Research
Our research teams build the measurement science for the AI economy - quantifying data quality, agent trust, alignment, resilience, fairness, and systemic risk.
Cross-Index Intelligence: How Patterns Across Frameworks Reveal What Single Scores Cannot
We present a systematic analysis of emergent intelligence patterns that arise when scores from multiple Amplitude frameworks are examined jointly. High Fidelity paired with low Drift reveals compliant but misaligned agents. Elevated Cascade risk alongside depressed Harmony signals fragile concentrated markets. These cross-framework patterns surface systemic insights invisible to any individual measurement instrument.
Data Science
Developing real-time data quality scoring methodologies that evaluate external data sources consumed by AI agents during inference-time operations.
Meridian
Agent Trust
Building the behavioral trust layer for autonomous agents - identity verification, behavioral consistency, and adversarial resilience testing.
Provenance, Fidelity, Threshold
Alignment & Control
Measuring the gap between human intent and agent behavior across delegation chains, and quantifying whether human oversight is real or ceremonial.
Drift, Mandate, Parity
Systemic Risk
Modeling failure propagation, market competition dynamics, and economic efficiency across interconnected agent ecosystems at scale.
Cascade, Convergence, Torque