Workforce AI that earns the trust it asks for.
RUDY's responsible AI controls are built into the product — not documented in a policy. Human review, confidence routing, explainability, fairness monitoring, and alignment with NIST AI RMF.
How RUDY governs every AI output
Human-in-the-loop review
Sensitive workforce recommendations require human review before action. RUDY routes high-risk AI outputs to manager review or OrgAdmin review — never automated for decisions that affect careers, wellbeing, or opportunity.
Confidence-based routing
Every AI output carries a confidence level. High-confidence suggestions can surface to managers. Medium-confidence outputs include review recommendations. Low-confidence outputs are held until sufficient data exists. Insufficient data results in no output.
Explainability by design
RUDY cannot generate a recommendation without generating its rationale. The explanation is not an optional drawer — it is produced alongside the recommendation and surfaced whenever the recommendation is shown.
Bias and fairness monitoring
RUDY monitors for demographic parity in AI outputs — recognizing that workforce AI that shows systematic differences by group is not responsible AI. Outputs with bias indicators are flagged for human review.
Source transparency
Every RUDY recommendation identifies what data was used and what was not used. This is shown to the manager reviewing the recommendation — not hidden in documentation.
Alignment with NIST AI RMF
RUDY's AI governance layer maps directly to NIST's AI Risk Management Framework: validity and reliability, safety, accountability and transparency, explainability and interpretability, privacy enhancement, and fairness with harmful bias managed.
Responsible AI is a product requirement, not a policy document.
RUDY's governance controls are visible in every AI output — not buried in a terms of service.
No surveillance. No black-box scoring. Human review where it matters.