Analysis on enterprise AI governance, inline policy enforcement, agentic AI security, and regulatory compliance.
Cato Networks acquired Aim Security in September 2025 and is folding its AI security capabilities into the Cato SASE Cloud platform through early 2026. This comparison lays out where a SASE-delivered AI security module fits, where a dedicated identity-aware policy gateway with per-decision audit fits, and which buyer each one serves, with honest pick-if framing for both.
Read post →OpenRouter is a hosted unified API to 400+ models across 50+ providers, with routing, fallbacks, BYOK, and a real guardrails layer that does PII detection, prompt-injection screening, model allowlists, and per-key budgets. Its policy binds to an API key, and its logging is opt-in observability. This piece covers what OpenRouter does well, why its key-bound model differs from identity-bound enforcement, and who needs a self-hosted alternative.
MuleSoft AI Gateway reached GA for its LLM capabilities on March 30, 2026 and runs on the Omni Gateway, formerly Flex Gateway, now at version 1.13. It governs LLM, MCP, and A2A traffic through one control plane with real policies: LLM Token Based Rate Limit, LLM PII Detection, and delegated content safety. This piece covers what MuleSoft AI Gateway does well, where its audit and identity model stops, and how a MuleSoft shop composes the two.
Read post →Solo.io announced Gloo AI Gateway in July 2024. It no longer exists under that name. Solo.io donated Gloo Gateway to the CNCF as kgateway, launched agentgateway in April 2025, contributed agentgateway to the Linux Foundation in August 2025, and removed Gloo from its product line entirely. The Gloo AI Gateway page now redirects to agentgateway. This piece covers what the product actually is today, what it enforces, and where a regulated workload still needs a second layer.
Read post →Guardrails AI is an Apache 2.0 Python framework with 70 validators in its Hub, covering PII detection through Presidio, jailbreak detection, secrets scanning, and structured output validation. It runs in the application process, or as a Flask server with OpenAI-compatible endpoints. Both modes are opt-in: a code path that skips the guard is unguarded. This piece covers what Guardrails AI validates well, what it never evaluates, and how the two layers compose.
Read post →F5 AI Gateway, announced November 2024, is a containerized Kubernetes proxy with a pluggable processor model. Processors modify, reject, or annotate traffic, and F5 ships prompt injection detection, data security matchers, and language identification. Its core stores an auditable record of every request and exports it to S3. That record carries no signature and no natural-person binding. This piece separates F5 AI Gateway from F5 AI Guardrails, then walks through the composition pattern.
Read post →Envoy AI Gateway reached 1.0 on June 23, 2026 with 16 providers behind one OpenAI-compatible API, cross-provider translation, token-aware rate limiting, and an MCP gateway with CEL-based per-tool authorization. It is the strongest open-source routing layer for a Kubernetes platform team. Its identity model projects JWT claims and its telemetry is OpenTelemetry. This piece covers what Envoy AI Gateway does, what a regulated workload still needs, and how the two layers compose.
Read post →Apigee is Google Cloud API management used as an AI gateway. Model Armor policies filter prompt injection and jailbreaks, semantic caching runs through Vertex embeddings, and LLM token policies handle cost. What Apigee authenticates is the calling app, the developer, or the API product. DeepInspect authenticates the natural person behind the request, classifies prompt content against PII, PHI, and MNPI, and commits a signed per-decision audit record. This piece walks through what each does and how they compose.
Read post →AWS has no product named AI Gateway. What people mean is one of four things: Bedrock AgentCore Gateway, the API Gateway plus Bedrock reference pattern, the Multi-Provider Generative AI Gateway guidance that deploys LiteLLM into your account, or Bedrock Guardrails. Each does a real job. None binds a natural person to the model call or signs a per-decision audit record. This piece separates the four, then walks through what a regulated workload on AWS still has to add.
Read post →Vercel AI Gateway and DeepInspect both sit between an application and model APIs, and they solve different problems. Vercel AI Gateway gives developers one endpoint for many models with routing, failover, and spend tracking. DeepInspect enforces identity-bound policy and produces per-decision audit records for regulated environments. This compares what each does, where each fits, and how to pick.
Read post →Anthropic Claude Enterprise and OpenAI ChatGPT Enterprise both publish enterprise control surfaces: SSO integration, audit log APIs, admin consoles, data residency options. This piece compares the two on the controls that actually determine compliance posture, and identifies the enforcement gap that neither provider closes at the request layer.
Read post →Azure AI Content Safety is Microsoft''s native content-moderation service for AI workloads running on Azure OpenAI and Azure-hosted models. DeepInspect is a model-agnostic policy enforcement gateway that sits in front of any HTTP-based LLM, regardless of cloud. The two services answer different questions. Content Safety asks "is this content harmful for moderation purposes?" DeepInspect asks "does this specific identity, under this specific policy, get to send this specific request to this specific model right now?" This comparison covers what each service is, where each fits, the architectural differences, and how to think about combining them in a multi-cloud deployment.
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