https://github.com/meesho/bharatmlstack

BharatMLStack is an open-source, end-to-end machine learning infrastructure stack built at Meesho to support real-time and batch ML workloads at Bharat scale
https://github.com/meesho/bharatmlstack

ai feature-engineering feature-store-online machine-learning ml mlops

Last synced: about 2 months ago
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BharatMLStack is an open-source, end-to-end machine learning infrastructure stack built at Meesho to support real-time and batch ML workloads at Bharat scale

• Host: GitHub
• URL: https://github.com/meesho/bharatmlstack
• Owner: Meesho
• License: other
• Created: 2025-05-23T06:34:12.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2026-01-29T16:14:06.000Z (4 months ago)
• Last Synced: 2026-01-30T02:07:06.470Z (4 months ago)
• Topics: ai, feature-engineering, feature-store-online, machine-learning, ml, mlops
• Language: Go
• Homepage:
• Size: 159 MB
• Stars: 615
• Watchers: 10
• Forks: 59
• Open Issues: 18
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

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## What is BharatMLStack?

BharatMLStack is a production-ready, cloud-agnostic ML infrastructure platform that powers real-time feature serving, model inference, and embedding search at massive scale. Built and battle-tested at [Meesho](https://meesho.com), it is designed to help organizations ship ML to production faster, cheaper, and more reliably.

## Our Vision

BharatMLStack is built around **four core tenets**:

### Workflow Integration & Productivity

> Ship ML to production faster than ever.

- **3x faster** experiment-to-deployment cycles

- **95% reduction** in model onboarding time

### Cloud-Agnostic & Lock-In Free

> Run anywhere. Own your stack.

- Runs across **public cloud, on-prem, and edge**

- Kubernetes-native with zero vendor lock-in

### Economic Efficiency

> Do more with less.

- **60–70% lower** infrastructure costs vs hyperscaler managed services

- Optimized resource utilization across CPU and GPU workloads

### Availability & Scalability

> Enterprise-grade reliability at internet scale.

- **99.99% uptime** across clusters

- **1M+ QPS** with low latency

## Designed Truly for Bharat Scale

Built for the demands of one of the world's largest e-commerce platforms:

| Metric | Performance |

|--------|-------------|

| **Feature Store** | 2.4M QPS (batch of 100 id lookups) |

| **Model Inference** | 1M+ QPS |

| **Embedding Search** | 500K QPS |

| **Feature Retrieval Latency** | Sub-10ms |

## Core Components

| Component | Description | Version | Docs |

|-----------|-------------|---------|------|

| **[TruffleBox UI](./trufflebox-ui/)** | Web console for feature registry, cataloging, and approval workflows | `v1.3.0` | [Docs](https://meesho.github.io/BharatMLStack/trufflebox-ui/v1.0.0/userguide) |

| **[Online Feature Store](./online-feature-store/)** | Sub-10ms feature retrieval at millions of QPS with streaming ingestion | `v1.2.0` | [Docs](https://meesho.github.io/BharatMLStack/category/online-feature-store) |

| **[Inferflow](./inferflow/)** | DAG-based real-time inference orchestration for composable ML pipelines | `v1.0.0` | [Docs](https://meesho.github.io/BharatMLStack/category/inferflow) |

| **[Numerix](./numerix/)** | Rust-powered math compute engine for high-performance matrix ops | `v1.0.0` | [Docs](https://meesho.github.io/BharatMLStack/category/numerix) |

| **[Skye](./skye/)** | Vector similarity search with pluggable backends | `v1.0.0` | [Docs](https://meesho.github.io/BharatMLStack/category/skye) |

| **[Go SDK](./go-sdk/)** | Go client for Feature Store, Interaction Store, and logging | `v1.3.0` | [Docs](https://meesho.github.io/BharatMLStack/category/go-sdk) |

| **[Python SDK](./py-sdk/)** | Python client libraries for Feature Store and inference logging | `v1.0.1` | [Docs](https://meesho.github.io/BharatMLStack/category/python-sdk) |

| **[Interaction Store](./interaction-store/)** | ScyllaDB-backed store for user interaction signals at sub-10ms | — | — |

| **[Horizon](./horizon/)** | Control plane that orchestrates all services and powers TruffleBox UI | `v1.3.0` | — |

> Full documentation at [meesho.github.io/BharatMLStack](https://meesho.github.io/BharatMLStack/) | [Blogs](https://meesho.github.io/BharatMLStack/blog)

- [All Blog Posts](https://meesho.github.io/BharatMLStack/blog)

## Quick Start

```bash

git clone https://github.com/Meesho/BharatMLStack.git

cd BharatMLStack/quick-start

#Set versions

ONFS_VERSION=v1.2.0 HORIZON_VERSION=v1.3.0 TRUFFLEBOX_VERSION=v1.3.0 NUMERIX_VERSION=v1.0.0

./start.sh

```

For step-by-step setup, Docker Compose details, sample data, and health checks, see the full **[Quick Start Guide →](./quick-start/README.md)**.

## Architecture



  



## Use-Cases

BharatMLStack powers a wide range of ML-driven applications:

| Use-Case | What BharatMLStack Enables |

|----------|---------------------------|

| **Personalized Candidate Generation** | Retrieve and rank millions of candidates in real time using feature vectors and embedding similarity |

| **Personalized Ranking** | Serve user, item, and context features at ultra-low latency to power real-time ranking models |

| **Fraud & Risk Detection** | Stream interaction signals and features to detect anomalies and fraudulent patterns in milliseconds |

| **Image Search** | Run embedding search at 500K QPS to match visual queries against massive product catalogs |

| **LLM Recommender Systems** | Orchestrate LLM inference pipelines with feature enrichment for next-gen recommendation engines |

| **DL & LLM Deployments at Scale** | Deploy and scale deep learning and large language models across GPU clusters with Inferflow orchestration |

## Contributing

We welcome contributions from the community! Please see our [Contributing Guide](CONTRIBUTING.md) for details on how to get started.

## Community & Support

- **Discord**: Join our [community chat](https://discord.gg/XkT7XsV2AU)

- **Issues**: Report bugs and request features on [GitHub Issues](https://github.com/Meesho/BharatMLStack/issues)

- **Email**: Contact us at [ml-oss@meesho.com](mailto:ml-oss@meesho.com)

## License

BharatMLStack is open-source software licensed under the [BharatMLStack Business Source License 1.1](LICENSE.md).

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