Governance, Risk & Compliance

Designed for regulated AI environments_

Semantic XAI (Explainable AI) for meaning risk management

DeepaData is a Semantic XAI layer — it explains what emotional context AI interactions contain, through interpretation, not inference. It sits alongside existing model-risk tooling to add meaning-level accountability for regulated environments.

How It Works

Five steps to semantic governance_

Interpret. Seal. Govern. Share. Verify.

1

Interpret

EDM.jsonExtract what was significant

2

Seal

.ddnaSigned by DeepaData

3

Govern

MetadataCompliance in-band

4

Share

VitaPassMoves with the subject

5

Verify

APIConfirm authenticity

The XAI Distinction

Semantic XAI vs Traditional XAI_

Traditional XAI explains model mechanics. DeepaData explains model meaning. This is a different governance layer — adjacent but distinct.

Traditional XAI

  • Model explainability
  • "Why did the model output X?"
  • Feature importance, SHAP values
  • Model risk management

DeepaData (Semantic XAI)

  • Interpretation explainability
  • "What did the AI imply about a person?"
  • Semantic provenance, affective context
  • Meaning risk management

Strategic value

Semantic XAI addresses meaning-level risk: what was expressed, what was interpreted, and what policy applied.

Interpretation enables auditability

Structured artifacts make emotional context inspectable and cryptographically sealed. Without an artifact, context remains transient and difficult to audit.

Regulatory frameworks addressed_

Audit-friendly records designed to support evolving regulatory requirements across jurisdictions.

EU AI Act

Designed For

DeepaData structures expressed or interpreted content into governed artifacts, rather than deriving hidden states from behavioral signals. This distinction supports a more defensible processing model in regulatory review.

  • Article 5(1)(f) - Prohibited practices
  • Article 6 - High-risk classification
  • Article 13 - Transparency

GDPR

Supported

Artifacts are designed to carry consent, retention, and portability metadata to support subject-rights workflows (including erasure and export) where applicable.

  • Article 17 - Right to erasure
  • Article 20 - Data portability
  • Article 22 - Automated decisions

HIPAA

Policy Labels

Healthcare policy labels and audit trails for covered entities and business associates.

  • 45 CFR 164.312 - Technical safeguards
  • 45 CFR 164.530 - Administrative requirements

CCPA

Supported

California consumer rights supported through portable, deletable artifacts.

  • Section 1798.100 - Right to know
  • Section 1798.105 - Right to delete

Enterprise governance capabilities_

Complete accountability across every decision, action, and policy outcome.

Complete Audit Trails

Every artifact includes provenance, timestamp, model version, and consent basis. Artifact-level provenance to support audits, investigations, and post-incident review.

Risk Review Support

Support internal review with structured records and policy metadata for higher-sensitivity use cases.

Policy Enforcement

Governance metadata travels with every record. Jurisdiction, retention, and consent rules enforced at the data layer.

Cryptographic Integrity

W3C Data Integrity Proofs (eddsa-jcs-2022) ensure tamper-evident integrity. Verify authenticity independently.

What DeepaData uniquely provides_

Interpretation governance
Emotional/affective inference risk
Semantic artifacts with provenance
Explicit vs inferred separation
Evidence-grade meaning records
AI-human psychological boundary

Meaning-level governance for emotional context is under-served. Semantic XAI fills this gap.

Ready to govern meaning risk?

Start with API access, or talk to us about enterprise deployment.