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FitRank

Admins and leadership · Thresholds and model versions

Control the cut-offs and the model, with a safety gate

Admins decide how strict the shortlist is and which model is in use. Every model is tested against plain rules before it can be switched on, and every change is kept in history.

FitRank band cut-offs: shortlist from 80% and review from 50%, with a reason for each change and a versioned change history
Your cut-offs, versioned and audited

The problem

AI tools change behaviour without warning, and nobody inside the company can set how cautious they are or undo an update that made things worse.

How it works

  1. 1Set the shortlist and review cut-offs, with a reason. Each change is a new version and applies to the next run.
  2. 2Compare trained models on test tasks they never saw: best person in the top five, best person first and confidence error.
  3. 3Switch to a model or roll back in one click. A model that ranks worse than the current one is refused unless you override it on purpose.
  4. 4Past runs keep the model and cut-offs they used.
FitRank model versions table comparing trained models on held-out test tasks, with the active model, switch buttons and switch history
Switch or roll back a model in one click
FitRank test reports: each model tested on unseen tasks against a simple ranking, with right person in top five, right person first and confidence error
Every model tested against plain rules

What's included

Where teams use it

Questions about thresholds and model versions

Can a worse model be switched on by accident?

No. A model that ranks worse than the current one on held-out tests is refused unless an admin overrides it on purpose.

Do threshold changes rewrite old results?

No. A change applies to the next run; past runs keep the cut-offs they used.

More of FitRank

See all 19 capabilities

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