Holistic AI measures risk. Zytra measures risk, governs it, and produces the evidence your regulator will accept.
Holistic AI's strength is risk quantification — impact assessments, fairness audits, and compliance reporting across EU AI Act, NIST, and ISO 42001. That covers the enterprise compliance layer well. It does not cover the MRM workflows, BFSI-specific guardrails, or India regulatory frameworks that a regulated bank's AI governance program actually requires.
Holistic AI
Zytra
Risk scores vs residual risk
Holistic AI produces risk scores. Zytra produces residual risk scores — the exposure remaining after your specific controls are applied. The difference is what drives investment decisions and what satisfies a regulator.
Inherent risk (what Holistic AI measures)
How risky is this AI system by category and deployment pattern — before controls. Inherent risk scores tell you where to look, and Holistic AI does this well. They do not tell you whether your current controls are adequate or where your exposure actually sits.
Control effectiveness (what's missing)
A risk score without control effectiveness measurement is a risk catalogue, not risk management. What fraction of the risk surface is the control actually active on? When did it last produce test evidence? What is the effectiveness score? These questions require measurement, not documentation.
Residual risk (what Zytra produces)
Residual Risk = Inherent Risk × (1 − Control Effectiveness). This is the number that tells a board or regulator what your actual exposure is. A domain heat map of residual scores — by risk category, after controls — is what a model risk committee and an OCC/RBI examiner will accept as evidence of governance maturity.
Framework coverage
| Framework | Holistic AI | Zytra |
|---|---|---|
| EU AI Act | ✓ Risk assessment + impact | ✓ Clause-level + automated evidence |
| NIST AI RMF | ✓ Function-level | ✓ Sub-practice citations |
| ISO/IEC 42001 | ✓ | ✓ + DORA simultaneous mapping |
| SR 11-7 · Model Risk Management | — | ✓ MRM workflow engine |
| RBI 2024 AI Circular | — | ✓ Clause-level, exam-ready |
| SEBI Algorithmic AI Oversight | — | ✓ |
| DPDP Act 2023 | — | ✓ Inference-pipeline level |
| MAS TRM · Singapore | — | ✓ |
| OCC / FFIEC · US banking | — | ✓ |
| Agentic AI security (D-09/D-10/D-11) | — | ✓ Multi-agent, MCP, A2A |
Assessment based on Holistic AI's publicly available documentation as of Q3 2026.
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