Match open orders to the ledger
Source checked before the write
Agents operate in the systems where the work is already done. Retrieval is limited to authorized sources. Each tool call is checked for scope before execution. Changes to a record require approval. The same controls apply to our own delivery.
What we do
A goal is split into steps. The gateway runs them, and the model proposes what happens next.
Permission is enforced in the application, before a call leaves.
Production systems connect through the gateway, with only the scope the task was granted.
Representative cases run before a release.
A change to a record waits for someone on the operating team.
Agents take booking, routing, drafting, and matching through the systems a team already uses. Scope is checked before a call. A change to a record stays with a person.
Authorized steps continue after the response, rather than returning to a manual queue.
Exceptions and record changes remain with the operating team.
Recommendations appear in the workflow where the decision is made.
Multi-step tasks replace repeated manual entry.
Research, evaluation, and operations each run on an agent built for that function.
We start in the operation: the workflow as it runs, the systems it touches, and what has to be true before an agent takes a step.
A golden dataset comes before the build. It holds the cases that should succeed, the requests that should stop, and the sources each case has to read.
Those cases decide the guardrails. Reads, tool calls, and the actions that wait for a person are written down before anything is connected.
The workflow is then built into the systems the team already uses: orchestration, the tool connections, and the approval handoff.
We run the golden dataset against that build, revise the misses, and repeat the pass. Release waits on citation, refusal, and routing.
Work where Agentic AI was part of what shipped.
