f48209fdad) `Predictive ML`\n- 👁️ **[2024]** [Experimenting with Handwriting Recognition for The New York Times Crossword](https://open.nytimes.com/experimenting-with-handwriting-recognition-for-new-york-times-crossword-a78e08fec08f) `CV`\n- 📊 **[2023]** [How The New York Times Cooking Team Makes Personalized Recipe Recommendations](https://open.nytimes.com/how-the-new-york-times-cooking-team-makes-personalized-recipe-recommendations-7b86df9b22ec) `Predictive ML`\n- 📊 **[2022]** [How The New York Times Uses Machine Learning To Make Its Paywall Smarter](https://open.nytimes.com/how-the-new-york-times-uses-machine-learning-to-make-its-paywall-smarter-e5771d5f46f8) `Predictive ML`\n- 📊 **[2021]** [Machine Learning and Reader Input Help Us Recommend Articles](https://open.nytimes.com/we-recommend-articles-with-a-little-help-from-our-friends-machine-learning-and-reader-input-e17e85d6cf04) `Predictive ML`\n\n### 🏢 Scribd\n\n- 👁️ **[2021]** [Identifying Document Types at Scribd](https://tech.scribd.com/blog/2021/identifying-document-types.html) `CV`\n- 💬 **[2021]** [Information Extraction at Scribd](https://tech.scribd.com/blog/2021/information-extraction-at-scribd.html) `NLP`\n- 📊 **[2021]** [Embedding-based Retrieval at Scribd](https://tech.scribd.com/blog/2021/embedding-based-retrieval-scribd.html) `Predictive ML`\n- 📊 **[2021]** [Categorizing user-uploaded documents](https://tech.scribd.com/blog/2021/categorizing-user-uploaded-documents.html) `Predictive ML`\n\n### 🏢 Spotify\n\n- 🤖 **[2025]** [1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent (Part 1)](https://engineering.atspotify.com/2025/11/spotifys-background-coding-agent-part-1) `AI agents`\n- 🤖 **[2025]** [Background Coding Agents: Predictable Results Through Strong Feedback Loops (Part 3)](https://engineering.atspotify.com/2025/12/feedback-loops-background-coding-agents-part-3) `AI agents`\n- 🤖 **[2025]** [Background Coding Agents: Context Engineering (Part 2)](https://engineering.atspotify.com/2025/11/context-engineering-background-coding-agents-part-2) `AI agents`\n- 🤖 **[2025]** [Rewriting all of Spotify's code base, all the time](https://www.youtube.com/watch?v=1oicrAfrEIk) `AI agents`\n- 🧠 **[2024]** [How We Generated Millions of Content Annotations](https://engineering.atspotify.com/2024/10/how-we-generated-millions-of-content-annotations/) `Generative AI \u0026 LLM`\n- 📊 **[2023]** [How We Automated Content Marketing to Acquire Users at Scale](https://engineering.atspotify.com/2023/11/how-we-automated-content-marketing-to-acquire-users-at-scale/) `Predictive ML`\n- 📊 **[2023]** [Experimenting with Machine Learning to Target In-App Messaging](https://engineering.atspotify.com/2023/06/experimenting-with-machine-learning-to-target-in-app-messaging/) `Predictive ML`\n- 📊 **[2023]** [Spotify Track Neural Recommender System](https://medium.com/stanford-cs224w/spotify-track-neural-recommender-system-51d266e31e16) `Predictive ML`\n- 📊 **[2023]** [Large-Scale Generation of ML Podcast Previews at Spotify with Google Dataflow](https://engineering.atspotify.com/2023/04/large-scale-generation-of-ml-podcast-previews-at-spotify-with-google-dataflow/) `Predictive ML`\n- 💬 **[2022]** [Introducing Natural Language Search for Podcast Episodes](https://engineering.atspotify.com/2022/03/introducing-natural-language-search-for-podcast-episodes/) `NLP`\n- 📊 **[2022]** [How We Built Infrastructure to Run User Forecasts at Spotify](https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/) `Predictive ML`\n- 📊 **[2021]** [The Rise (and Lessons Learned) of ML Models to Personalize Content on Home (Part I)](https://engineering.atspotify.com/2021/11/the-rise-and-lessons-learned-of-ml-models-to-personalize-content-on-home-part-i/) `Predictive ML`\n- 📊 **[2021]** [The Rise (and Lessons Learned) of ML Models to Personalize Content on Home (Part II)](https://engineering.atspotify.com/2021/11/the-rise-and-lessons-learned-of-ml-models-to-personalize-content-on-home-part-ii/) `Predictive ML`\n- 📊 **[2020]** [Reach for the Top: How Spotify Built Shortcuts in Just Six Months](https://engineering.atspotify.com/2020/04/reach-for-the-top-how-spotify-built-shortcuts-in-just-six-months/) `Predictive ML`\n\n### 🏢 Thomson Reuters\n\n- 🤖 **[2025]** [From Copilot to Colleague: Trustworthy Agents for High-Stakes](https://www.youtube.com/watch?v=kDEvo2__Ijg) `AI agents`\n- 🤖 **[2025]** [Deep Research in Westlaw and CoCounsel: Building Agents That Research Like Lawyers](https://medium.com/tr-labs-ml-engineering-blog/deep-research-in-westlaw-and-cocounsel-building-agents-that-research-like-lawyers-508ad5c70e45) `AI agents`\n- 🔍 **[2024]** [Better Customer Support Using Retrieval-Augmented Generation (RAG) at Thomson Reuters](https://medium.com/tr-labs-ml-engineering-blog/better-customer-support-using-retrieval-augmented-generation-rag-at-thomson-reuters-4d140a6044c3) `RAG`\n\n### 🏢 Tubi\n\n- 📊 **[2024]** [How to Monitor a Recommender System](https://code.tubitv.com/how-to-monitor-a-recommender-system-6d720c922c90) `Predictive ML`\n- 💬 **[2022]** [Using Pre-Trained NLP Models to Interpret User Feedback at Tubi](https://code.tubitv.com/using-pre-trained-nlp-models-to-interpret-user-feedback-at-tubi-6dffecf46510) `NLP`\n\n### 🏢 Vimeo\n\n- 🔍 **[2024]** [Unlocking knowledge sharing for videos with RAG](https://medium.com/vimeo-engineering-blog/unlocking-knowledge-sharing-for-videos-with-rag-810ab496ae59) `RAG`\n- 🧠 **[2023]** [From idea to reality: Elevating our customer support through generative AI](https://medium.com/vimeo-engineering-blog/from-idea-to-reality-elevating-our-customer-support-through-generative-ai-101a2c5ea680) `Generative AI \u0026 LLM`\n\n[⬆️ Back to Top](#-quick-navigation)\n\n---\n\n\u003ca id=\"social-platforms\"\u003e\u003c/a\u003e\n\n## 🌐 Social platforms\n\n\u003e **99 case studies** from **14 companies**\n\n### 🏢 Bumble\n\n- 💬 **[2021]** [Multilingual message content moderation at scale (part 1)](https://medium.com/bumble-tech/multilingual-message-content-moderation-at-scale-ddd0da1e23ed) `NLP`\n- 💬 **[2021]** [Multilingual message content moderation at scale (part 2)](https://medium.com/bumble-tech/multilingual-message-content-moderation-at-scale-7ea562e29e25) `NLP`\n- 👁️ **[2020]** [Image detection as a service](https://medium.com/bumble-tech/image-detection-as-a-service-9bd463f74f43) `CV`\n\n### 🏢 Discord\n\n- 🧠 **[2024]** [Developing rapidly with Generative AI](https://discord.com/blog/developing-rapidly-with-generative-ai) `Generative AI \u0026 LLM`\n- 💬 **[2024]** [Learning from structure: Discord's Entity-Relationship Embeddings](https://discord.com/blog/learning-from-structure-discords-entity-relationship-embeddings) `NLP`\n\n### 🏢 Ebay\n\n- 📊 **[2022]** [Multi-Relevance Ranking Model for Similar Item Recommendation](https://tech.ebayinc.com/engineering/multi-relevance-ranking-model-for-similar-item-recommendation/) `Predictive ML`\n\n### 🏢 Glassdoor\n\n- 📊 **[2025]** [Inside Glassdoor’s Multi-Stage Recommendation System](https://medium.com/glassdoor-engineering/inside-glassdoors-multi-stage-recommendation-system-cee58b52a75a) `Predictive ML`\n- 📊 **[2022]** [Personalized Fishbowl Recommendations with Learned Embeddings: Part 2](https://medium.com/glassdoor-engineering/personalized-fishbowl-recommendations-with-learned-embeddings-part-2-78a16b04d396) `Predictive ML`\n- 📊 **[2022]** [Personalized Fishbowl Recommendations with Learned Embeddings: Part 1](https://medium.com/glassdoor-engineering/personalized-fishbowl-recommendations-with-learned-embeddings-part-1-6031abe84661) `Predictive ML`\n\n### 🏢 LinkedIn\n\n- 🤖 **[2025]** [The LinkedIn Generative AI Application Tech Stack: Extending to Build AI Agents](https://www.linkedin.com/blog/engineering/generative-ai/the-linkedin-generative-ai-application-tech-stack-extending-to-build-ai-agents) `AI agents`\n- 🤖 **[2025]** [Building the agentic future of recruiting: how we engineered LinkedIn’s Hiring Assistant](https://www.linkedin.com/blog/engineering/ai/how-we-engineered-linkedins-hiring-assistant) `AI agents`\n- 🧠 **[2024]** [Under the hood: the tech behind the first agent from LinkedIn, Hiring Assistant](https://www.linkedin.com/blog/engineering/generative-ai/the-tech-behind-the-first-agent-from-linkedin-hiring-assistant) `Generative AI \u0026 LLM`\n- 🔍 **[2024]** [Musings on building a Generative AI product](https://www.linkedin.com/blog/engineering/generative-ai/musings-on-building-a-generative-ai-product) `RAG`\n- 📊 **[2024]** [Finding AI-generated (deepfake) faces in the wild](https://arxiv.org/abs/2311.08577) `Predictive ML`\n- 📊 **[2024]** [Candidate Generation in a Large Scale Graph Recommendation System: People You May Know](https://www.linkedin.com/blog/engineering/recommendations/candidate-generation-in-a-la","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/hackthacker%2Fawesome-ml-llm-case-studies/projects"}