AI that your auditor will actually trust
Transparent. Overridable. Audit-logged. Enterprise AI the way governance demands it.
AI Governance: Building a Defensible Governance Framework — 22 Apr
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AI proposes. Humans confirm. System records both. The foundational principle embedded into every module, every workflow, every decision on SustainGRC.
Not a bolt-on copilot. Not a chatbot overlay. AI is woven into the platform's data model — computing scores, generating findings, detecting gaps, and forecasting risk. Always transparent. Always overridable. Always audit-logged.
Every AI-assisted workflow on the platform follows this pattern. No exceptions. No shortcuts.
Build a living map of your entire supply network. Auto-classify suppliers by tier, criticality, spend, and geography — then overlay ESG risk signals from across the platform.
Scans 5 modules to compute readiness % per regulation
Findings auto-generated: missing · partial · misaligned · outdated · configured
Risk-tiers AI systems using transparent rule-based scoring
35% use-case domain, 25% data sensitivity, 20% decision autonomy, 20% scale of impact
Scores every metric on two axes (Emissions DQ × Denominator DQ)
PCAF v2.0 aligned, weakest-link logic, per-holding decomposition
Forecasts 6–12 month risk trajectory across supplier portfolio
Key drivers identified and ranked by impact
Autonomous agents that run continuously across your data estate — each one specialised, all of them governed by the same three-phase loop.
Natural language queries across all platform data. Ask 'What are my GCC compliance gaps?' — get answers grounded in your metrics with source citations.
Statistical agents identify outliers, sudden shifts, and unit mismatches across your metric estate. Alerts before errors propagate to disclosures.
Agents scan data sources against active frameworks, flagging missing metrics, stale records, and coverage blind spots. Auto-assigns remediation tasks.
Trajectory scoring across enterprise risk, supply chain, and third-party portfolios. 6-to-12-month forecasts with confidence levels and key drivers.
AI maps your data against 8+ frameworks simultaneously — GCC, GRI, ISSB, TCFD, SASB, CSRD, UNGC, TNFD. Collect once, report many.
Regulatory Intelligence agents inspect 8 platform modules to compute readiness per regulation. Findings generated automatically, overrides logged.
Enterprise AI in governance demands more than accuracy - it demands defensibility. Every design decision prioritises auditability.
Every AI-computed score displays its formula, input values, and which regulation or methodology drove the result. Auditors can reconstruct any number independently.
No user creates and approves. Role-based permissions enforce four-eye principles across all state transitions. Time-bound evaluation periods with hard locks.
Every score and decision links to its evidence. Evidence carries verification status: PENDING - VERIFIED - REJECTED. No floating assertions.
All entities follow DRAFT - IN_REVIEW - APPROVED - LOCKED. LOCKED records cannot be modified. Override history preserved permanently.
Computed CSRD readiness: 68%
Generated 4 findings for ESG Reporting module
Anomaly detected: Scope 1 emissions 1340% QoQ
Override finding F-2026-041 - Not Applicable
Reason: Addressed via external audit
Supplier risk trajectory: 58 - 64 (6-mo forecast)
4 recommendations generated, routed to Risk team
Approved assessment ASS-2026-012- LOCKED
Reason: Reviewed with audit partner
Append-only - Immutable - 7-year retention
Trained on public internet data
No source attribution or citations
Hallucination risk on every query
No audit trail of AI interactions
Same answer for every customer
Can't override or challenge AI output
Queries YOUR governed data
Every claim cites specific records
Retrieval-only—no invented facts
Scoped by framework, period, domain
RBAC enforced responses
Transparent. Overridable. Audit-logged. Enterprise AI the way governance demands it.