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Hi all, I work with startups and enterprises to lift existing applications and make them ready for public release—scalable, cost-efficient, and built to last.
If you’re shipping something ambitious, I can be your fractional engineering and AI partner for:
Architecture and technical direction, Scalability and performance, Cloud and infra cost optimization, Hands-on implementation
I’m also building VidForgeX, an AI video intelligence platform—announcing soon.
I like working with founders and teams who want a senior partner, not a ticket-taker. Get in touch and let’s get going.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Ledger — AI CFO Platform
Ledger is an AI platform that acts as an always-on Chief Financial Officer for founders — connecting to accounts, learning cash rhythm, and surfacing risks before they become real problems. I designed the full landing page.
My role: UI/UX Design
Scope: Landing page
Financial tools for founders usually feel either cold (dashboards) or intimidating (accounting software).
For Ledger, we borrowed from old-world institutional finance instead — serif type, oil-painting textures, classical architecture — so an AI CFO feels like real authority, not another app.
This color pallet works so well with data and makes everything look premium. love it!
Built this over a weekend as an experiment with AI-assisted design and development.
Duo Case is an absurd concept for turning two iPhones into a very unofficial foldable iPhone. The goal was to see how far AI could accelerate the process while keeping creative direction, design decisions and final execution in human hands.
A weekend build that looks this polished is wild. Where did AI actually save you the most time here, the concepting or the production grind?
just shipped the core of Skillship — an AI-powered LMS built for schools.
One platform, many schools, and one rule that shaped every decision: School A must never see School B's data. Tenant-scoped models, filtered querysets at the base class, UUIDs everywhere.
Four AI features live:
— Career Pilot: personalised career paths for students
— Question generator: chapter PDF in, board-aligned MCQs out
— Adaptive quizzes: difficulty follows actual performance
— Semantic search: teachers ask in plain English, pgvector finds the material
Django + DRF for the LMS core, a separate FastAPI service for all AI work (Gemini + a pgvector RAG pipeline), Next.js 14 on the front. Django brokers every AI call — the AI layer never touches the browser.
The hard part wasn't the AI. It was making multi-tenancy boring enough that no future dev can leak a school's data by accident.
Open for new work — full-stack builds, AI integrations, RAG pipelines, multi-tenant SaaS. Send me a project.
The tenant boundary is where I'd put the first failure test. I'd try to make a user from one school retrieve another school's record before I trusted any of the AI features.