Analysis on enterprise AI governance, inline policy enforcement, agentic AI security, and regulatory compliance.
Envoy AI Gateway is now Agent Router, an open-source project for routing model and MCP traffic. This buyer guide separates routing alternatives from identity-aware control layers that authorize HTTP AI requests and preserve decision evidence.
Read post →FERPA applies to AI tools the moment they touch a student education record, and the "school official" exception only covers your AI vendor when four specific conditions are met. Most edtech AI integrations were built before anyone checked those conditions against the AI step specifically. This piece walks through what FERPA actually requires when AI processes education records, exactly where the school official exception breaks for AI vendors, and the architecture that closes the gap.
Read post →AI audit trail requirements for the EU AI Act, HIPAA, DORA, NIST, and mortgage decisions. See the decision-record fields, retention questions, and evidence boundary each regime brings to an AI audit and regulatory review.
Read post →OpenAI Agent Builder security starts with prompt injection, structured outputs, and approval for MCP operations. This guide maps those workflow controls to the model-request authorization record enterprises need for each routed HTTP call.
Microsoft Purview and Nightfall both address sensitive-data exposure, but their strongest operating contexts differ. Purview ties data posture and DLP to Microsoft 365, Azure, Fabric, Edge, endpoints, and supported integrations, with audit and investigation. Nightfall emphasizes cloud DLP for SaaS and endpoints, including browsers and GenAI use. This guide compares prerequisites and sensors, policy paths and evidence, migration tests, and the separate role of identity-aware HTTP enforcement.
Read post →PromptArmor now centers continuous risk intelligence for third-party AI vendors, assets, connectors, and MCP tools. That makes its replacement decision different from a prompt-filter comparison. This guide compares Credo AI, Microsoft Purview DSPM, a TPRM workflow with direct vendor evidence, and DeepInspect by inventory source, risk object, monitoring signal, approval artifact, and runtime enforcement boundary.
Read post →Pillar Security spans AI asset discovery, posture analysis, agentic red teaming, runtime guardrails, endpoint governance, and compliance evidence. Replacing it requires a module-exit plan rather than a generic AI security shortlist. This guide compares Mindgard, Cisco AI Defense, Microsoft Defender for Cloud AI, and DeepInspect by control surface, integration dependency, evidence output, and production acceptance test.
Mindgard spans reconnaissance and automated red teaming, plus assessment and remediation. It also covers runtime threat response and continuous assurance. A credible replacement plan separates those modules before comparing Pillar Security, Cisco AI Defense, Palo Alto Networks Prisma AIRS, and DeepInspect. This guide turns the shortlist into a lifecycle acceptance matrix, with strict boundaries around discovery and testing, plus runtime screening and identity-aware HTTP policy. Audit evidence remains a separate requirement.
Orca AI-SPM uses agentless cloud scanning to inventory AI models and packages, assess configuration, detect sensitive data and exposed keys, and connect risks through cloud context. Wiz is the closest graph-based CNAPP alternative. Microsoft Defender for Cloud fits Microsoft-centered multicloud posture and Azure AI threat alerts. Noma extends discovery toward endpoint, SaaS, agent, MCP, skill, and tool surfaces. DeepInspect covers the separate job of identity-bound authorization and independent evidence for authenticated HTTP model requests.
Microsoft Purview applies data classification, DLP, audit, communication compliance, eDiscovery, retention, and compliance controls across supported Copilot and generative AI surfaces. Nightfall fits browser, endpoint, agent, and MCP data-exfiltration controls. Google Sensitive Data Protection fits discovery, classification, de-identification, and inspection APIs. Amazon Macie fits sensitive-data posture for Amazon S3. DeepInspect fits identity-bound policy on authenticated HTTP LLM requests. The right replacement follows the control point rather than the suite name.
Read post →Microsoft Defender for Cloud combines multicloud AI asset discovery, an AI bill of materials, configuration recommendations, attack-path analysis, and Azure-focused AI threat alerts. Wiz is the closest cloud-security alternative for graph-based posture and runtime findings. Orca emphasizes agentless cloud inventory and sensitive training-data exposure. Noma reaches agents, MCP servers, tools, and runtime behavior. DeepInspect governs authenticated HTTP model requests with identity-bound policy and independent decision evidence.
Prisma AIRS and Zscaler AI Guard overlap at live AI application inspection, but their current product families span different surfaces. A fair comparison matches Prisma AIRS AI Runtime Security against Zscaler AI Guard for Apps on the same prompt and response route, then evaluates AI Guard for Users separately. Buyers should test deployment, identity, actions, evidence, bypass, latency, failure behavior, export and retention.
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