AI PDF Chatbot
Chat with enterprise documents instantly.
Built with RAG, vector search, streaming responses, and enterprise-grade access control.
Problem
Manual document search wastes hours across large PDF libraries.
Outcome
90% faster information retrieval with cited, source-grounded answers.
Solution Architecture
Production RAG stack — ingest, index, retrieve, and stream cited answers for enterprise document libraries.
10k+
Pages indexed
<2s
Retrieval p95
SSE
Streaming answers
Ingest pipeline
Upload
FastAPI
S3-compatible storage
OCR
Scanned PDF text extract
Chunk
Overlap-aware splitting
Embed
LangChain
OpenAI embeddings
Query & retrieval loop
Vector DB
Qdrant
Top-k semantic retrieval
LLM
OpenAI
Grounded answers + citations
Citations
- p.12
- p.47
- p.103
What we shipped
Multi-tenant document isolation
Page-level source citations
Private / on-prem deployment ready
Cross-cutting production layer
Key Features
Multi-document chat
Query across entire libraries in one conversation.
Role-based access
Enterprise RBAC keeps sensitive docs internal.
Source citation
Every answer links back to page-level references.
Streaming answers
Token streaming for instant perceived response.
Admin analytics
Usage and ingestion metrics for ops teams.
Tech Stack
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