Perfumind
An AI fragrance discovery platform I built solo, end to end: a Next.js web app, a FastAPI/LangChain backend and Supabase, with LLM-orchestrated research and recommendations across a catalogue of 4,000+ perfumes.
Writing on AI engineering, LLM tooling and shipping software to production, plus in-depth write-ups of the projects I’ve built.
An AI fragrance discovery platform I built solo, end to end: a Next.js web app, a FastAPI/LangChain backend and Supabase, with LLM-orchestrated research and recommendations across a catalogue of 4,000+ perfumes.
A Model Context Protocol server that gives AI agents structured movie and TV data through 23 tools, with an LRU cache that cuts upstream API calls by 50–75%.
My BEng dissertation at the University of Sheffield: a custom instance-segmentation model that finds grape bunches in vineyard images and video, reaching an 82% F1 score at IoU 0.50 with 0.3 s inference.
My MSc project: a web platform that deploys cloud-native network functions on Kubernetes and continuously retunes their autoscaling from ML forecasts, reducing cost by 5–10% on fluctuating workloads.
A Word-to-PDF conversion service built as five microservices on Kubernetes, with RabbitMQ queues for asynchronous processing, MongoDB GridFS for file storage and JWT authentication. Designed to absorb up to 50,000 conversion requests.