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SustainGRC AI Governance
Most enterprises have an AI policy.
What they don 't have is a system.
The gap isn't awareness. It's architecture. One system that discovers, classifies, and continuously governs every AI system in your organisation — against EU AI Act, ISO 42001, and NIST AI RMF. From one record.
Multi-framework
EU AI Act
ISO 42001
NIST AI RMF 1.0
Platform Capabilities
Responsible AI by Design
InsightLens follows our foundational principle for AI in governance and compliance.
80%
of large organisations claim AI governance initiatives
Fewer than half can demonstrate measurable maturity. Not because they lack intent — because they lack infrastructure.
60-80%
of enterprise AI use is unregistered
Shadow AI is the compliance blind spot quarterly audit cycles can't catch. The exposure is embedded before risk even knows to look.
€35M
maximum EU AI Act penalty
Or 7% of global annual turnover — whichever is higher. The window between "we have a policy" and "we have a finding" is closing fast.
How it works
Five phases. One registry. Full audit trail.
From shadow AI discovery to board reporting — every step produces auditable evidence, not documentation.
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Classify
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Assess
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Evidence
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Report
Find every AI system — including the ones nobody told you about
Shadow AI is where the liability sits. SustainGRC passively discovers AI API calls across your network, flags AI-enabled vendors at procurement, and provides self-service intake for business units. Every discovery enters the registry with mandatory owner assignment before it progresses
Network scan for known AI providers (OpenAI, Azure AI, Google Vertex, AWS Bedrock)
Procurement hook flags AI-enabled vendors automatically
Self-service intake for business-unit-led registration
Enterprise-Grade
Built for Regulated Environments
Security, transparency, and auditability are foundational—not afterthoughts.
Built into your GRC — not bolted on
High-risk AI systems automatically create linked entries in Enterprise Risk Management. AI-specific controls slot into your existing Controls Library. No parallel silo.
Transparent by design
Every classification and readiness score shows its formula, inputs, and regulatory basis. No black-box scoring. No maturity models. Binary: compliant or finding raised.
AI proposes, humans confirm
AI assists with classification and gap detection. It never computes final scores or makes governance decisions. Every suggestion requires explicit human confirmation.
ESG × AI convergence
AI governance data feeds directly into CSRD disclosures (ESRS G1, S1), materiality assessments, and climate model governance — because sustainability reports must now cover AI risk.
How it works
What we deliberately don't build
If a feature requires a data scientist to configure or a PhD to interpret, it doesn't belong in a governance tool.
ML model monitoring dashboards
We surface alerts from your existing tools. We don't rebuild Datadog.
Algorithmic fairness testing
Bias testing is domain-specific. We ingest results as evidence. We don't score fairness.
AI ethics maturity models
Subjective, non-auditable, easily gamed. We do rule-based gap analysis against published standards.
Explainability visualisations
LIME/SHAP dashboards don't answer the CISO's question. Art. 13 demands plain-language purpose statements.
Regulatory timeline
EU AI Act enforcement is already underway
Regulation isn't waiting. Prohibited AI practices and GPAI transparency rules are already in force. High-risk enforcement is next.
February 2025
Prohibited AI practices
Social scoring, manipulative AI, real-time biometric surveillance (with exceptions).
August 2025
GPAI transparency rules
General-purpose AI model providers must comply with transparency and copyright obligations.
2 August 2026
High-risk AI enforcement
Conformity assessments, risk management, technical documentation, human oversight, and post-market monitoring become mandatory.
August 2027
Full implementation
All remaining provisions including AI embedded in regulated products.
Frequently AskedQuestions
One platform. Data and decisions that hold up.
Discovery to board reporting in weeks, not quarters. No data science team required.
