AI Products That Survive the Demo — and the Second Run.
Most AI products are great in the demo and bad in production. We design and build the ones that hold up when the data drifts, the prompt evolves, and the users keep coming back.
Built for: AI startup founders, model interface teams, and agentic-product builders
What we know about AI startups.
Model output isn't the product. The product is everything around the model — prompts, grounding, evaluation, observability, recovery from bad outputs.
Evaluation is design. If you can't measure quality, you can't ship. Eval harnesses are first-class artifacts, not afterthoughts.
Cost is a design constraint. Caching, batching, model routing, and prompt compression are the difference between a product and a money-losing demo.
Agents need brakes. Tool-using agents take action. The interfaces and guardrails matter more than the model behind them.
The interface is most of the moat. Models commoditize. Brand, UX, and integration depth don't.
What we build for AI startups.
Model interfaces, agent platforms, RAG systems, and the design layer that makes any of it usable.
Recent work in this space.
AI Startups questions, answered.
- Whatever fits the use case. Claude (Anthropic), GPT (OpenAI), Gemini (Google), Llama / Mistral / DeepSeek (open-source). We pick based on capability, cost, latency, and your data residency needs.
Build an AI product that survives production.
Book a free 30-minute call. We'll audit your model interface, agent system, or eval setup.