CatalogueData & Artificial IntelligenceMLOps, AI Governance & Model Security
Data & Artificial Intelligence

MLOps, AI Governance & Model Security

Governance, lifecycle controls and operational tooling for responsibly deploying, monitoring and retiring AI models and AI-enabled applications.

Who this is for
  • CIO and risk leaders
  • AI product owners
  • Security teams
  • Data science leaders
Outcomes it serves
  • Clear AI ownership and risk decisions
  • Reproducible model releases
  • Continuous quality and drift monitoring
  • Documented controls for regulators and customers
Capabilities
  • AI inventory and risk-tiering
  • Model documentation and approval gates
  • Evaluation and red-team plans
  • Versioning, deployment and rollback
  • Monitoring for drift, abuse and cost
  • Incident, change and retirement procedures
What is delivered
  • Confirmed scope, stakeholders, assumptions and acceptance criteria
  • Assessment, design or implementation work products
  • Decision log, risk register and issue resolution
  • Testing or evidence pack appropriate to the service
  • Knowledge transfer, administrator guidance and handover
  • Follow-up support or managed-service transition where contracted
Options
  • AI governance program
  • Model registry and pipelines
  • Independent validation
  • Managed model monitoring
  • Policy and training package
What may change the price
  • Edition, modules and user/location count
  • Hosting, environments and availability target
  • Data migration and integrations
  • Configuration versus custom development
  • Security, compliance and assurance scope
  • Training, support and service level

Content on this page comes from the governed ARRIX catalogue record DAI-08; pricing is confirmed only through a reviewed quotation.

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