Measurement for AI Frontiers

The measurement science
for AI impact.

Four frameworks. Three layers. One standard. VaryOn Amplitude quantifies what no one else measures - from data quality to agent trust to systemic risk.

Frameworks for the AI Economy

Data Layer

VaryOn Meridian

Data Quality

Is this data worth consuming, and what should an agent pay for it?

Meridian evaluates external data sources consumed by AI agents across four orthogonal dimensions, producing a composite score mapped to procurement tiers and dynamic pricing. Delivered in real time via MCP server integration during agent tool-call execution.

Dimensions

ScarcityQualityDecision ImpactDefensibility

Aggregation

Weighted Geometric Mean - Non-compensatory

Scale

0-100 -> Platinum / Gold / Silver / Bronze / Unrated

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Agent Layer

VaryOn Drift

Alignment Impact

Is this agent still serving its principal’s intent?

Drift detects the invisible gap between what a human principal wants and what an agent actually does - especially across delegation chains where alignment degrades per hop. Its shadow principal detection acts as a multiplicative gate, identifying when third-party interests silently influence agent behavior and directly capping the maximum possible score.

Dimensions

Goal FidelityDelegation DegradationOverride AnalysisShadow Principal DetectionPreference Drift

Aggregation

Gated Geometric Mean - Shadow principal as multiplicative gate

Scale

0–100 → Aligned / Drifting / Misaligned

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Ecosystem Layer

VaryOn Cascade

Systemic Impact

If something breaks, how far does the damage spread?

Cascade is the financial stress test for the agent economy. A single compromised agent can poison 87% of downstream decisions within 4 hours. Cascade runs Monte Carlo simulations on observed network topology to estimate propagation probability - the systemic risk measurement central banks are demanding.

Dimensions

Interconnection DensityCascade ProbabilityBehavioral CorrelationRecovery TimeConcentration Risk

Aggregation

Weighted Geometric Mean with Monte Carlo simulation

Scale

0–100 → Critical Risk / Elevated / Contained

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Ecosystem Layer

VaryOn Convergence

Collusion Impact

Are autonomous agents colluding to manipulate market prices?

Convergence detects emergent algorithmic collusion and anti-competitive behavior in AI agent markets through statistical analysis of observable market outcomes. The framework identifies when autonomous AI agents converge on supra-competitive pricing equilibria - sustaining prices 200% or more above competitive levels - without any explicit communication or coordination protocol.

Dimensions

Price ConvergenceMarket DivisionCommunication AnalysisBid Pattern AnalysisConsumer Welfare

Aggregation

Minimum-of-Components - Non-compensatory

Scale

0–100 → Collusive / Competitive / Healthy

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When frameworks combine, invisible patterns emerge.

Amplitude's power multiplies at the intersections.

Convergence + Cascade

Systemic Competition Risk

Market concentration in a dense network means anti-competitive behavior goes systemic.

Cascade

Uncontrollable Failure

When humans can't intervene and failures propagate, the system is ungovernable.

Drift

Silent Misalignment

An agent drifting from intent while human oversight is ceremonial creates invisible risk.

Convergence

Coordinated Discrimination

Fairness failures in a concentrated market amplify bias across the entire ecosystem.

Cascade

Efficiency Crisis

Transaction friction compounds through interconnected networks, destroying value at systemic scale.

Meridian

Data ROI

High-quality data inputs directly correlated with genuine economic efficiency.

Solutions for critical AI governance gaps.

Each product addresses a specific AI risk that existing tools miss. Deploy individually or combine for comprehensive governance.

Drift

Shadow Principal Detection

Detect when AI agents secretly optimize for third-party interests. Uncover commission bias and hidden conflicts.

✓ Spearman correlation
✓ 10+ shadow patterns
✓ Real-time monitoring
✓ SEC/FTC compliance

Meridian

Data Quality Gate for AI

Save 20-40% on AI costs by preventing bad data from reaching expensive models. Smart filtering that downgrades to cheaper models when data quality doesn't justify premium processing.

✓ Multi-dimensional scoring
✓ Automatic model routing
✓ Cost optimization
✓ MCP server for Claude

Convergence

Collusion Detection

Identify when AI agents collude to fix prices or divide markets. Detect anti-competitive patterns before they trigger antitrust violations with million-dollar penalties.

✓ Lerner Index calculation
✓ Price correlation analysis
✓ Market division detection
✓ DOJ/FTC reporting

Cascade

System Risk Simulation

Chaos engineering for AI systems. Run Monte Carlo simulations to predict how individual agent failures cascade through your network. Essential for insurance and board-level risk reporting.

✓ 1000+ failure scenarios
✓ Network topology analysis
✓ Recovery time estimation
✓ Insurance risk models

Three operational tiers. Transaction-grade scores serve inline at <100ms for real-time decisions. Monitoring-grade analysis runs continuously for compliance dashboards. Assessment-grade evaluations run deep simulations over hours for certification and regulatory audit.

Platform Capabilities

Enterprise-ready infrastructure for AI governance at scale

REST API

All Frameworks · Tiered Access

Programmatic access to every Amplitude framework score. From developer prototyping to enterprise-scale scoring with webhooks, custom thresholds, and white-label integration for agent marketplaces.

100K+ req/sWebhooksSDKs

Developer to Enterprise tiers

Policy Engine

Regulatory Compliance · Automated

Automated compliance mapping to EU AI Act, NIST AI Agent Standards, and sector-specific regulations. Continuous audit trails, regulatory reporting, and certification-ready documentation.

EU AI ActNISTSOC 2

Compliance automation

Every question a regulator, judge, or enterprise buyer would ask about AI agents - answered.

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