I will build a rag ai chatbot trained on your documents with vector search

A
amansin001
A
amansin001
Aman

About this gig

Give your customers or team instant, accurate answers from your own documents, with sources they can check.


I build Retrieval-Augmented Generation (RAG) chatbots that search your content using vector embeddings and answer with OpenAI or Claude models, grounded in your data instead of guessing.


What you get:

- Ingestion of PDFs, DOCX, web pages, Notion/Docs exports or database content

- Smart chunking, embeddings and similarity search (pgvector, Pinecone or similar)

- Answers with citations and an 'I don't know' fallback to reduce hallucinations

- Clean chat UI in Next.js/React, or an API you can plug into your product

- Optional auth, usage logs and feedback buttons

- Deployment and a clear README


Why me:

7+ years full stack (React, Next.js, Node.js, Python, AWS) with hands-on experience in NLP pipelines, embeddings and similarity search. I care about retrieval quality, not just a pretty chat box.


Send me a sample of your documents and your use case before ordering.

Get to know Aman

Aman

Professional software engineer

4.9(149)
  • FromIndia
  • Member sinceAug 2013
  • Avg. response time1 hour
  • Last delivery3 years
  • Languages

    English
I'm Aman, a full stack engineer with 7+ years building production web apps, APIs and cloud systems. I help startups and businesses ship reliable software fast. What I do: - MCP servers, AI agents and LLM tool integrations - RAG chatbots with vector search - React and Next.js apps, SaaS MVPs - Node.js, Python and Java APIs and integrations - AWS serverless debugging, Docker and Kubernetes I focus on clean code, clear communication and on-time delivery. Message me before ordering and I'll reply quickly with a clear plan.