What It Measures
Waltrump AI OrchestratorEvidence-based AI Health
AI Health Score for Your AI Applications
Understand how reliable, measurable, scalable, and trustworthy an AI application is using an internal readiness and improvement score.
Measure. Compare. Improve. Trust Your AI.
Best Fit
Product owners, CTOs, engineering teams, governance leaders, founders, and enterprises that need a clearer picture before scaling AI usage.
Capability Focus
A readiness view built from eight health dimensions
Quality
Measure whether outputs meet task and response-quality expectations.
Performance
Track latency and execution behavior across representative workflows.
Confidence
Separate stronger conclusions from early signals supported by limited evidence.
Evidence Coverage
Understand how much benchmark, provider, Gateway, and reliability evidence supports the score.
Cost Efficiency
Identify potential optimization while keeping quality and reliability visible.
Reliability
Review failures, consistency, provider availability, and fallback signals.
Risk Level
Surface measurable conditions that may require further review before rollout.
Improvement Potential
Prioritize benchmark-based recommendations for the next evaluation cycle.
How It Works
Turn available evidence into an improvement priority
01Collect evidence
02Measure health dimensions
03Calculate confidence
04Review risk
05Prioritize improvements
06Measure again
Readiness Value
- Explain AI readiness clearly
- Find evidence gaps
- Prioritize measurable improvements
- Support controlled scaling decisions
Not Certification
AI Health is an evidence-based internal readiness and improvement score. It is not public certification, compliance certification, or an external approval.
Invite-only Beta
Understand where your AI is ready—and where it needs evidence.
Request an AI Health assessment to review readiness, risk, confidence, and improvement potential.