AI for product teams
Customer-facing AI features built right. Internal tools that beat Retool. Prototype-to-production handled.
プロダクトチームが任せる3つの業務
Customer-facing AI feature
In your design system, with the eval harness.
Internal admin / ops tools
Auth, rbac, audit logs — beyond retool.
Prototype-to-production
V0 or bolt prototype → real production build.
プロダクトチームのために構築するもの
Customer-facing AI feature
Built into your product, in your design system, with the eval harness to know it works. Not a chat box bolted on.
Internal admin / ops tools
Replaces the Retool app your team has outgrown. Auth, RBAC, audit logs included.
Prototype-to-production
Take a v0 or Bolt prototype, deliver a production-grade build on top. Auth, payments, infra, error handling.
AI eval + observability
Confidence that the feature actually works in production. Logging, prompt regression, hallucination guards.
よくあるご質問
We have a v0 or lovable prototype — can you ship it to production?
Yes. that's a common shape. we take the prototype as the brief and build the production version on top: streaming, eval suite, audit logging, in-product ux in your design system.
What does the ai eval harness actually cover?
Prompt regression tests, hallucination guards on cited fields, latency budgets, and logging of inputs, prompt, model, output, reviewer per call. enough that when the model version changes you know within an hour whether the feature still works.
How do you avoid shipping another chat box bolted on?
We start from the workflow, not the chat ui. for the fintech assistant we mapped the three highest-volume support tickets first, then built the feature inside the existing in-app surfaces. chat is one mode among several — not the default just because it's the fastest demo.
