// autonomous software company
We grow agents that run real business operations.
Each agent starts as a seed, is cultivated against live production data, and ships only when it beats the human baseline.
// the method
Grown, not shipped.
Plant
Every agent starts inside a real operation — a question someone is paid to answer, a job someone already runs by hand. The seed is a live problem with an owner, never a synthetic demo.
Cultivate
It grows against production data with a human in the loop, and its answers are scored against ground truth that human confirmed. Wrong and visible is survivable. Confident and wrong is the failure we breed out.
Gate
It ships only when the measurements clear the bar — and the bar travels with it. Every agent carries its scorecard in production, where the people relying on it can see it.
what every agent inherits
- reads before writes write access is earned last, if at all
- no shell a fixed tool surface; running commands isn't on it
- eval-gated confirmed answers stand between changes and production
- measured in the open the scorecard ships with the agent, not the pitch
// the roster
One shipped. More in the ground.
Evalyst
private betaThe AI analyst that has to prove it's right.
Evalyst connects to your databases — and writes its own connectors for everything else you can describe: the billing API, the internal service. It answers the questions a founder would otherwise dig out with a SQL client at midnight, with a discipline most analysts never get held to:
- connects by description no connector? the agent writes one, tests it in a sandbox, and registers it only if it works
- read-only, proven credentials that can write refuse to activate when a source attaches
- gated by confirmed answers every change re-runs a bank your team signed off on; one silent error and it doesn't ship
- no LLM at refresh dashboards re-run stored SQL, so a number moves only when the data moves
more agents are in cultivation — each one is named when it beats its baseline.
// the soil
The farm has real soil.
Smart Agents Farm grew out of a usage-billing video platform, where the first agent learned its trade answering revenue questions that used to take a founder and a SQL client at midnight. That's the pattern: agents are raised inside businesses that depend on the answers — not built for demos and adapted later.
// people
No open roles right now.
If you've spent time teaching software to know when it's wrong — or being the person who finds out why the number changed — introduce yourself anyway.
contact()
hello@smartagents.farm — a human answers. For the product, evalyst.ai has its own door.