Services
Responsible AI Governance
Shipping and operating generative AI responsibly takes more than a security review at the end. It takes an expert with extensive experience in releasing safe and secure AI systems, who is directly embedded in the release process and has a clear-eyed view of whether the broader governance program holds up under real threats and real frameworks.
Casaba does both. We embed as the security release gate for generative AI products, and we assess whether an organization's AI governance program holds up under real conditions. We help teams ship and operate AI responsibly, from early design through deployment.
How we engage
Two ways we work with you
Embedded release gate and advisory
An ongoing function. We own the security release gate for your generative AI products and advise engineering teams from early design forward. We identify and help measure risks as teams build, make informed go/no-go decisions, and prepare teams to pass the gate. The goal is to help teams ship safely, not to block releases.
AI governance program assessment
A point-in-time assessment of the maturity of your AI security program across the whole organization, not just one product. We test whether controls hold under adversarial conditions and close the gap between what the documentation says and what the security posture actually is.
What we evaluate
The areas we assess across the AI lifecycle
Responsible AI compliance
Whether responsible AI commitments hold up in practice: content safety classifiers, harm category coverage, jailbreak resistance, and whether RAI policy is translated into real technical controls rather than living only on paper.
Development pipeline gates
Whether security and RAI review checkpoints are built into the AI development lifecycle and actually enforced, rather than skipped under deadline pressure for urgent releases.
Prompt-injection resistance
How well the product defends against direct and indirect prompt injection across every input surface: user prompts, retrieved documents, tool outputs, and any external content that reaches the model's context.
Data security and privacy
How sensitive data is handled across data flows, retrieval pipeline integrity, credential handling, PII exposure, memory management, and cross-tenant isolation in multi-user environments.
Tool and agent governance
For products that use tools, plugins, MCP servers, or autonomous agents: trust boundaries, sandbox policies, tool access controls, confirmation requirements, and whether these hold under adversarial conditions.
Defense-in-depth
Whether the product relies on a single safety mechanism or layers its defenses: instruction hierarchies, output classifiers, input sanitization, domain-specific safety constraints, and fallback behaviors.
Operational readiness
Whether the product has appropriate monitoring, logging, and incident response capabilities for AI-specific failure modes.
Compliance alignment
Practical alignment with NIST AI RMF, ISO/IEC 42001, the EU AI Act, and industry-specific regulations. Not just whether policies exist, but whether implementation would withstand audit scrutiny.
How we approach it
We test whether controls work, not just whether they're documented
Our engagements combine document review, stakeholder interviews, and hands-on technical evaluation. We don't just read policies - we test whether they work. We build custom test harnesses to probe agent governance controls at scale, and we work closely with product, security, and compliance stakeholders throughout.
When we find issues, we give specific, actionable guidance tied to your product and timeline, not generic framework checklists. Our team pairs deep expertise in AI measurement and mitigation with a traditional cybersecurity background in attack surface analysis and risk assessment, so we understand both the AI-specific risks and the broader security context.
What organizations get
A security partner who understands generative AI from the inside
A dedicated gatekeeper with AI security depth
Your engineering teams get a security partner who understands generative AI from the inside, not a generic auditor reading from a checklist.
Faster, safer releases
By advising teams early and providing clear requirements, we reduce friction at the release gate. Teams that engage with us during development rarely get surprised at the gate.
Consistent standards across products
When an organization has multiple AI products or features shipping on different timelines, we provide consistent evaluation standards and institutional knowledge across all of them.
Risk visibility for leadership
Our assessments give product leadership and security leadership clear visibility into the risk posture of each AI product before it ships.
Why it matters
The stakes are too high for ad hoc processes
Generative AI ships at an unprecedented pace, and the consequences of shipping something unsafe are significant - from harmful content to data breaches to regulatory exposure. The gap between policy documentation and actual security posture is where risk lives.
Casaba has served as the security release gate for some of the most significant generative AI products in the world, partnering with leaders like Microsoft, and we bring that depth of practice to every organization we work with.
Need a release gate or a governance assessment for your AI?
We have done this for the world's biggest AI products. Let's talk about yours. See our Microsoft Copilot case study, or explore AI/LLM security testing.
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