I will build a rag chatbot and retrieval pipeline for your documents and knowledge base


About this gig
I build RAG chatbots and retrieval pipelines that actually work on real business documents not Streamlit demos that break on anything beyond simple PDFs.
I built the retrieval system behind AskTuring.ai, an enterprise AI knowledge base that processes 15+ document formats with accuracy that outperformed every off-the-shelf RAG solution we tested.
If you have tried a basic RAG setup and got frustrated by wrong answers, hallucinations, or missed context from tables and images that is exactly what I solve.
What I build that basic RAG chatbot gigs do not:
- Custom chunking strategies optimized per document type (not one-size-fits-all 512-token splits)
- Hybrid retrieval combining semantic search + BM25 for dramatically better recall
- Citation tracking with source provenance know exactly where every answer comes from
- Multi-format document handling: tables, scanned PDFs, images, spreadsheets, mixed-content docs
- Evaluation pipelines with retrieval metrics so you can measure quality
- Production deployment with monitoring a real API, not a demo
Message me before ordering to discuss your RAG chatbot requirements.
Get to know Talha J. Siam
Senior Software Engineer
- FromBangladesh
- Member sinceApr 2026
- Avg. response time1 hour
Languages
English
FAQ
How is this different from a $100 RAG chatbot gig?
Most budget gigs use default LangChain settings — fixed chunk sizes, single embedding model, basic similarity search. The result works on simple PDFs but breaks on real business documents with tables, images, or complex formatting. I build custom retrieval pipelines tuned to your specific documents.
What document formats does your RAG system support?
PDF (text and scanned), Word, Excel, PowerPoint, HTML, Markdown, CSV, images with OCR, and custom formats. The Premium tier includes intelligent format detection with OCR fallback for scanned documents.
Can the RAG chatbot integrate with my existing application?
Yes — I deliver a production API (REST or GraphQL) that your application calls. Not a standalone demo. This plugs into your existing product, internal tool, or customer-facing app.
