Context-Aware Search, Summarization, and Secure Collaboration with Local LLMs
In today’s enterprise landscape, documentation is both an asset and a bottleneck. From compliance-heavy industries like finance and healthcare to fast-moving product teams, knowledge silos slow down decision-making, reduce productivity, and create risk. We built the Enterprise AI Document Platform to solve that.
Why We Built This
Enterprises are sitting on a goldmine of internal documents—policy manuals, technical specs, knowledge base articles, contracts—but most of it is:
- Hard to search
- Harder to summarize
- Trapped in outdated systems
What if you could chat with your documents, search them semantically, and get instant, secure answers—all with full control and no data leakage?
That’s what this platform delivers.
Key Features
- Local LLM Inference
Uses Ollama with models like Llama3, Mistral, and Phi for low-latency, offline LLM capability. - Vector Store with ChromaDB
Documents are chunked and embedded for fast, accurate semantic search. - Secure Upload + Access Control
Upload PDFs, DOCXs, TXTs, or web pages. Fully local processing keeps your documents safe. - RAG-based Q&A Interface
Ask questions like “What’s our latest refund policy?” or “Summarize this 100-page report” and get contextual responses. - Summarization Engine
Summarize documents or extract key insights instantly using your selected LLM. - Built-in Admin Panel
Track document uploads, manage history, and tweak settings—no terminal needed.
Visual Walkthrough
- Document Upload: Drag and drop your files, and they’re processed into vector space.
- Semantic Search: Search naturally—no keywords required. The platform understands meaning, not just text.
- AI Chat: Ask multi-turn questions. Get answers that cite document sources.
- Summarization Panel: Convert long documents into digestible insights in one click.
Enterprise-Ready
- Runs locally: No sensitive data leaves your network
- Works offline: Perfect for air-gapped or regulated environments
- Modular: Replace LLMs, embeddings, or vector DBs to fit your stack
- Customizable UI: Built with Python, Streamlit, and Tailwind-style components
Tech Stack
- Backend: FastAPI, LangChain, Ollama, ChromaDB
- Frontend: Streamlit (enhanced with modern UI components)
- Infra: Dockerized for easy deployment
- LLMs: Llama3, Mistral, Phi (via Ollama)
Who It’s For
- CTOs/CIOs building internal AI platforms
- Legal/Compliance teams managing document-heavy workflows
- AI Architects deploying LLM solutions without sending data to OpenAI or Anthropic
- DevOps teams needing searchable runbooks or logs
Getting Started
- Clone the repo
- Install dependencies via
setup.sh - Run Ollama and start the server
- Upload your docs and start chatting
Full instructions on GitHub:
enterprise-ai-document-platform
Coming Soon
- Multi-user support with role-based access
- Integration with enterprise DMS and email
- Multi-modal input (image and voice)
- Enhanced source citation and PDF export of chat responses
Final Thoughts
This project is more than a doc search tool—it’s your enterprise’s AI knowledge layer. We’re bridging the gap between static documentation and dynamic decision-making. Give it a spin, fork it, contribute, and help shape the future of document intelligence.
🔗 View on GitHub
Built by Jagadish Thoutam