AI-native operations,
under close watch.
Agents wired to the tools you already use, automation that fails closed, and claims governed by evidence, so the AI never outruns the truth.
What this looks like
Agents wired to the tools you already use.
An operator surface, the same pattern behind our own Grepler, that lets an AI agent work across your apps with per-user auth and permissions, instead of thirty open tabs.
Every claim mapped to a source.
An evidence library ties each product and marketing claim to where it came from, so the AI-written copy never says something you can't back up.
Automation that stops before it spends.
The plumbing underneath is fail-closed and reversible: it runs in observation mode first, is engineered to stop before it spends, and switches back with one flag.
The work writes down what it learns.
We capture what we learn as we learn it, and the system reads it before it acts, so AI-driven work stays correct instead of relearning the same thing every time.
How we start
A two-week paid discovery, so the plan isn't a guess.
We map where AI actually helps, and where it would just add risk, then come back with a concrete plan. From there, a flat monthly retainer on a three-month trial, with a weekly report tied to real outcomes.
Start a build
Put AI to work, carefully.
Tell us where you think AI could help. We'll come back with a two-week discovery plan, and an honest read on where it shouldn't.
Book a discovery →