The story behind Matters.AI funding journey

Insider Data Risk & Behaviour Detection

We Detect Intent, Not Just Anomalies

Matters detects risky data access, unusual behavior, and potential misuse, and helps you investigate and act before sensitive data is exposed.

 
PROBLEM
Most breaches come from the inside, where users have legitimate credentials but illegitimate intentions.

Logs show activity. They don’t show data risk.

A file download looks the same whether it’s harmless or sensitive, leaving teams blind to real exposure.

Too many alerts. Not enough context

Thousands of data access events surface every day but without understanding sensitivity and intent, most get ignored.

Legacy tools miss real data misuse

When access looks normal, risky behavior goes unnoticed, even when sensitive data is involved.

SOLUTION
Behavioral Intelligence That Predicts Pre-Breach Intent
Matters doesn't wait for the exfiltration to happen. We use agentic modeling to understand the "Human-Data Relationship”, identifying when a trusted user begins acting like a threat.

Behavioral Discovery

Matters.AI learns the unique "data signature" of every user and role, establishing a baseline of normal, productive data interaction.

Anomaly Assessment

When a user accesses sensitive data they haven't touched in 6 months, we spike their risk score and prioritize them for review.

Agentic Intervention

We can automatically revoke access or trigger multi-factor authentication if it detects a user attempting to bulk-download proprietary IP.

Vigilant Oversight

24/7 monitoring ensures that "Privileged User" status isn't being abused, tracking data movement in real-time across SaaS and endpoints.

Proven Track Record

Matters successfully identified "Flight Risk" behavior in a major tech firm 48 hours before the employee attempted to move code to a personal drive.

Women Working On Laptop
start today

Security gaps don't wait. Neither should you.

Matters gives you instant visibility, prioritized risks, and guided fixes all in one platform.