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10 articles in AI Security & Governance
A practical guide to ML governance and model risk management: the governed model lifecycle, roles, validation, production monitoring and governing generative AI models.
Mansukh MarakanaHow to run HIPAA-regulated PHI workloads on Databricks: shared responsibility, the BAA and compliance security profile, a lakehouse architecture, Unity Catalog controls and…
Darshil HirparaA right-sized AI governance framework for startups and small businesses: essentials, risk tiers, an acceptable use policy, a 90-day plan and regulatory expectations.
Mansukh MarakanaIndicative costs for HIPAA-compliant AI agents by type, what the HIPAA premium pays for, healthcare-specific cost drivers, running costs and a worked estimate.
Hetal KHow to design HIPAA-compliant AI applications: a reference architecture, Security Rule safeguards for prompts, indexes and logs, de-identification and a BAA checklist for…
Mansukh MarakanaReview AI-generated code for secrets, dependencies, authorization, provenance and test quality. Includes a local static-analysis example and a practical pull-request policy template.
Paresh PurohitCompare LLM guardrail rules, classifiers and model reviewers. Includes a runnable output validator, action-policy boundaries and a practical testing checklist.
Hetal KDesign permission-aware RAG with trusted identity, document-level authorization, cache boundaries and revocation tests. Includes a runnable policy example.
Paresh PurohitThreat-model AI agents with prompt injection paths, a least-privilege tool matrix, approval boundaries and adversarial tests for unsafe tool calls.
Darshil HirparaAI introduces new security risks, from data leakage to prompt injection. These best practices help you adopt AI safely and responsibly.
Vimisha KLet’s plan your next step
Tell us about your goals, current systems and priorities. We’ll help you define a practical scope and the next step.
