Enterprise AI security platform in four modules: AI Discovery, AI Supply Chain Security (model scanning), AI Attack Simulation and AI Runtime Security.
Security teams that want the model artefact and the running agent covered by one vendor and one console, since the platform is organised into four named modules: AI Discovery for shadow-AI inventory, AI Supply Chain Security for validating model integrity before deployment, AI Attack Simulation for continuous adversarial testing, and AI Runtime Security for inline detection and enforcement. It is aimed at buyers who already operate a security operations function, because the runtime module's stated job is to feed detections and enforcement events into existing SIEM and SOAR workflows. The agentic pages also extend to coding agents through Agent Harness Security, which integrates into each coding agent's native hook surface.
Almost nothing commercial is published: no pricing, no tier list, no free tier and no trial appear on the platform, module or solution pages, and every call to action is 'Book a demo' or 'Request a Demo'. No latency figure is published either, with the runtime pages saying only that threats are detected and responded to 'without impacting performance in production', and the single efficacy number on the site is '75%+ Reduction in exposure to AI exploits' with no methodology, sample size or date attached. Integration detail is thin for evaluation purposes, because the platform page lists connector categories (cloud, CI/CD, data platforms, SIEM/SOAR, API gateways, MLOps tools) but names no connector vendors, and the only named technical integration points are LiteLLM proxy interception, SDK instrumentation, gateway inspection and MCP-based systems.
Pros
Cons
AI Discovery builds an inventory of AI applications, models and assets to surface shadow AI. AI Supply Chain Security, previously called Model Scanner, validates model integrity and supply chain before deployment. AI Attack Simulation, previously Automated Red Teaming for AI, runs adversarial simulations continuously. AI Runtime Security, previously AI Detection & Response or AIDR, provides runtime visibility, threat detection and inline blocking or redaction according to policy and platform capabilities.
Nothing. No tiers, seat prices, per-model rates, free tier or trial appear on the platform, module or solution pages, and every call to action is a demo request. Buyers should expect a sales-led process and should ask for the figures the site omits: latency under load, detection and false-positive rates with methodology, named connectors, and whether a self-hosted deployment is available for their environment.
Only one efficacy figure appears, '75%+ Reduction in exposure to AI exploits', stated without methodology, sample size or date and not independently verified. No latency figure is published at all; the runtime pages say only that threats are detected and responded to without impacting performance in production. Other statistics on the site, such as 76% reporting shadow AI concerns, are survey framing rather than product measurements.
Few. The platform page lists connector categories only: cloud, CI/CD, data platforms, SIEM/SOAR, API gateways and MLOps tools. The agentic page names LiteLLM proxy interception, SDK instrumentation and gateway inspection as methods, and OpenAI, AWS Bedrock and MCP-based systems as supported agent ecosystems. AWS and Databricks are listed as featured technology partners. Agent Harness Security hooks into each coding agent's native hook surface.
Facts sourced from the vendor’s own site, last verified 2026-10-10.
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