Navigate the global AI regulatory landscape with confidence. NIST AI RMF, ISO 42001, EU AI Act, and DPDP Act 2023 compliance — built for regulated enterprises.
We implement and audit against every major AI governance standard globally.
End-to-end governance across the AI lifecycle — from model development to production monitoring.
Systematic identification, classification, and prioritization of AI risks — bias, hallucination, adversarial inputs, model drift, data poisoning.
Custom AI governance policies, acceptable use frameworks, model cards, datasheets for datasets, and AI ethics boards.
Red team testing of LLMs and ML models — prompt injection, jailbreaks, data extraction, supply chain (OWASP LLM Top 10).
SHAP/LIME interpretability reports, demographic bias audits, fairness metrics, and regulatory-grade model documentation.
Training data lineage, consent tracking, PII anonymization, data minimization controls, and cross-border transfer assessments.
Production AI monitoring — model drift detection, anomaly alerts, automated compliance reporting, and incident response playbooks.
Structured, time-bound delivery with measurable compliance outcomes.
Complete AI asset inventory — all models, training pipelines, data sources, and third-party AI APIs. Risk classification against EU AI Act tiers and NIST AI RMF profiles.
Current-state vs. target-state compliance gap analysis. Prioritized remediation roadmap with effort estimates, ownership, and regulatory deadlines mapped.
Deploy governance controls — policies, model cards, approval workflows, testing gates, DPA agreements, conformity documentation. ISO 42001 AIMS setup.
Pre-certification internal audit, evidence pack for external auditors, board-level AI governance report, and ongoing quarterly compliance reviews.
The regulatory window for informal AI deployment has closed. The EU AI Act entered into force in August 2024, with prohibited AI practices banned from February 2025 and high-risk system requirements applying from August 2026. India's DPDP Act 2023 imposes obligations on any AI system processing personal data. NIST AI RMF has been adopted as a procurement requirement by US federal agencies and many Fortune 500 supplier contracts.
Under the EU AI Act, AI systems are classified into four risk tiers. Prohibited systems (e.g., social scoring, real-time biometric surveillance in public spaces) are banned outright. High-risk systems — including AI in critical infrastructure, HR hiring, credit scoring, law enforcement, and healthcare — require conformity assessments, human oversight, transparency documentation, and registration in the EU database before deployment. Limited-risk systems (chatbots, deepfakes) face transparency obligations. Minimal-risk systems are unregulated but benefit from voluntary codes of conduct.
The NIST AI Risk Management Framework organizes AI governance across four core functions: GOVERN (organizational accountability, culture, policies), MAP (risk context identification, stakeholder analysis), MEASURE (risk analysis, testing, evaluation), and MANAGE (risk treatment, response, recovery). Our engagements implement all four functions with measurable maturity levels and audit evidence.
ISO 42001:2023 is the first international standard for AI management systems, following the Annex SL structure familiar from ISO 27001 and ISO 9001. Certification demonstrates to customers, regulators, and partners that your AI governance is systematic, repeatable, and independently verified. We provide gap assessments, implementation support, and readiness reviews for your chosen certification body.
India's Digital Personal Data Protection Act 2023 treats AI training and inference as data processing activities subject to consent, purpose limitation, and data fiduciary obligations. Organizations must appoint a Data Protection Officer, implement breach notification within 72 hours, and conduct Data Protection Impact Assessments for high-risk processing — including many AI applications. Cross-border data transfers are permitted only to approved countries listed by the government. Our DPDP compliance program maps every AI data flow to these obligations.
Modern AI systems depend on foundation models, third-party APIs, open-source libraries, and pre-trained weights from external providers. Each dependency introduces governance risk — model bias inherited from upstream training data, unauthorized PII in third-party LLM outputs, and licensing obligations from open-source model weights. We assess your AI supply chain and implement controls including SBOM (Software Bill of Materials) for AI, vendor risk questionnaires, and contractual data processing agreements.
Assess your AI system against NIST AI RMF, EU AI Act, or ISO 42001 — get a compliance score instantly
Book an AI Governance Discovery Session — 60 minutes, no obligation. Walk away with a prioritized compliance roadmap.