Cross

Knowledge and controlled action

Let an agent work across CRM and ERP with controlled actions

Employees gather data in one system and update another, and a wrong or repeated write causes problems.

Who this helps

COO, CIO, Enterprise applications leader, Process owner

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The situation

Employees collect information in one system and make changes in another. A chat agent can describe the steps, but a wrong or repeated write could create operational problems. CRM and ERP have different identities, data models and update timing. One write can succeed while the next times out, and simply repeating the whole request can duplicate work.

What we build

We build an agent that can act across systems only through bounded, verified steps.

  • The agent reads relevant records through scoped connectors, within a bounded process and approved state transitions.
  • It builds a typed action proposal with before and after values and preconditions, then pauses for the required approval.
  • After approval it rechecks current state, executes with a unique transaction key and verifies each downstream result. Step status is saved so recovery starts at the failed step.
  • A stale record stops the write and refreshes the proposal. Timeouts check transaction status before any retry. Reversing a completed step follows business rules and may need manual correction, and irreversible actions are never presented as safely undoable.
  • Read and write scopes are separate, credentials are protected and retrieved records cannot authorize a tool call. We identify every remote business-system API and model call, even when the agent itself runs privately.

What you get

  • An action proposal. Typed before and after values, preconditions and the source of each fact, ready for approval.
  • An execution record. The approved action and the verified result in each system it touched.
  • Recovery tasks. Incomplete or disputed operations become explicit tasks that start at the failed step.

Where people stay in control

  • The process owner approves allowed actions and value limits.
  • A person confirms consequential changes with the exact object and values visible.
  • The application checks authorization immediately before execution, and approval expires if the proposal or target changes materially.

When another approach fits

A deterministic integration is better for stable, fixed rules. Add an agent when interpreting varied requests changes the plan and the bounded tools can still enforce policy.

Related work

Scope it with us

Bring the workflow, the data you can share and the decision it supports. We agree how the work will be evaluated before anything is built.

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