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Purpose

Plenty of tools add AI to hiring. What sets Exterview apart is how the intelligence is built, controlled, and compounded, described here by capability, not by comparison to any one vendor.

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The pillars

Per-customer compounding calibration

Your evaluations are tuned to your bar and improve every cycle. The advantage accrues to you, it isn’t averaged into a shared model.

Reproducible scoring

The same inputs produce the same result, versioned and traceable. Nothing drifts silently underneath you.

The post-hire loop (Upcoming)

D30/60/90 outcomes are designed to feed back into rubrics and role definitions, quality of hire, not just speed of hire.

Specialized agents

Each hiring stage runs on a purpose-built agent, not one monolithic model handling everything.

Content-based, human-reviewed

Scoring is grounded in what a candidate says, and a human always owns the decision.

Above the ATS

An intelligence layer that upgrades your existing stack instead of forcing a rip-and-replace.

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Generic hiring AI vs. Exterview

Framed by capability, not vendor. The point isn’t who else is in the market, it’s what “good” should mean.

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FAQs

The label is common; the approach isn’t. Per-customer compounding calibration, and an Upcoming post-hire loop, are structurally different from serving one shared model.
Calibration that compounds inside your organization. The longer you run, the sharper, and more uniquely yours, it becomes.
Smaya is available today. You can ask it about your hiring data from the Smaya page, from a candidate report or from a connected assistant, and its AI Employees do the work with your approval on consequential steps. Upcoming: asking from Slack, and the full agent swarm that runs a role end to end. See Smaya and Agent swarm.