I will build a rag chatbot for your documents or knowledge base


Over deze dienst
Need an AI chatbot that can answer questions using your own documents or knowledge base?
I will build a custom RAG (Retrieval-Augmented Generation) chatbot that retrieves relevant information from your data before generating an answer.
This can be useful for company documentation, product information, FAQs, internal knowledge bases, manuals, policies, research material, and other structured or unstructured documents.
What I can build
Document-based AI chatbots
Knowledge-base assistants
PDF/document Q&A systems
RAG pipelines
Vector-search based retrieval
LLM-powered question answering
Source/context-grounded responses
Streamlit AI interfaces
Custom retrieval and response workflows
Typical workflow
Your Documents Processing Embeddings Vector Search Relevant Context LLM Answer
I can also add validation or human review steps when the application should avoid answering when sufficient information cannot be retrieved.
Technologies
Python · RAG · LLMs · LangGraph · Vector Databases · NLP · Streamlit · APIs
I can work with your existing documents and requirements, or help structure the retrieval workflow around your use case.
Please contact me before ordering if you need custom integration
Maak kennis met Sahil Kaushik
- Afkomstig uitIndia
- Lid sindsmei 2022
- Gem. reactietijd1 uur
Talen
Engels, Hindi, Punjabi
Mijn portfolio
Veelgestelde vragen
What documents can you use?
I can work with common document and text-based knowledge sources such as PDFs, text documents, FAQs, and structured knowledge bases. The exact format should be discussed before ordering.
Can the chatbot answer only from my documents?
Yes. The workflow can be designed to retrieve relevant context and restrict responses when sufficient supporting information is not available.
Can you add a web interface?
Yes. I can build a simple interactive interface using Streamlit or integrate the RAG workflow into an existing application depending on the requirements.
Can you use my existing LLM or API?
Yes, where the provider offers a suitable API and the required credentials/access are available.
Can you add citations or sources to answers?
Yes. The application can be designed to expose the retrieved document or source information used to generate an answer

