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I will build rag chatbots for your documents
Keshav Sharma
About this gig
I build custom RAG (retrieval-augmented generation) chatbots that read your PDFs, website, or knowledge base and answer questions accurately, with citations, so your users or team can stop digging through files.
What you get:
- AI chatbot grounded in your own content
- Source-cited answers to reduce hallucinations
- RAG pipeline with semantic search and vector retrieval
- Pinecone vector database integration
- LangChain and LLM API integration
- Clean chat UI or embeddable website widget
- Full source code and admin access
- Setup documentation and handover
I can build AI knowledge assistants for documentation, websites, internal company data, support content, product knowledge, and custom business use cases.
Im a software engineer with hands-on experience building RAG systems using semantic chunking, embeddings, Pinecone vector search, LangChain, and LLM APIs.
Message me before ordering with your data source and use case so I can recommend the right architecture and package.
Get to know Keshav Sharma
Keshav Sharma
Software Developer
- FromIndia
- Member sinceJan 2026
- Avg. response time1 hour
Languages
English, Hindi
I’m a Full-Stack Developer and Backend Engineer focused on building scalable web applications, APIs, and AI-powered solutions. I work with Node.js, TypeScript, Golang, React, Next.js, PostgreSQL, MongoDB, Redis, Docker, and cloud technologies. My experience includes REST APIs, microservices, ERP integrations, database migrations, real-time systems, and RAG-based AI solutions. I focus on clean code, scalable architecture, clear communication, and delivering reliable solutions that solve real business problems.
My Portfolio
FAQ
Will the chatbot actually answer from my data?
Yes. I use a RAG pipeline that retrieves relevant information from your documents, website, knowledge base, or other supported data sources before generating an answer. Source citations can also be included.
Will I receive the complete source code?
Yes. You will receive the complete source code included in your selected package. You can host, modify, and extend the system independently.
What type of data can I connect?
I can work with PDFs, DOCX files, TXT and Markdown files, website content, knowledge bases, and certain structured business data sources. Message me before ordering to confirm your specific source.
What technologies do you use?
Depending on the project, I can use LangChain, Pinecone or another suitable vector database, embeddings, and LLM APIs. The final architecture depends on your data size and use case.
Are AI API and hosting costs included?
No. Any paid LLM API, vector database, cloud, or hosting costs are paid directly by you to the respective provider. I can help estimate the expected running costs before development.
Can the chatbot be integrated into my website?
Yes. Depending on the package and project scope, I can build a standalone chat interface or an embeddable chatbot widget for your website.
Can you add AI agent features or actions?
Yes. The chatbot can be extended with tool calling or agentic actions such as API calls, database lookups, booking flows, or other business actions. These features require separate scoping.
What do you need from me to get started?
Please provide your data source or sample files, the chatbot's intended users, expected use case, preferred deployment environment, and examples of important questions the chatbot should answer.
