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Token costs change everything.
A working demo and a sustainable product are different things. We size context, cache aggressively, and pick smaller models for the hot paths so the unit economics survive a paying user base.
Strategy, design, engineering, and AI integration under one roof. Real software you own, in weeks.
The wins come from the same place they always did, but the failure modes are new. Four of them show up on almost every build we've seen.
A working demo and a sustainable product are different things. We size context, cache aggressively, and pick smaller models for the hot paths so the unit economics survive a paying user base.
GPT-4 to Claude to a fine-tune to whatever ships next. We keep the model behind a single interface in your code, so swapping providers is a config change, not a rewrite.
Most AI products show up well in a 60-second demo and lose users by day three. We design onboarding around getting one real result inside the first session, before anyone tours the features.
PII handling, data residency, audit logs, SSO, retention policies. We design with those questions in mind so the first enterprise security review doesn't become a six-week rewrite.
A working default stack we ship most projects on. We'll change the parts that don't fit, and explain the tradeoffs when we do.
Next.js, React, TypeScript, Tailwind, shadcn/ui
Node + TypeScript or Python, Postgres, Redis
OpenAI, Anthropic, Google, open-source via Together or Replicate
pgvector, Pinecone, or Weaviate, depending on scale and ops budget
Clerk or Supabase Auth, Stripe for subscriptions and metering
Vercel or AWS, deployed in your cloud account from day one
Weekly demos, weekly progress updates, and your repo on day one. You always know where the build is, and what the next deliverable looks like.
Two or three working sessions. We map the user, the job to be done, and the one workflow the product has to be excellent at. You leave with a written scope and an architecture sketch, even if you don't hire us.
Wireframes, prototype of the core flow, model and provider choice, data model, and a cost-per-user estimate. This is where we kill the features that won't move the needle.
Code lives in your GitHub from day one. We deploy to your hosting, your domain, your accounts. Friday demos, weekly Loom updates, and a shared Linear board. No monthly check-in surprises.
Cost guardrails, error budgets, eval coverage on the prompts that matter, auth flows pen-tested. We run the launch with you, watch the first wave of users, and stay close for the first 30 days.
Not a comprehensive list, just the ones we keep ending up on. If your idea looks like one of these, we already have a head start.
Industry-specific tools where the moat is the data model and the prompts, not the base model. Legal review, clinical notes, real-estate lease abstraction, fintech reconciliation.
Multi-tenant SaaS with the AI doing the work the user used to do manually. Procurement-ready, SSO from day one, role-based access, and audit logs that survive enterprise security reviews.
Products that take actions, not just answer questions. Tools, memory, human-in-the-loop, and clear escape hatches for when the agent gets it wrong (because it will).
APIs, SDKs, and developer-facing products where the integration story matters more than the marketing site. We ship docs, code samples, and SDKs alongside the product.
One AI-native interface replacing a multi-tab, multi-tool internal workflow. Drafting, summarisation, extraction, review, and the boring glue around them.
Two-sided platforms for prompts, agents, fine-tunes, or models. Trust, payments, search, and a content-quality bar that doesn't collapse under spam.
Pricing depends on what you're building, who it's for, what infrastructure you're bringing, and how fast it has to ship. We'll quote in writing before any work starts, with a fixed scope and a fixed timeline.
The discovery call is free. The scope doc you walk away with is yours, even if you don't hire us.
The ones founders ask before kicking off a build. Don’t see yours?
Ask on a discovery call4 to 8 weeks for an MVP, 10 to 14 weeks for a full multi-tenant build. Both are fixed-scope and fixed-timeline. Discovery, design, and architecture happen in the first two weeks before any production code is written.
Yes. Code lives in your GitHub from day one. Production runs in your cloud account, on your domain, with your secrets. We hand over keys, never gate access, and don't insert proprietary middleware between you and your stack.
Default: Next.js + TypeScript + Tailwind on the frontend, Node or Python on the backend with Postgres + Redis, OpenAI / Anthropic / Google for AI providers, Clerk or Supabase for auth, Stripe for billing, Vercel or AWS for hosting. We'll change parts that don't fit and explain the tradeoffs.
Every AI call sits behind a single interface in your codebase. Swapping GPT for Claude, or to a fine-tune, is a config change rather than a rewrite. You stay portable as the model landscape moves.
We model cost-per-user before architecture, with caching, context sizing, and routing built in to protect margins. You launch with a per-user cost dashboard so you can see margins at every tier.
30 days of stabilisation are included by default. After that, optional ongoing partnership for new features, model upgrades, and scale work. Or your team can take it from here with the documentation we hand over.
30 minutes, no pitch. Walk us through the idea and we'll tell you whether it's an MVP shape or a full build, what the stack should look like, and what we'd ship in the first 4 weeks.