Abhinraj N A

You don't need another chatbot. You need an AI system that actually gets work done.

That's what I build.

I build AI automations, RAG systems, LLM applications, and AI agents that take repetitive knowledge-work off your team's hands.

Think:
→ Reading and extracting information from hundreds of documents
→ Searching internal knowledge and giving grounded answers
→ Screening and matching candidates
→ Researching information across multiple sources
→ Classifying, comparing, and processing business data
→ Turning multi-step manual workflows into AI-powered systems

My approach is simple:
Understand the workflow → find where the real bottleneck is → build the AI system around it.
I'm not interested in adding an LLM just because it's trendy.
If a normal piece of code solves the problem better, I'll use code.
If RAG is needed, I'll build RAG.
If the workflow needs an agent, I'll build an agent.
If the AI needs guardrails and human approval, I'll build those in too.
I've built systems using Python, FastAPI, LangGraph, LangChain, CrewAI, PostgreSQL, ChromaDB, embeddings, semantic search, structured outputs, and LLM APIs.

One of my current projects, RecruitIQ, is an AI recruitment platform that doesn't simply throw candidates into an LLM and ask for a score. It uses semantic retrieval → structured matching → LLM-generated explanations to evaluate candidate-job fit. I also built a LangGraph research system with conditional workflows, parallel verification, checkpointing, streaming, and human approval.
If you have a workflow that currently requires people to read, search, compare, classify, research, or respond manually — send it to me.
I'll tell you where AI can actually help, what I'd automate, and how I'd build it.
No AI for the sake of AI. Just useful systems that solve real problems.