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Reference build · Agent Ops Console

Let agents act. Keep people accountable.

A reference console that brings flagged AI decisions, supporting evidence and human approvals into one review workspace.

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What this demonstrates

Agent Ops Console project cover

The gap this closes

An agent that runs end to end still needs someone accountable for the calls that matter. The promise of escalating only what it genuinely cannot settle needs a place for that escalation to go: somewhere a person can see a decision, understand why the agent made it, and approve or reverse it, with a record that holds up later.

The review queue

Decisions arrive as structured events rather than opinions. Each one carries the proposed action, the inputs the agent used and a confidence score. Most clear automatically. Only the items a rule flags reach a person, sorted so that the riskiest, meaning low confidence and high value, sit at the top of the queue.

The review queue. Only what a rule flags reaches a person, sorted so low confidence and high value sit at the top.
The review queue. Only what a rule flags reaches a person, sorted so low confidence and high value sit at the top.

The decision, up close

On a flagged item the reviewer sees the whole picture: the proposed action, the evidence behind it, the source document the agent read and the fields it extracted, and a plain read on why the agent was unsure. From there it is one click to approve, edit, override with a reason, send back or escalate.

A flagged decision up close: the proposed action, the evidence, the source document and the fields extracted from it.
A flagged decision up close: the proposed action, the evidence, the source document and the fields extracted from it.

Every override is training data

An override is not just a correction. It is captured with a reason code and fed back, so the same case is handled automatically next time and the share of decisions needing a person keeps shrinking. The audit log underneath is immutable and hash chained, because these are real business actions such as orders dispatched and payments approved, and they have to be defensible later.

The audit log underneath, immutable and hash chained, because these are real business actions.
The audit log underneath, immutable and hash chained, because these are real business actions.

The escalation policy is the product

What reaches a person is a rule rather than a guess. Confidence and value thresholds, categories that always get a look, and a hold when the agent is unsure. Tuning that policy is where the time savings live, and a metrics view shows the loop tightening as overrides train the agent.

The routing policy and the metrics that show the loop tightening as overrides train the agent.
The routing policy and the metrics that show the loop tightening as overrides train the agent.

Where the line is

The console is for decisions a person should be able to see and reverse. Genuinely low stakes autonomous steps do not need it, and wrapping them in review only adds friction. Drawing that line for each workflow, deciding what the agent owns and what a person signs off, is part of the build.

How to engage with us

Good work starts
with a conversation.

Tell us what you want to build or improve, and we will come back with a practical next step rather than a sales sequence.

Teams we have worked with

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