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Purpose

Every AI output in Exterview is itself evaluated, traced, and made auditable before a person acts on it. This is where Responsible AI stops being a policy statement and becomes a running layer over production.

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The critic layer (coming soon)

Exterview is building a critic-agent evaluation to run over the outputs its agents produce — a separate evaluation pass that checks each report before it reaches a reviewer. Once live, an output that fails these checks would be flagged for human review rather than passed through silently.

Grounding

Claims in a report must trace to evidence from the session, not to unsupported assertion.

Rubric adherence

The score has to reflect your configured rubric, not drift away from the criteria you signed off.

Consistency

Comparable evidence produces comparable scores across candidates and sessions.

Safety and quality

Outputs are checked for quality and safety issues before they surface to a person.
This is still being built and is not running yet. We’ll update this page when it becomes available.

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Observability over every step

Every agent run is instrumented today. Exterview records the inputs, the steps, and the output of each evaluation, so you can see not just what was produced but how the system behaved.

Traced end to end

Each evaluation carries a trace of what the agent saw and produced.

Operational monitoring

Run success, latency, and cost are tracked against real production traffic today.

Quality signals (coming soon)

We’re building automatic quality scoring for every run, so weak outputs become visible rather than hidden.

Drift and regression watch (coming soon)

We’re building ongoing monitoring of AI performance over time, so a regression can be caught rather than discovered later.

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Auditability

Because every AI step and every evaluation is logged, the chain is reviewable after the fact: what the agent saw, what it produced, what was flagged, and which person approved the outcome. That trail is the evidence a compliance reviewer needs. See Auditability.

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Responsible AI, operationally

Responsible AI is enforced here, in Monitor, not only asserted. Content-based scoring, explainable outputs, mandatory human review, and no autonomous adverse decisions are checked and recorded at this layer. See Responsible AI for the principles; this page is where they run.

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FAQs

Yes. This layer improves the quality and traceability of AI outputs; it never replaces the human who owns the outcome. No adverse decision is made autonomously.
It is routed to human review rather than used silently. A person sees the flag, the evidence, and the trace before acting.
Yes. The trace and the critic’s checks are recorded and reviewable, and feed the audit trail. See Auditability.

Calibration

How scoring stays reproducible as evaluations run.

Outcome Intelligence

Post-hire signals that feed evaluation quality.

Responsible AI

The principles this layer enforces.

Auditability

The traceable record across actions and results.