G2

Avinash P.

Business development manager

Mid-Market (51-1000 emp.)

8/18/2026

"Sharpest reduction in data risk we have measured year over year"

5/5

What do you like best about Matters.AI - AI Security Engineer for Data?

A cloud platform business holds tenant data, configuration data, and workload metadata across regions and accounts. Coordinating between security and engineering used to involve a lot of back and forth. The shared view in Matters has cut that out.

The remediation guidance is specific enough that the receiving engineer knows what to do without a separate conversation. False positive rate is the lowest I have seen in a DSPM tool. It changes the conversation from 'is this real' to 'how do we fix this'. Integration into our existing SIEM and ticketing tools was straightforward. The platform plays well with the stack we already have.

Insider risk indicators are tied to data movement rather than purely behavioral analytics, which makes alerts more credible. The platform identifies sensitive data inside log files and backup snapshots, which other tools we tried completely missed. It has freed up real time for the team to focus on the higher-impact work. Review collected by and hosted on G2.com.

What do you dislike about Matters.AI - AI Security Engineer for Data?

The findings view could use additional filter dimensions for environments with very large scan result sets. Standard filters cover most cases, but more granularity would be nice. Region-specific compliance views could be surfaced more prominently. The data needed for cross-jurisdiction reporting is in the platform, but a dedicated regional compliance lens would be a useful add. Review collected by and hosted on G2.com.

What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?

Our last DSPM tool produced more noise than signal, and we needed something that could actually be operated by the team without constant tuning. Our environment spans engineering systems, customer project data, and the cloud and SaaS tools the team runs, and we needed continuous visibility across all of it.

The endpoint visibility piece, powered by eBPF tracing, has given us data movement insight that file scans alone could not deliver. The continuous scanning model means we catch new exposures shortly after they appear instead of months later in an audit. Matters gave us continuous visibility into data discovery, classification, and access exposure across the environments that matter. Review collected by and hosted on G2.com.