AI Governance, Security & Compliance

AI adoption is now a regulated activity. Between India's DPDP Act, the EU AI Act's global reach and US frameworks like NIST AI RMF, "we'll figure out governance later" is a liability. We come from security engineering — we build it in from the start.

Assess Your AI Risk Posture
Capabilities

Trustworthy AI, Provable on Paper

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AI Governance Frameworks

Policies, model inventories, risk classification and approval workflows aligned to NIST AI RMF and ISO/IEC 42001 — sized for your organization, not a 200-page binder nobody reads.

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Data Residency & Sovereign AI

Architectures that keep personal data within your jurisdiction: private LLM platforms, consent-aware data pipelines and processing records aligned to laws like India's DPDP Act and the GDPR — for BFSI, health and government.

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Global Compliance Readiness

AI control postures for SOC 2 and HIPAA environments, EU AI Act readiness for products sold into Europe, and vendor AI-risk assessments your enterprise customers will demand.

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LLM Red Teaming

Structured adversarial testing of your AI systems: prompt injection, jailbreaks, data exfiltration paths and unsafe-output probing — with reproducible findings and fixes.

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AI Platform Security Hardening

Securing the stack around the model: identity and access for AI services, secrets handling, network segmentation for GPU clusters and supply-chain review of model artifacts.

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Incident Response for AI

Playbooks for model failures, data leaks via prompts and harmful outputs — who rolls back, who notifies, and what evidence you must preserve.

Why It Matters Now

Governance Is Becoming a Sales Requirement

Enterprise buyers worldwide now send AI-risk questionnaires before signing anything, and data-protection regimes from the EU AI Act and GDPR to India's DPDP Act make data-residency architecture a board-level topic. Companies with credible AI governance close deals faster and enter regulated markets competitors can't touch.

Because OPLEXUS also builds AI infrastructure and applications, our governance work is technical, not theatrical — controls are implemented in the platform, not just described in a document.

  • Security engineering heritage. Our team designed enterprise security architectures before AI made it fashionable.
  • Framework-mapped deliverables. Every control traces to NIST AI RMF / ISO 42001 / DPDP clauses.
  • Tested, not asserted. Red-team findings validate that controls actually hold.
  • Audit-ready artifacts. Model cards, DPIAs and processing records your auditors can use as-is.

Could Your AI Stack Pass an Audit Today?

Start with a fixed-scope AI risk assessment. Two weeks, a scored posture report, and a prioritized remediation plan.

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