Frontier AI.
Built for hiring judgment.
Cernor follows a candidate’s experience from the first claim to the final recommendation. It checks the evidence, investigates important gaps and shows your team what holds up.
Deep decision intelligence. Ready to use today.
Scale the depth.
Keep the judgment.
Give every applicant the attention a shortlist demands. See what supports each recommendation and why it changed.
Set the bar.
Make it count.
A vague requirement can change who gets through. Cernor identifies the decisions hidden in your brief, so your team settles them before evaluating candidates.
Cernor shows the choices. Your team sets the bar.
What this shows: several credible readings of the same role are reduced to the few choices that actually change who gets through. Your team resolves those choices once, and every candidate is then read against that one approved bar.
See the reason.
Challenge the decision.
See which requirements a candidate meets, what supports that view and what still needs checking. Ask why the recommendation changed without starting the review again.
The history survives the handoff.
What this shows: a model output on its own is a moment, and it cannot survive a handoff. Seated inside the Standard your team approved and the Project that carries evidence, policy, history and authority, the same judgment holds.
Every applicant.
The full depth of the system.
Cernor evaluates the whole record, challenges weak evidence and investigates material gaps. New information updates the assessments it affects, with the cause of each change preserved.
Know what changed, what caused it and what still needs an answer.
What this shows: what looks like a single Project on the surface is many coordinated reasoning and software steps underneath. They include understanding the role, reading every candidate, challenging weak evidence, isolating what stays open, and refreshing only the decisions that change actually touched.
New evidence earns a new assessment. The history stays intact.
A decision is allowed to change.
Your team can trace it back to the agreed criteria, the source evidence and the previous assessment.
Stronger models.
No silent rewrites.
Compare a new model’s assessment with the one your team accepted. Inspect the differences before adopting a new reading.
Your earlier decisions stay available to check.
What this shows: a model change is held against the decisions already accepted rather than applied quietly. Model identity and decision history stay attached to each decision, so where a new model would read the same evidence differently, your team can see the difference instead of inheriting it.
AI
judgment.
Frontier AI evaluates the career behind every application.
Decision
memory.
See the evidence behind today’s recommendation and why it changed.
Human
authority.
Your team sets the requirements and decides who advances.
Give your next hiring decision the depth it deserves.
Bring a role you are hiring for. Every applicant gets the same serious read against it, with the evidence and the reasons attached.