MVPs in 4-8 weeks. AI baked into the architecture from day one - not bolted on at the end. Production-ready infrastructure from launch. When the next model ships, you swap. You don’t rebuild.
Built for founders who want real code, not a no-code prototype.
Six months to MVP is the death of momentum. By the time you ship, the opportunity has moved or your seed runway is gone. You need weeks, not quarters - without the no-code ceiling.
The model you started with is already two generations behind. If your AI integration is hard-coded to one provider, every model change becomes a refactor instead of a config swap.
The agency hands you a prototype. Three months later you’re re-platforming because none of the infrastructure was designed for real users, real data, or real load.
Most dev shops bolt a chatbot on the corner of your app. AI as a core capability - infrastructure-grade, integrated with your data, observable in production - is a different skill set.
Each phase is fixed scope and fixed cost. You see the work evolve weekly, not in a single hand-off at the end.
We map your product hypothesis, the AI use case, the data sources, and the success metrics. We define what “done” looks like for the MVP - not for the eventual product.
You walk away with
Lean product spec, schema sketch, AI-flow diagram, success metrics. Used as the contract for the build.
We design the data model in Drizzle, the auth & permissions, the AI orchestration layer (model-agnostic, observable), and the deploy pipeline. Real infrastructure from the start - not throwaway.
You walk away with
Schema in TypeScript, RLS policies, AI integration design, infra blueprint, all reviewable before any feature code lands.
Vertical slices: schema + server logic + UI + tests + AI integration per feature. Weekly syncs. Real product visible from week one. You see the build evolve, not a black-box reveal at the end.
You walk away with
Production-ready MVP deployed on Vercel, observable on Trigger.dev & Supabase, with documentation and handover-ready code.
We support the first weeks in production - monitoring, fixing the surprises, prioritising fast iterations based on real user behaviour. Then a clean handover to your team, or an ongoing retainer if you want us to keep shipping.
You walk away with
Stable launch, instrumentation in place, prioritised post-launch backlog. Handover or retainer - your choice.
These are how we shipped Ohana’s payment system - and how we ship every product. They’re also why those products are still running.
AI orchestration is a first-class layer, not a hard-coded SDK call inside a controller. Observable. Swappable. Testable. Trace AI calls like you trace database queries.
We never hard-code “the model.” All AI traffic routes through OpenRouter (or an equivalent abstraction), so swapping Claude, GPT, or any frontier model is a config change - not a refactor.
Postgres with row-level security, schema in TypeScript via Drizzle, migrations in version control. Not Firebase, not a JSON blob. Real data model from the first slice.
Vercel for hosting, Supabase for data & auth, Trigger.dev for background work, GitHub Actions for CI/CD. The same infrastructure pattern that powers Ohana - on track for $60M+ in annual payment volume in 2026.
Our stack philosophy
Frontend & hosting
Next.js on Vercel. App Router, server components, edge deployment. Hire-able by your future engineering team.
Database & auth
Supabase Postgres with Drizzle ORM. Row-level security for permissions you can audit and version-control.
Background & jobs
Trigger.dev for anything async, scheduled, or retryable. Observable in production. No DIY queues.
AI orchestration
Model-agnostic via OpenRouter. Always the latest model per use case. No lock-in to yesterday’s SDK.
Real product. In your repo. Owned by you. Hire-able by your next engineer.
Sometimes the right move is a no-code prototype to validate the demand first. Sometimes you need to ship a non-AI version of the product to find out whether anyone wants it. Sometimes the “AI” idea is a feature, not a product.
Discovery tells you which one you are. If a code MVP isn’t the right move yet, we’ll say so - and you keep the spec we produced.
30-minute discovery call. Tell us the idea. We’ll talk realistic scope, realistic timeline, and whether we’re the right team.
No NDA. No slide decks. No PM in the meeting.
