A platform that
learns and improves.
Every governance evaluation is a data point. Nomotic's intelligence layer analyzes patterns across your entire agent fleet — measuring policy effectiveness, identifying escalation ROI, and generating adaptive threshold recommendations. Governance gets smarter over time.
Every evaluation
teaches the platform.
Static governance doesn't improve. Nomotic's intelligence layer closes the loop — analyzing what governance decisions worked, which escalations were justified, where thresholds need calibration. The platform learns from your agent fleet's behavior so your governance policies don't stay frozen at deployment-day assumptions.
- ✓ Policy effectiveness metrics with lookback windows
- ✓ Escalation ROI — did human review change the outcome?
- ✓ Adaptive threshold recommendations backed by behavioral data
- ✓ Counterfactual replay for audit and policy analysis
- ✓ Governance scorecard for compliance reporting
- ✓ Sequential optimization that reduces intervention cost over time
Complete intelligence infrastructure.
Policy Effectiveness Analytics
Did your governance configuration actually reduce risk and friction? Effectiveness reports measure drift reduction, escalation ROI, and false positive rates across configurable lookback windows.
All TiersAdaptive Threshold Recommendations
The intelligence layer analyzes 60-day behavioral trajectories and recommends threshold adjustments — per agent, per dimension. Evidence-based configuration rather than guesswork.
All TiersCounterfactual Replay
Replay any agent's historical evaluations against alternative governance configurations. Answer 'what would have happened if' for every audit question, every policy change proposal.
EnterpriseEscalation ROI
Measure whether human escalations are generating value. Did the reviewer change the verdict? How often? How quickly? Reviewer time ROI tells you if your escalation policy is calibrated correctly.
All TiersGovernance Scorecard
SOC2 and HIPAA compliance mapping. Gap analysis against framework requirements. Archetype benchmarking. The document your auditors and compliance teams actually need.
Team+Decision-Theoretic Optimization
Cost-sensitive governance with dynamic threshold derivation from asymmetric error cost profiles. Value of information computation for escalation decisions. Sequential policy optimization.
EnterpriseSimple to integrate.
Powerful at scale.
from nomotic.intelligence import PolicyAnalytics
analytics = PolicyAnalytics(runtime)
# Governance effectiveness metrics
report = analytics.effectiveness_report(lookback_days=30)
print(report.escalation_roi) # 8.2
print(report.drift_reduction_pct) # 0.39
print(report.false_positive_rate) # 0.06
# Policy recommendations based on behavioral data
recs = analytics.threshold_recommendations()
for rec in recs:
print(f"{rec.agent_id}: {rec.dimension} {rec.current} → {rec.suggested}")
# finance-analyst: allow_threshold 0.65 → 0.70
# claims-processor: deny_threshold 0.30 → 0.28
Intelligence features
across tiers.
| Feature | Community | Team | Enterprise |
|---|---|---|---|
| Evaluation metrics and audit analytics | ✓ | ✓ | ✓ |
| Trust trajectory visualization | ✓ | ✓ | ✓ |
| Behavioral scorecard (SOC2/HIPAA compliance mapping) | — | ✓ | ✓ |
| Escalation ROI reporting | — | ✓ | ✓ |
| Policy effectiveness analytics | — | ✓ | ✓ |
| Counterfactual replay (what-if analysis) | — | — | ✓ |
| Adaptive threshold recommendations | — | — | ✓ |
| Sequential governance optimization | — | — | ✓ |
| Fleet-level policy coordination analytics | — | — | ✓ |
| Decision-theoretic cost model calibration | — | — | ✓ |
Governance that
gets smarter over time.
Basic analytics are available in all tiers. Adaptive recommendations, counterfactual replay, and decision-theoretic optimization unlock in Enterprise.