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  • Download: Recovery Exercise Planning Pack

    This download bundle helps Resilience Engineer teams design recovery around business services, dependencies, and tested objectives using Exercise plan and evidence log in AWS environments. It emphasizes protect backup identity and immutability boundaries and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Download: Agentic AI Control Review Pack

    This download bundle helps AI Governance Lead teams bound tool access, autonomy, memory, and approval points using Tool authorization and approval review in Microsoft Azure environments. It emphasizes record actions and make consequential steps interruptible and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • AI Governance Control Maturity Assessment

    This assessment helps AI Governance Lead teams assign ownership across use-case intake, data, models, applications, and operations using Intake, accountability, evidence, monitoring in Multi-Cloud environments. It emphasizes capture evidence proportionate to impact and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Enterprise RAG Production Readiness Assessment

    This assessment helps AI Leader teams treat retrieval quality, permissions, provenance, and answer evaluation as one design using Retrieval, permissions, evaluation, operations in Private Cloud environments. It emphasizes preserve source-level access controls through indexing and retrieval and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Video Tutorial: Rehearse an Isolated Recovery Environment

    This video tutorial helps Resilience Engineer teams design recovery around business services, dependencies, and tested objectives using Recovery orchestration and validation in AWS environments. It emphasizes protect backup identity and immutability boundaries and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Video Tutorial: Add Human Approval to an Agentic Workflow

    This video tutorial helps AI Engineer teams bound tool access, autonomy, memory, and approval points using Tool gateway and approval queue in Microsoft Azure environments. It emphasizes record actions and make consequential steps interruptible and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • RAG Production Review Workbook

    This tool helps AI Architect teams treat retrieval quality, permissions, provenance, and answer evaluation as one design using Retrieval, evaluation, security, and operations checks in Private Cloud environments. It emphasizes preserve source-level access controls through indexing and retrieval and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Illustrative Case Study: Exercising Recovery for a Telecommunications Control Service

    This illustrative case study helps Resilience Architect teams design recovery around business services, dependencies, and tested objectives using Isolated recovery environment and runbooks in Hybrid Cloud environments. It emphasizes protect backup identity and immutability boundaries and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Illustrative Case Study: Governing RAG for a Public-Sector Knowledge Service

    This illustrative case study helps AI Governance Lead teams treat retrieval quality, permissions, provenance, and answer evaluation as one design using Permission-aware retrieval and evaluation in Private Cloud environments. It emphasizes preserve source-level access controls through indexing and retrieval and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Enterprise Governance for Retrieval-Augmented Generation

    This whitepaper helps AI Leader teams assign ownership across use-case intake, data, models, applications, and operations using RAG evaluation, provenance, and access control in Private Cloud environments. It emphasizes capture evidence proportionate to impact and provides implementation decisions that can be reviewed without relying on vendor or customer claims.