Agents
Systems that decide
Multi-agent architectures with real tool use, hand-off between specialists, and a latency and cost budget that survives production traffic.
LangGraph · Pydantic AI · MCP · OpenAI · Claude · Gemini
AI Engineer · Lahore, Punjab, Pakistan · Open for work
I build agentic AI systems, voice agents, RAG pipelines and computer vision models. Trained, deployed and left running in production. 150 repositories of it, in the open.

What I actually do
Most of my work is the distance between those two things: labelling the data properly, choosing the smallest model that clears the bar, and building the service around it that a team can run without me.
Agents
Multi-agent architectures with real tool use, hand-off between specialists, and a latency and cost budget that survives production traffic.
LangGraph · Pydantic AI · MCP · OpenAI · Claude · Gemini
Voice
Agentic voice assistants that listen, reason and answer inside a turn. Live transcription, tool calls mid-conversation, speech back without the wait.
AssemblyAI · ElevenLabs · DeepSeek · Realtime APIs
Language
Retrieval over private documents, knowledge graphs where relationships matter, and federated setups for data that is not allowed to move.
LangChain · Vector databases · Neo4j · Hugging Face
Vision
Detection and recognition models trained on custom footage, then wrapped in a streaming inference service the camera can actually feed.
YOLOv11 · Ultralytics · OpenCV · MediaPipe
Selected work
A multi-agent system where research, analysis and recommendation agents divide a market question between them and report back with reasoning.
Multi-agent pipeline
A real-time voice agent wiring DeepSeek-R1 reasoning to AssemblyAI transcription and ElevenLabs speech, tuned for turn latency.
Real-time turns
A research assistant built on the programmatic agent hand-off pattern, so a question moves between specialist agents instead of one model guessing.
Agent hand-off pattern
Production-ready retrieval that builds a knowledge graph first, so answers follow relationships in the source material rather than nearest-neighbour luck.
Graph-grounded answers
A YOLOv11 detector trained on a custom facial dataset that reads emotion straight from a live video feed, class by class, frame by frame.
5 emotion classes, real time
Workplace safety monitoring that flags smoking in real-time camera feeds, built for sites where a missed detection is a compliance failure.
Live video inference
Available for work
Send the problem, the data you have, and the deadline. You will get a straight answer about whether AI is the right tool for it.
Start a project