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English
$
USD
I will build rag ai agents with langgraph, crag and self rag
Pranav
About this gig
Looking to integrate an AI model into your application, build a custom chatbot, or create a knowledge-base system that can answer questions from your documents?
I can help you build custom AI solutions using RAG, advanced retrieval, and MCP integrations designed around your projects requirements.
What I can build for you
- AI LLM integration
- Standard and advanced RAG systems
- End-to-end RAG pipelines
- Custom document-based chatbots
- CRAG / Self-RAG implementations
- MCP and custom tool integrations
- AI applications connected to your existing backend
RAG Systems I Build
Standard RAG
- Document ingestion
- Chunking & embeddings
- Vector database
- Semantic retrieval
Self-RAG
- Retrieval decision-making
- Relevance evaluation
- Self-reflection
- Answer quality checking
CRAG (Corrective RAG)
- Retrieval quality evaluation
- Corrective retrieval
- Web retrieval fallback
- Hallucination reduction
Tech Stack
- Frameworks: LangGraph, LangChain, FastAPI, MCP
- Databases: Supabase, FAISS, Pinecone, Qdrant, ChromaDB
- Models: OpenAI (GPT), Anthropic (Claude), Gemini LLMs
Please message me before placing an order so we can discuss your requirements and select the right package.
Get to know Pranav
Pranav
AI Engineer
- FromIndia
- Member sinceJul 2024
- Avg. response time1 hour
Languages
Hindi, Punjabi, English
I’m an AI Engineer specializing in building AI agents, RAG applications, and production-ready LLM systems. I can help businesses turn AI ideas into reliable, scalable applications—from intelligent chatbots and document Q&A systems to autonomous multi-agent workflows.
* Experienced with Python, LangGraph, LangChain, RAG, FastAPI, and LLM APIs
* Build AI agents and multi-agent systems for real-world business workflows
* Develop RAG systems for PDFs, documents, websites, and knowledge bases
* Experienced with Docker, MLOps, vector databases, and cloud deployment
My Portfolio
FAQ
Can you build a RAG chatbot or knowledge-base AI agent?
Yes. I can build RAG systems that use your PDFs, documents, websites, databases or company knowledge to provide contextual answers. I can integrate vector databases such as Pinecone, Qdrant, Supabase or pgvector.
What technologies do you work with?
I typically work with Python, TypeScript/JavaScript, React, Next.js, Node.js, FastAPI, PostgreSQL, Docker, and AI tools such as LLM APIs, vector databases, and RAG pipelines.
What type of RAG you can build? And which is best for me.
I can Build standard RAG, CRAG (Corrective Retrieval-Augmented Generation) and Self RAG (Self-Reflective Retrieval-Augmented Generation) Which one is best for you :- Contact me before ordering, and I can recommend the most suitable one for you
