AI product development for startups.

AI-native products, end-to-end.

When AI is the core of the product, not a feature bolted onto the side, the build looks different. Model behavior is part of the UX. Eval pipelines are part of the deploy. We design and engineer AI products where the AI is the product.

• AI-native SaaS MVPs — full product, from onboarding to billing, with AI at the center of the value prop.
• Internal AI tools — copilots, assistants, and embedded AI features for ops, support, sales, and research teams.
• AI marketing sites — content, design, and engineering of high-converting sites that put a real AI demo front-and-center.
• Prototypes and proof-of-concepts — production-grade prototypes that let you validate with users in days, not months.
• Model behavior tuning — prompt engineering, retrieval pipelines, fine-tuning, and eval harnesses tuned to your real data.
• API and SDK products — developer-facing AI products with clean APIs, docs, and onboarding.

Founders, product teams, and operators shipping AI.

Early-stage founders who need to ship an AI MVP before the runway runs out. Product teams at established companies that need an AI feature shipped without reorging the whole team. Operators who need an internal tool that actually works in production, not a Notion template.

If you can describe the user problem in two sentences, we can probably help. If you need a six-month discovery phase, you need a consultancy, not us.

From brief to production in 4–8 weeks.

1. Audit — 30-minute call. We map the product, the user, the data, and the model behavior. We confirm AI is the right tool.
2. Design — Fixed-price quote in 48 hours. Plain-English scope, with explicit deliverables: what the product does, what it doesn't, what success looks like.
3. Ship — Working product in week one. We build in production, against real data, with a real deploy from day one.
4. Operate — Optional month-to-month care: we tune evals, monitor quality, ship improvements. Cancel any time.

Modern, boring, shippable.

We work in the modern AI product stack, picking tools that fit the product rather than the other way around:

• Frontend: React, Next.js, TypeScript, Tailwind, shadcn/ui
• Backend: Node.js, Python (FastAPI, Django), Postgres, Redis
• AI: OpenAI, Anthropic Claude, Google Gemini, open-source models (Llama, Mistral)
• Infrastructure: Vercel, AWS, GCP, Fly.io, Supabase
• Tooling: LangChain, LlamaIndex, Pinecone, Weaviate, pgvector for retrieval
• Eval & observability: LangSmith, Helicone, Braintrust, custom eval harnesses

Senior-only. Auditable. Fixed scope.

• Senior-only delivery. Every brief is read by the founder; every line of code is written by the founder. No account managers, no offshore handoffs, no second-rate juniors.
• Design + engineering, one person. You get one decision-maker owning the product shape, the UX, the model behavior, and the deploy. No handoffs, no drift.
• Shipped, not pitched. We measure success on systems running in production on your real data — not on slides or pilots that never end.
• Fixed scope, not retainers. You know exactly what you're paying for and what you'll get. Monthly care is optional and cancel-anytime.

Frequently asked questions.

What kinds of AI products do you build?

AI-native SaaS, internal AI tools, copilots, AI marketing sites, and production-grade prototypes. Anything where AI is the core of the product experience, not a bolt-on.

How long does it take to ship an AI product?

Most products go from brief to production in 4–8 weeks. Marketing sites and prototypes ship in 2–4 weeks. Full SaaS MVPs typically run 6 weeks.

Do you handle design or just engineering?

Both. We do product design, UX, and engineering under one roof. You get one person owning the full surface from product shape to the production deploy.

What stack do you work in?

TypeScript, React, Next.js, Node, Python, Postgres, and the major LLM APIs (OpenAI, Anthropic, Google). We pick the stack that fits the product rather than the other way around.

Can you take an existing product and add AI features?

Yes. We work with both greenfield products and existing codebases. For existing products, the audit call covers what changes are needed and what stays.

More ways we put AI to work.

• AI automation for operations — agents that take over inbox triage, ticket routing, CRM updates, and approvals.
• Custom AI systems — RAG, fine-tuning, multi-agent orchestration, and private deployment.