Experience the full Evo AI-SPM solution.
AI models, packages/libraries, skills, and MCP servers are embedded across your code and the apps you’ve shipped, invisible to traditional scanners.
There are no CVEs for models and no standard way to assess license risk, data exposure, or unsafe agent behavior at scale.
Static approved lists and ticket-based reviews slow teams down, and developers bypass them to ship faster.
Evo AI-SPM discovers, scores, and governs AI across code and production — extending your existing Snyk SCA, SAST, and CI/CD workflows without friction.
Discovery continuously maps AI models, agents, frameworks, datasets, MCP servers, and Skills across your code and running applications — generating an AI-BOM and relationship maps that show which apps and models are attached to your data.
Risk Intelligence goes beyond high-level risk buckets; every score breaks down from category to specific attacker goals, so you know exactly which guardrails to build. Evo scores each discovered model across five security categories using Attack Success Rate: the percentage of real adversarial attacks that succeed, on an independent 0–1000 index per category. Because context changes risk, models are also tested inside realistic agent archetypes: coding agents, internal data agents, personal assistants, customer-facing chatbots, so you see how risk shifts with deployment.
Policy turns plain-English intent into enforceable, audit-ready guardrails and ships five expert-built policies active on day one that auto-raise issues (i.e when a model’s Risk Index crosses 300).
Govern AI with confidence. Gain a system of record for AI assets and enforce policy across code and production, without slowing innovation.
Eliminate shadow AI and prioritize real risk. Automatically discover AI assets in code and enforce guardrails directly in developer workflows.
Scale AI without security friction. Pre-approve models, agents, and tools before production — and maintain visibility as architecture evolves.