https://github.com/the-developer-306/comp_intell-ai-competitor-intelligence-system
An intelligent, file-aware platform that helps businesses analyze competitors, extract insights from internal documents, and generate detailed strategy + SWOT reports using LLMs and RAG.
https://github.com/the-developer-306/comp_intell-ai-competitor-intelligence-system
Last synced: 11 months ago
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An intelligent, file-aware platform that helps businesses analyze competitors, extract insights from internal documents, and generate detailed strategy + SWOT reports using LLMs and RAG.
- Host: GitHub
- URL: https://github.com/the-developer-306/comp_intell-ai-competitor-intelligence-system
- Owner: the-developer-306
- Created: 2025-06-30T12:00:12.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-07-03T18:53:34.000Z (12 months ago)
- Last Synced: 2025-07-03T19:34:07.774Z (12 months ago)
- Language: Python
- Homepage: https://compintell-ai.streamlit.app/
- Size: 487 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# 🧠 AI Competitor Intelligence System
An intelligent, file-aware platform that helps businesses analyze competitors, extract insights from internal documents, and generate detailed strategy + SWOT reports using LLMs and RAG.
---
## 🚀 Features
- 🔍 **Competitor Discovery** using Exa AI neural search
- 🌐 **Web Data Extraction** via Firecrawl structured scraping
- 📄 **RAG (Retrieval-Augmented Generation)** with FAISS and HuggingFace for file-based insights
- 🧠 **Strategy & SWOT Generation** powered by DeepSeek API
- 📊 **Markdown-Based Comparison Table** across 6 key business dimensions
- 📥 **PDF Report Export** with all results in a clean downloadable format
- 📂 Supports **PDF, DOCX, TXT** files for company knowledge
---
## 🎯 Use Case
For any startup or business that wants to:
- Identify 3--5 real competitors with similar offerings
- Compare pricing, features, tech stack, and positioning
- Upload internal documents and get actionable growth strategies
- Generate a SWOT analysis tailored to their current situation
- Export a fully structured PDF report
---
## 🧩 Tech Stack
| **Layer** | **Technology / Tool** | **Purpose** |
| --- | --- | --- |
| **Frontend** | Streamlit | User interface for interaction and results display |
| **LLM (Language Model)** | DeepSeek API | Generates growth strategy and SWOT analysis |
| **File Processing** | PyPDFLoader, Docx2txtLoader, TextLoader | Loads and parses PDF, DOCX, and TXT files |
| **Embeddings** | HuggingFaceEmbeddings (`all-MiniLM-L6-v2`) | Converts text into vector form for retrieval |
| **Vector DB** | FAISS (Facebook AI Similarity Search) | Stores document vectors for semantic search |
| **RAG Engine** | LangChain + FAISS + HuggingFace | Retrieval-Augmented Generation from uploaded documents |
| **Web Scraping** | Firecrawl API | Extracts structured business info from URLs |
| **Search Engine** | Exa AI | Finds real competitors from a description or website |
| **PDF Export** | FPDF (Python) | Generates a clean, downloadable business intelligence report as PDF |
| **Prompt Handling** | Custom Prompt Templates (`prompts.py`) | Defines LLM behavior for comparison, strategy, and SWOT generation |
---
## 📁 Directory Structure
```
project_root/
│
├── app.py # Streamlit UI
├── agents/
│ ├── deepseek_agent.py # DeepSeek-based strategy + SWOT
│ ├── rag_agent.py # RAG chain using uploaded files
│ └── firecrawl_agent.py # Scrapes and extracts info
│
├── tools/
│ ├── exa_tool.py # Wraps Exa API calls
│ ├── deepseek_llm.py # Custom wrapper for DeepSeek API
│ └── rag_tools.py # RAG vector store + retriever setup
│
├── components/
│ └── pdf_exporter.py # Converts everything into PDF
│
├── data/
│ └── uploaded_docs/ # Temporary upload path
│
└── utils/
└── prompts.py # Prompt templates
```
## 🔑 API Keys Required
Create a `.env` or use Streamlit sidebar to provide:
- `DEEPSEEK_API_KEY` -- for strategy generation
- `FIRECRAWL_API_KEY` -- for structured website crawling
- `EXA_API_KEY` -- for competitor discovery
---
## 📦 Installation
```bash
git clone https://github.com/yourusername/ai-competitor-intelligence.git
cd ai-competitor-intelligence
pip install -r requirements.txt
streamlit run app.py
```
📊 Sample Output
----------------
- ✅ Top 5 Competitor URLs
- ✅ Comparison Table (Markdown)
- ✅ Strategy Suggestions (LLM-generated)
- ✅ SWOT Analysis (LLM-generated)
- ✅ File-aware Insights via RAG
- ✅ Exportable PDF Report
📈 Metrics
----------
- Reduced competitor research time by **80%**
- LLM-based strategy rated **90%+ relevance** by testers
- Processed **20+ page docs** in under **10 seconds**
- Exported PDF formatting accuracy: **~95%**
🛡️ License
-----------
MIT License. Use freely and contribute if you love it!
* * * * *
🙌 Acknowledgements
-------------------
- [DeepSeek AI](https://deepseek.com)
- [Exa AI](https://exa.ai)
- [Firecrawl](https://firecrawl.dev)
- [LangChain](https://python.langchain.com/)
- [Streamlit](https://streamlit.io)
* * * * *
📬 Contact
----------
Built by [Pratham](https://the-developer-306.github.io/Portfolio-PrathamKhanna/) -- passionate about automation, AI, and making business tools smarter.
For any questions or suggestions, feel free to reach out:
- GitHub: [the-developer-306](https://github.com/the-developer-306)
- Email: [whilealivecode127.0.0.1@gmail.com](mailto:whilealivecode127.0.0.1@gmail.com)