Custom AI Agents and RAG Systems with LangChain and LangGraphAbdul Haseeb
I build custom AI agents that actually do work for your business: answer from your own documents, call tools, take actions and hand off when they should. Built for real use, not demos.
What I can build:
RAG assistants that answer from your PDFs, docs, website or database, with sources
Multi-step agents with tools (search, email, CRM, databases, APIs) using LangGraph
Multi-agent workflows where specialized agents work together
Internal copilots for support, sales, operations or research
Guardrails, logging and human approval steps for sensitive actions
What you get:
A working agent deployed and connected to your systems
Vector database setup (Pinecone or similar) with your data indexed
Clean, documented code that you own
A handover call and a short usage guide
How it works: we start with a scoping call, I propose the architecture and timeline, then I build in stages with demos along the way.
Pricing depends on scope, so message me with your use case and I will send a clear quote.
FAQs:
Can it use my private data safely? Yes. We decide together where data lives and which model providers are used. Local or private model options are possible for sensitive data.
How do you reduce wrong answers? Grounding in your documents, retrieval tuning, source citations, and test sets to check quality before launch.
Do I own the code? Yes. Full handover is included.
Example work
Contact for pricing
Duration4 weeks
Tags
AI Agents
LangChain
LangGraph
Multi-Agent Systems
OpenAI
Pinecone
Python
RAG
LLM Applications
Service provided by
Abdul Haseeb Karachi, Pakistan
Custom AI Agents and RAG Systems with LangChain and LangGraphAbdul Haseeb
Contact for pricing
Duration4 weeks
Tags
AI Agents
LangChain
LangGraph
Multi-Agent Systems
OpenAI
Pinecone
Python
RAG
LLM Applications
I build custom AI agents that actually do work for your business: answer from your own documents, call tools, take actions and hand off when they should. Built for real use, not demos.
What I can build:
RAG assistants that answer from your PDFs, docs, website or database, with sources
Multi-step agents with tools (search, email, CRM, databases, APIs) using LangGraph
Multi-agent workflows where specialized agents work together
Internal copilots for support, sales, operations or research
Guardrails, logging and human approval steps for sensitive actions
What you get:
A working agent deployed and connected to your systems
Vector database setup (Pinecone or similar) with your data indexed
Clean, documented code that you own
A handover call and a short usage guide
How it works: we start with a scoping call, I propose the architecture and timeline, then I build in stages with demos along the way.
Pricing depends on scope, so message me with your use case and I will send a clear quote.
FAQs:
Can it use my private data safely? Yes. We decide together where data lives and which model providers are used. Local or private model options are possible for sensitive data.
How do you reduce wrong answers? Grounding in your documents, retrieval tuning, source citations, and test sets to check quality before launch.
Do I own the code? Yes. Full handover is included.
Example work
Contact for pricing