AI in your product
When the agent needs a home, we build it: AI features inside an existing product, customer-facing assistants and search, and the dashboards and admin panels your team uses to supervise agents. We shipped our own agent product, Leafer, the same way.
What we build
- AI features inside an existing SaaS
- Customer-facing assistants and smart search
- Dashboards and approval queues for your agents
- New AI products from blank repo to launch
How we think about it
An AI feature is only as good as the product around it. We build both, so nothing falls between the seams.
What you get
- AI features users actually use
- A product that is live, not a prototype
- A codebase the next engineer can read
- Releases every week
Built with
- TypeScript, React, Next.js
- Node, Postgres, background workers
- Design systems and accessible front ends
- CI/CD, monitoring, performance budgets
Audit, pilot, then run.
Audit
We map where your team loses time, pick the one or two jobs worth automating first, and estimate the saving.
Pilot
We build the first agent or automation on your real data and tools, with a person approving its output.
Run & improve
We monitor it, measure accuracy and time saved, and widen what it handles as trust grows.