Data ProtectionAI Security

Metomic

Finds sensitive data across SaaS apps and controls what employees and AI agents can do with it.

Data Loss Prevention (DLP)Data Security Posture Management (DSPM)AI Usage Control

Metomic Overview

What it does

Metomic is a Software as a Service (SaaS) and AI data security platform that combines Data Loss Prevention (DLP) and Data Security Posture Management (DSPM) for collaborative cloud applications. It discovers and classifies sensitive data in tools such as Slack, Google Drive, and Notion using a library of hundreds of classifiers tuned on real SaaS data, then applies controls that coach, allow, block, or hold risky requests before data leaves approved boundaries.

How it works

The platform connects to each SaaS application through a prebuilt API connector, with no endpoint agent and nothing to host. A browser extension observes which AI tools employees reach, including shadow AI, and inspects prompts in flight. AI agents route their tool calls through Metomic, which scans requests and responses, redacts sensitive values, and can pause an action until the agent owner approves it in Slack or Microsoft Teams. Classification covers personal, health, and payment data plus credentials such as cloud keys, and each agent action is logged and exportable to a Security Information and Event Management (SIEM) system.

Credentials and traction

SOC 2 Type II certified following a 2024 audit by Johanson Group. Named customers include Zappi, Oyster, TravelPerk, Zego, Juni, and Gorilla, with published case studies across fintech, insurance, healthtech, and HR technology. The platform is available through AWS Marketplace and targets mid-market and enterprise security teams securing employee AI adoption and SaaS collaboration data.

Key Capabilities

Data Loss Prevention (DLP)

Data Security Posture Management (DSPM)

Discovers and classifies sensitive data (PII, PHI, payment data, IP, secrets) across structured and unstructured stores by combining deterministic techniques such as patterns, keywords, and validators with AI/ML techniques such as unsupervised clustering and small language models. Breadth of the technique blend, and whether classification extends to prompts, model outputs, and vector databases, are the primary differentiators; products that rely on pattern matching alone sit at the low end.

Discovers and classifies sensitive data across a heterogeneous cloud estate in one inventory: object storage, managed data warehouses and lakes, cloud database services, and SaaS applications, including sources that are not supported out of the box through custom connectors. Breadth of supported sources and depth per source vary; on-premises and mainframe estates are covered under On-Premises and Mainframe Data Discovery.

AI Usage Control

At a glance

Deployment: Agentless (API Integration) · Browser Extension · SaaS
Compliance: SOC 2 Type II
Integrations: 18 tools
Support: Email Support

Info last updated on September 7, 2026

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