143 posts on comparisons & alternatives.
Credal gives employees a sanctioned internal AI portal. The pattern works when employee AI usage is the entire scope. The pattern stops working when machine-to-machine, agent-driven, or vendor-embedded AI traffic must be covered by the same policy and the same audit trail. This piece walks through where the portal stops and what fills the gap.
IBM watsonx.governance is the model lifecycle governance product from IBM, covering model risk management, model documentation, agent evaluation, and production monitoring. IBM also ships a model gateway in watsonx.ai that routes inference across OpenAI, Anthropic, Bedrock and others. This article walks through what each of those covers, where the boundary ends, how the April 2026 SR 26-2 model risk guidance changes the banking picture, and what an independent enforcement layer at the AI request boundary adds.
Collibra AI Governance extends the Collibra Data Intelligence Platform with AI use case catalogs, model documentation, policy management, and stakeholder workflows. The product surface is the metadata layer over data and AI assets. Inline policy enforcement at the AI request boundary sits at a different architectural layer. This article walks through what Collibra covers, where the boundary ends, and how the two layers fit together.
The AI security category is fragmented across 14 distinct tool types: AI gateway / policy enforcement, AI DLP, AI SPM, model security, guardrails, agent identity, red teaming, model risk management, AI observability, vendor risk for AI, AI incident response, AI training data security, federated learning security, and AI supply chain. Each category solves a different layer of the AI stack. Buyers who treat the category as one bucket overspend on overlap and underspend on the actual enforcement layer. This list walks through what each category does, where it sits in the architecture, and what to ask vendors before buying.
Databricks closed its acquisition of Panther on August 3, 2026, seven weeks after announcing it, folding Panther into Lakewatch, its security-lakehouse product, to form an agentic SIEM. The deal extends Databricks security lakehouse with an agentic SOC. Detection of AI-driven attacks sits in one architectural place. Per-decision enforcement on AI traffic sits in another. The two are not interchangeable.
The NSA published an MCP security information sheet in June 2026 calling out limited audit logging and weak access controls. The Cloud Security Alliance documented a design-level RCE across every official MCP SDK. MCPTox measured tool-poisoning success rates up to 72% against real servers. This piece sorts the MCP security tooling that actually exists into scanners, gateways, and registries, names what each one covers, and marks which failure modes no HTTP control can reach.
LiteLLM and DeepInspect both sit in front of model APIs as a proxy, which makes them look like alternatives. They are built for different jobs. LiteLLM unifies providers and manages keys and spend for developers. DeepInspect enforces identity, policy, and per-decision audit for security and compliance. This piece compares the two by design center, where they overlap, and when running both makes sense.
On 28 July 2026 Cyera agreed to buy Oasis Security for roughly $1 billion, about $700 million of it cash, weeks after raising $600 million at a $12 billion valuation. It is the second-largest cybersecurity deal of the year and the sixth platform absorption of an AI-agent or identity startup in twelve months. This reads the deal as category validation for identity-bound authorization of AI-agent activity, and sets out the RFP question a platform lead should ask about where that control sits.
Zenity governs AI agents built on platforms like Salesforce Agentforce, Microsoft Copilot Studio, and ServiceNow, with build-time posture checks, observability, and runtime risk detection. DeepInspect enforces identity-bound policy and produces a per-decision audit record on the HTTP calls between users or agents and LLMs. This comparison draws the boundary between the two layers and gives honest pick-if guidance.
Cisco AI Defense pairs model validation with real-time guardrails that block adversarial attacks, prompt injection, and unsafe agent behavior, delivered across Cisco security fabric and AI-aware SASE. This comparison separates threat-and-content guardrails from identity-bound authorization and per-decision audit, shows where each layer sits, and gives honest pick-if guidance for both.
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.