AI agents doing real work, reliably.
Three workflows our customers run on Meerkats. We keep their names private and show you what each agent had to know before it could act, the rules it works inside, who can change what, and the record every run leaves.
Different work. The same way of making agents reliable.
A short list per workflow: which information to trust, what the terms mean, which rules apply, what it may do. The agent becomes reliable once that list exists.
The catalog is the single name authority. Every agent, workflow and report uses the same meaning, so nobody reconciles numbers.
Each run reads the timeline, the state and the rules from the context layer. The model never sees raw rows, so runs are cheap and the same every time.
Every write is a registered, permissioned operation with a cap, a verify read and a rollback. Nothing else can write.
Those actions run alone. Everything else stages a plan with its evidence and waits.
Inputs with sync time, the rule, the plan, the approver, the change, the read-back, and the outcome afterwards. Open any run.
Bring us one workflow. We’ll start there.
We connect the systems you already run, write down what the agent must know before it acts, and start with recommendations before actions. The next workflow reuses what the first one built.