Assessments
System-specific assessments for production AI, agents, RAG pipelines, and MCP servers. Each page defines the boundary, risks, scenarios, evidence, access, retest, and what the assessment does not prove.
Choose the trigger
Each page is a qualified entry point for a specific production trigger. Use the detailed matrix, scenarios, metrics, and evidence requirements to decide whether the scope fits.
Production AI Security
A system-boundary review for live AI SaaS products that need defensible controls, reproducible tests, and evidence a security reviewer can follow.
Best fit: You have a live AI feature, an enterprise security review, or a material risk decision that cannot be answered with a generic AI policy.
Read the pageAgentic AI Security
A threat-model-led assessment for agents that plan, call tools, retain state, delegate work, or act on behalf of users.
Best fit: Your agent can read, write, transact, browse, or coordinate across systems and needs bounded autonomy before a customer-facing launch or enterprise review.
Read the pageRAG Security
A stage-by-stage assessment for ingestion, indexing, retrieval authorization, context assembly, citation, and tenant isolation in production RAG systems.
Best fit: Your RAG system produces plausible answers, but you need to prove that retrieval is authorized, sources are trustworthy, and a customer cannot influence another customer’s context.
Read the pageMCP Security
A production-readiness assessment for remote MCP servers covering authentication, tool scope, tenant isolation, outbound access, auditability, and failure containment.
Best fit: You are moving an MCP server from internal experiment to customer-facing or multi-tenant production and need evidence that tools cannot exceed their declared scope.
Read the pageOperating pattern
The shared pattern is simple: name the production boundary, map the failure, change the critical path, and keep the evidence or evaluation suite with the team.
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Every page names the artifact, owner, access, and decision that should exist after the work.
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Every page names the artifact, owner, access, and decision that should exist after the work.
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Every page names the artifact, owner, access, and decision that should exist after the work.
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Every page names the artifact, owner, access, and decision that should exist after the work.
FAQ
The pages are written to answer the questions a buyer or engineer asks before a focused engagement: what is in scope, what evidence exists, how is it tested, and what remains outside the claim?
Start with the system boundary behind the urgent trigger: production AI for a broad review, agent security for tool-using autonomy, RAG security for retrieval and tenant issues, or MCP security for a remote privileged integration.
No. They are scoped engineering assessments with reproducible scenarios, evidence requirements, remediation priorities, and retest conditions. Auditors, customers, and legal teams remain the decision authorities for their respective reviews.
Yes. A production-adjacent environment with realistic identities, policies, tools, retrieval, and side effects is preferred. Synthetic tenants and records reduce exposure while preserving the security boundary being tested.
30 minutes. No deck. Leave with a clear next step.
