TRACE-AI Platform Overview

Operationalizing Responsible AI with Trust, Risk, Action, Compliance & Evidence

What is TRACE?

TRACE (Trust · Risk · Action · Compliance · Evidence) is a transparent, open, and standards-aligned assurance framework that converts AI evaluation metrics into real-time, clause-linked, audit-ready compliance evidence.

Built to support frameworks like the EU AI Act, NIST AI RMF, and ISO 42001, TRACE helps organizations move from Responsible AI intentions to verifiable execution—without black-box dependencies.

Why TRACE?

Modern AI systems are embedded in high-stakes environments—finance, healthcare, public policy—yet most organizations face persistent assurance gaps:

  • No clause-aligned audit trail

  • No deterministic mapping between metrics and controls

  • No real-time accountability for regulators or buyers

TRACE bridges these gaps by:

  • Linking raw metrics to statutory clauses

  • Automating SLA-bound control workflows

  • Producing cryptographically sealed evidence packages

Key Capabilities

Metric to Risk Mapping

Submits raw metrics (via API) and classifies contextual risk (Low / Elevated / Unacceptable) using domain-specific thresholds.

Automated Controls

Each residual risk triggers a predefined governance control, with:

  • SLA binding

  • Ownership mapping

  • Escalation paths

Clause Mapping

Every control is linked to legal clauses (e.g., EU AI Act Art. 15) and logged in a real-time clause ledger.

Assurance Envelope

TRACE packages the full evidence chain—Metric → Risk → Control → Clause—into a cryptographically sealed report.

TRACE Scorecard

TRACE translates complex evaluations into a Responsible AI Index (RAI), offering:

  • Health Index (0–100) + Star Rating

  • Radar chart across 7 pillars:

    • Performance

    • Fairness & Bias

    • Safety & Truthfulness

    • Task Adherence

    • Reliability

    • Robustness

    • Privacy

This gives boardrooms and regulators a unified view of model assurance posture.

Compliance Alignment

TRACE natively aligns with:

  1. NIST AI RMF

  2. EU AI Act

  3. ISO 42001

  4. GDPR

End-to-End Assurance Loop

  1. POST Raw Metric
    Submit via /metrics API.

  2. Contextual Risk Classification
    Auto-classified based on industry-specific thresholds.

  3. Control Triggered
    Eg: “Enable enterprise grounding” with SLA + owner + rollback.

  4. Clause Coverage Logged
    Control is linked to law (e.g., EU AI Act Art. 15).

  5. Immutable Evidence Sealed
    Hash-linked, independently verifiable assurance envelope.

Time to compliance proof: <90 seconds.