Matters.AI - AI Security Engineer for Data Reviews & Product Details

The platform is expanding quickly, with new partners and product launches adding to its data footprint week after week. Coverage across AWS, GCP, and its SaaS stack keeps pace without requiring me to constantly monitor or manage individual integrations. Review collected by and hosted on G2.com.

More chart options in reports would be helpful for creating presentation-ready visuals. The tabular exports cover most of what I need, but having additional visual formats would make the reporting feel more complete. I’d also welcome Terraform module support for IaC-driven scan setup on newly provisioned infrastructure. The setup process today is smooth, but native IaC support would reduce friction even further. Review collected by and hosted on G2.com.

We picked Matters because we needed something my team could actually operate at our scale without growing headcount. Our operations require a clear picture of where sensitive data lives across the systems we run. Onboarding was handled well. The CS team walked us through best practices rather than handing us a generic playbook. Continuous monitoring picks up configuration drift on data store permissions before it shows up in an audit finding.

The agentless approach for cloud data stores meant no security review headaches and no production performance hit. Exposure scoring reflects how exploitable a finding actually is, not just whether sensitive data is present. That changes how my team prioritizes. It does the job we hired it to do, and it does it well. Review collected by and hosted on G2.com.

Native CI/CD pipeline triggers for scanning on deployment events would be a nice addition. Today, scans are scheduled or manually triggered, and event-driven scans would close the feedback loop faster. Review collected by and hosted on G2.com.

What I keep coming back to is the breadth. Having DSPM, DLP, and DDR in one solution with a single operational view is rare.

Scan performance is strong. We run large estates, and the platform handles the volume without turning into a bottleneck. Sensitive data discovery in SaaS apps like Google Workspace and Slack has been a valuable addition alongside what we already get from cloud scans. Continuous monitoring also catches configuration drift in data store permissions before it turns into an audit finding.

Findings are presented with the relevant data context attached, so I can see what was found, where it lives, and why it matters before I even open the detailed view. Data lineage tracking shows where sensitive content originated and how it has propagated, which has been especially helpful for incident scoping. Overall, it’s a tool we genuinely rely on; not something we just install and forget. Review collected by and hosted on G2.com.

The reporting dashboard could benefit from a few more pre-built templates geared toward board-level presentations. The underlying data is already there, but having a couple of additional visualization options would make it easier to present and would save preparation time. Review collected by and hosted on G2.com.

We picked Matters because we needed something my team could actually operate at our scale without growing headcount. Our sensitive data, including customer PII, sits across multiple systems, and tracking that has always been a challenge.

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'. The platform identifies sensitive data inside log files and backup snapshots, which other tools we tried completely missed.

Scans run continuously and pick up new data stores as our infrastructure grows. We do not have to remember to re-scope coverage. The platform surfaces excessive permissions and toxic combinations clearly, which has been the most useful access governance signal we have had. Across the team the feedback has been consistently positive. Review collected by and hosted on G2.com.

Initial scan configuration would benefit from a wizard with more pre-built profiles for common cloud architectures. Manual setup works fine, but templates would shorten time to first scan. Review collected by and hosted on G2.com.

I value tools that give my team back time. Matters does that by cutting out the manual reconciliation work we used to do across separate scans.

Scans run continuously and pick up new data stores as our infrastructure grows. We do not have to remember to re-scope coverage. 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'. Coverage across AWS, GCP, and our SaaS stack works without us having to babysit individual integrations.

Insider risk indicators are tied to data movement rather than purely behavioral analytics, which makes alerts more credible. Integration into our existing SIEM and ticketing tools was straightforward. The platform plays well with the stack we already have. What we get out of it now is a meaningful step up from where we were before. Review collected by and hosted on G2.com.

Some of the configuration screens are dense. Splitting a few of them into guided steps would be a small UX improvement. Support for custom classification labels alongside the built-in taxonomy would give teams with internal data classification standards more flexibility.

Problems it solves and benefits:

We were already certified through a compliance program, but that gave us policy artifacts, not operational visibility into where sensitive data actually lived.

Coverage across our AWS data stores, our SaaS apps, and our endpoint fleet is delivered from one place with consistent context. Data lineage and fingerprinting let us trace where our specific sensitive content has traveled, not just where pattern matches exist. Matters gave us continuous visibility into data discovery, classification, and access exposure across the environments that matter.

Data security has moved from being a topic we used to dread in board reviews to one we can speak to with evidence. The platform paid for itself in the audit cycle alone, before factoring in the operational time savings across the team. Review collected by and hosted on G2.com.

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.

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.

The Platform reduced our weekly data audit work from form a full afternoon to maybe an hour. our payments business handles transaction data and customer PII at volume and that needs continuous oversight not point in time audits. Sensitive data discovery in SaaS apps like google workspace and slack has been a useful addition to what we get from cloud scan data lineage tracking shows us where sensitive content originated and where itit has been useful for incident scoping. the data fingerprinting approach lets us track our specific data assets, not just generic pattern matches. The platform identifies sensitive data inside log files and backup snapshot whic other tools we tried completely missed. it does the job we hired it to do and it does well Review collected by and hosted on G2.com.

Terraform module support for IaC-driven scan setup on newly provisioned infrastructure would be welcome. Today's setup process is smooth, but native IaC support would reduce friction further. Native integration with our internal ticketing tool would be a small but useful add. API and webhook options work, but a direct connector would be cleaner. Review collected by and hosted on G2.com.

Customer profiles, payment data, and address records sit across multiple data stores and analytics systems. The first thing I noticed running scans across our cloud estate is how much fewer false positives we got compared to the rule-based tool we used before.

Scans run continuously and pick up new data stores as our infrastructure grows. We do not have to remember to re-scope coverage. The endpoint visibility through eBPF tracing surfaces movement of sensitive data we would never have caught with file scans alone. The platform surfaces excessive permissions and toxic combinations clearly, which has been the most useful access governance signal we have had.

Insider risk indicators are tied to data movement rather than purely behavioral analytics, which makes alerts more credible. Across the team the feedback has been consistently positive. Review collected by and hosted on G2.com.

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. AppSec-to-DSPM integration that connects code-level findings to data store findings would create a tighter end-to-end workflow Review collected by and hosted on G2.com.

We chose Matters because we needed something my team could realistically run at our scale without adding headcount. We also needed a clear, reliable view of where sensitive data lives across the systems we operate.

The data lineage tracking shows where sensitive content originated and how it has propagated, which has been especially helpful for incident scoping. The asset inventory ties data security findings back to the right cloud accounts and owners, making it straightforward to route tickets.

Entitlement analysis connects sensitive data to the people who can actually access it. That intersection is usually where the real risk sits, and Matters surfaces it clearly. It earned its place in our stack within the first quarter. Review collected by and hosted on G2.com.

Pre-built mappings to specific Indian regulatory templates (RBI Master Directions, SEBI guidelines, IRDAI) would help reduce the effort involved in preparing regulatory reports. Documentation for some of the newer integrations is still being filled in. The core documentation is solid overall, but a few of the newer connectors would benefit from more detailed setup notes and clearer guidance. Review collected by and hosted on G2.com.

I like Matters.AI's AI-driven approach for identifying sensitive data and managing security risks. It helps improve visibility into sensitive data, identifies potential security risks, and strengthens data protection across cloud environments. I find this approach valuable because it simplifies data protection and enhances visibility. The setup was quite easy as well, which was a nice bonus. Review collected by and hosted on G2.com.

The platform could be even better with a more intuitive dashboard, deeper customization options, and clearer actionable recommendations to help teams prioritize risks and respond faster. Adding advanced automation and seamless integrations with existing security tools would make the platform even more powerful and efficient. Review collected by and hosted on G2.com.