AI Security
Ovalix Security Platform
Shadow AI discovery, GenAI data leakage prevention, and real-time AI usage policy enforcement.
Ovalix Security Platform Overview
What it does
The Ovalix Security Platform is an AI usage control and AI security platform that gives enterprises visibility and enforcement over every form of AI in use. It secures public generative AI applications, homegrown AI apps, AI coding agents, and autonomous AI agents through a discover, detect, govern, and prevent model: surfacing shadow AI, monitoring interactions, enforcing usage policies in real time, and blocking data leakage and adversarial manipulation before they cause harm.
How it works
The platform builds a continuously updated inventory of the AI applications, agents, models, and Model Context Protocol (MCP) servers in use, including tools adopted without IT approval. It monitors prompts, model responses, and data flows across sanctioned and unsanctioned AI services, detecting anomalies, compliance violations, and prompt-based attacks as they occur. Enforcement acts at the point of use: unsafe requests are blocked, sensitive data is redacted before it reaches AI services, and autonomous agent workflows are mapped decision by decision so invalid actions are stopped. Third-party AI applications receive risk assessments covering security, compliance, and data exposure.
Credentials and traction
Ovalix was named a Sample Vendor for AI Usage Control in the 2026 Gartner Hype Cycle for Workspace Security. The platform holds a Cloud Security Alliance (CSA) STAR Level 1 listing, with a CAIQ self-assessment published on the CSA STAR Registry in February 2026. Customers include COFCO, Blueair, Make-A-Wish, and International Seaways, and the platform targets enterprise security teams enabling organization-wide AI adoption.
Key Capabilities
mapped to solution categoriesDiscovers and categorizes the organization's use of third-party AI, whether consumed as a service, installed locally, or embedded inside other applications, building a continuously updated inventory of AI usage including shadow AI.
Defines organizational AI usage policies and enforces them at the point of use - allowing, blocking, redirecting, or constraining specific AI services, models, and features per user, group, or data context.
Inspects prompts, uploads, and AI-generated responses for sensitive data across modalities, preventing exposure of regulated or proprietary information to third-party AI services.
Assesses and scores the risk of discovered AI services and embedded AI features (data handling, training-use terms, hosting, vendor posture) to drive sanction/block decisions.
Detects anomalous AI usage patterns - unusual volumes, off-policy services, atypical data flows to AI endpoints - and alerts on potential misuse or exfiltration through AI channels.
Secures AI coding assistants and their Model Context Protocol connections against unsafe actions, data exposure and supply-chain risks.
Intercepts prompts and completions to prevent sensitive data (PII, credentials, internal IP), from being transmitted to external LLM services or returned in model responses.
Detects and blocks adversarial inputs designed to override system prompts, extract training data, or redirect model behavior. Detection approaches include pattern matching, input semantic analysis, and secondary model classification.
Evaluates model outputs against content policy, data classification rules, and format expectations before delivery to end users, blocking responses containing sensitive data or policy violations.
Discovers, governs and allowlists the Model Context Protocol servers and tools that AI agents are permitted to invoke.
Compliance
certificationsImplementation & support
Info last updated on July 26, 2026
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