// founder & ai engineer
> I build
I build AI-native products that turn business bottlenecks into momentum — autonomous agents that take action, intelligence that actually understands your data, and full-stack platforms shipped to production. Now building that for my own startup.
whoami
Founder & AI Engineer — computer vision, generative & agentic AI
cat highlights.txt
→ Shipped 10 production AI services — vision, voice and agentic pipelines
→ 91% top-1 precision on a web-scale face-matching engine
→ 98%+ reliable image retrieval pipeline under load
→ Voice-cloning platform live on AWS S3 + DynamoDB
./run --stack
Python · FastAPI · Multi-Agent Systems · LangGraph & n8n · RAG / Vector DBs · AWS + Azure
Who Am I?
For the last 3 years, I've been turning ambitious ideas into production systems that actually work — at scale, across industries, and around the world.
Now, I'm bringing that discipline to my own startup.
An AI-powered SaaS built to eliminate the bottlenecks that hold businesses back.
Turn bottlenecks into momentum.
Core Capabilities
RAG chatbots and private AI assistants — not generic API wrappers.
Production-grade vision pipelines — detection, face matching and identity verification at web scale.
Voice cloning and generative audio/image pipelines, from a single sample to production output.
Multi-agent systems with tool calling, LangGraph & n8n orchestration, and ecosystem integrations that take action, not just trigger alerts.
Full-stack, AI-native SaaS platforms built from concept to production — modern frontends, robust backends and scalable databases.
Cloud-native deployment — containers, managed ML infra and observability baked in.
production AI systems that shipped, not notebooks that ran once
An agentic AI service for voice cloning and audio generation from a single sample — autonomously handling clone regeneration, multi-output creation and resource optimisation. Integrates ElevenLabs' voice models with a FastAPI backend on AWS S3 + DynamoDB. If a user's clone goes missing, the backend regenerates it on the fly from the original sample, transparently to the user.
Self-healing clones — missing voice clones are regenerated automatically from the stored sample
Thread pooling & semaphores handle simultaneous requests without blocking
Outputs auto-expire after 10 minutes to keep the system memory-optimised at scale
A production system that finds visually similar faces on the web from a single uploaded photo, ranking results with learned embeddings and cosine similarity. Combines YOLOv8 person detection with InsightFace face embeddings behind a FastAPI service with background jobs, concurrency controls and fault-tolerant downloads, deployed on AWS ECS Fargate.
~91% top-1 precision@10 on an internal validation set
>98% download success rate with retry and circuit-breaker logic
~1.8s median latency for 20 candidates on a T4 GPU
A high-performance FastAPI microservice that detects and counts juggling patterns in video, supporting both direct uploads and S3-based processing. Built on YOLOv11 with asynchronous task management, configurable resource limits and automatic cleanup — designed for sports analytics and automated video analysis at scale.
Async, non-blocking processing for large video files
Full HTTP error taxonomy, retry logic and health-check monitoring
A domain-specific face verification service built entirely from scratch, without pre-trained models. Trained on curated image datasets to encode facial features, verify a submitted image against known identities, and return structured metadata — name, age and other attributes — with a confidence score, backed by MySQL.
Custom-trained feature encoding, no third-party face-recognition API
Structured, JSON metadata output for easy integration into other pipelines
I'm building AI-native products that eliminate real bottlenecks — automation, intelligence and full-stack platforms shipped to production, not proofs of concept. If that's useful to you, the fastest way to reach me is email; I usually reply within a day.