AI Product Development
End-to-end builds from idea to production-grade product. Real pipelines, decision systems, and applied models tuned to your constraints — not a demo that falls apart when real users show up.
Who this is for
Teams with a clear problem that AI can solve but no in-house expertise to build the solution. Founders who've seen a demo and need someone to turn it into a product that works at scale. Companies that tried a dev shop, got a prototype, and realized it can't handle production traffic.
How it works
Every engagement starts with a scoping phase where we define the problem, success criteria, and technical constraints. Then we build in focused sprints with weekly demos — you see working software every week, not a big reveal at the end.
The deliverable isn't a notebook or a proof of concept. It's a deployed, monitored, documented production system with clear ownership handoff.
What I've built
- HIPAA-compliant AI platforms processing real patient data
- Real-time computer vision pipelines for live sports analytics
- On-device AI systems running 100+ language translation offline
- Web3 commerce platforms with blockchain-backed digital assets
- Enterprise analytics pipelines supporting thousands of daily users
Requirements & Architecture
Problem definition, system design, and technology selection grounded in your real constraints.
Full Build
Frontend, backend, ML pipeline, API layer — whatever the product requires, from prototype to production.
Deployment & Infrastructure
Cloud setup, CI/CD, monitoring, and production hardening so the system runs without you babysitting it.
Documentation & Handoff
Clean codebase, architecture docs, and knowledge transfer so your team can maintain and extend it.
Clear deliverables, fixed timeline, weekly demos. Scoped on a call and documented before any code is written. Typical builds run 4–12 weeks.