# Matters.AI - AI Security Engineer for Data Reviews **Vendor:** Matters.AI **Category:** [ Data Security Posture Management (DSPM)](https://www.g2.com/categories/data-security-posture-management-dspm) **Average Rating:** 5.0/5.0 **Total Reviews:** 10 ## About Matters.AI - AI Security Engineer for Data Matters.AI is an AI-native data security platform that unifies DSPM, data detection and response, database activity monitoring, DLP, and insider risk management into a single intelligence layer. It is built for security teams that need to understand data incidents, not just detect them. Most enterprises have telemetry. What they lack is coherent context. When a data incident unfolds across authorized access, approved cloud storage, and legitimate business channels, scattered alerts from point tools cannot assemble the full story in time. Matters.AI is designed to close that gap. The platform continuously discovers and classifies sensitive data across cloud, SaaS, on-premises repositories, and endpoints. It builds a live data lineage graph to track how data originates, transforms, and propagates across environments. An intent modeling layer evaluates sequences of behavior and not isolated events to distinguish legitimate work from data misuse before exposure becomes irreversible. Endpoint-level visibility ties process behavior, file access, and egress destinations into a factual ground truth record that extends beyond database boundaries. When an incident occurs, Matters.AI generates an Evidence Pack. This is a structured and regulator-ready record of what data was involved, how it propagated, which identities accessed it, and what response actions were taken. It is produced continuously and not assembled manually after the fact. ## Matters.AI - AI Security Engineer for Data Reviews ### 1. The data visibility layer that compliance frameworks cannot provide **Rating:** 4.5/5.0 stars **Reviewed by:** Gaurav V. | CTO, Small-Business (50 or fewer emp.) **Reviewed Date:** April 14, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** We build AI infrastructure. Our platform processes customer ML workloads, training datasets, and model artifacts. Knowing where sensitive data ends up across our environment is not optional for us. It is a business requirement. Matters.AI gave us that answer fast. I check the dashboard weekly and the posture score tells me immediately if anything needs attention. The scans pick up new data stores on their own, classify what is in them, and flag anything sensitive. I do not need to remind anyone to audit anything. It just runs. The classification is sharp. It correctly distinguishes between a model configuration file and a file that contains actual customer data. That distinction matters when you are processing thousands of files across cloud storage. The accuracy has been consistent since day one. The interface is clean. My team did not need a walkthrough to start using it. Findings come with a clear priority and a recommended next step. I hand it off, it gets fixed.Support has been responsive. Setup was done in a day. No disruption to our production workloads. **What do you dislike about Matters.AI - AI Security Engineer for Data?** Nothing that impacts our work. The product does what it says. If anything, having a few more export options for the findings data would be a nice convenience. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** We handle customer data as part of our AI platform. That data moves through pipelines, lands in storage, gets processed, and sometimes ends up in places it should not. Before Matters.AI, we had no systematic way to track where sensitive data was sitting or who had access to it. Now we do. The platform scans continuously, classifies accurately, and gives us a risk score we track every month. When something shows up where it should not be, we know about it the same day and fix it the same week. That speed and visibility is what we needed. ### 2. Strong Partner and Innovative AI-Powered Data Classification **Rating:** 5.0/5.0 stars **Reviewed by:** Kamalakannan C. | Chief Technologist and Security Officer, Small-Business (50 or fewer emp.) **Reviewed Date:** March 24, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** Andromeda uses its DSPM capabilities to analyze the different data stores used in our product. The data insights and overall UX have been neat and intuitive. Its AI-powered classification and discovery feel like a clear differentiator in the market. The tool helps us identify and classify data, and it also recommends remediation in a way that feels genuinely innovative. Overall, it works as a complementary solution alongside our other security tools and practices. **What do you dislike about Matters.AI - AI Security Engineer for Data?** As a partner, I’d really appreciate having more co-branded marketing collateral and access to a dedicated partner portal. The product itself is strong, but the partner enablement side still feels like it could mature further to better support us. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** As both a user and a partner, we needed a DSPM solution that could meet two goals: protecting our own data while also being a credible offering for our clients. The platform provides clear, actionable insights into our data security posture, which makes it easier to understand what needs attention and why. ### 3. Matters.AI Makes Sensitive Data Discovery and Remediation Effortless **Rating:** 5.0/5.0 stars **Reviewed by:** Nashiha A. | Project Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** April 07, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** I handle project delivery for our security and data protection workstreams, and most tools in this space are built for full-time security engineers. They assume you live in the product eight hours a day. Matters.AI is different. It gives me what I need without demanding that I become a security specialist. The first thing I noticed was the dashboard. I land on it and immediately see our posture score, open findings by severity, and what has changed since my last login. No clicking through five tabs to piece together the picture. The layout is intuitive enough that I walked two non-technical team members through it in under fifteen minutes and they were comfortable navigating independently. The intelligence behind the scans is what keeps me confident in the output. The platform figured out which files contained personal identifiers, financial records, and access credentials across our cloud storage and connected applications. I did not have to set up detection rules or feed it sample data. It worked out of the box and the accuracy has been consistent enough that we stopped doing manual spot checks after the first few weeks. Connecting our cloud environment and productivity tools took less than a day. I had budgeted a week for integration based on past experience with other platforms. That time went back into actual project work instead. I specifically tracked system performance during the first month because our engineering team was cautious about anything touching live infrastructure. Zero impact. No latency, no resource spikes, no complaints from the engineering side. From a cost perspective, we replaced a patchwork of manual processes and partial tooling with one platform. The return was clear within the first quarter, both in time saved and in the confidence we now have when answering questions about our data security practices. The team behind the product has been available and responsive throughout. Setup was guided without being hand-holding. Post-deployment, they have flagged configuration opportunities before we asked, which tells me they actually pay attention to how customers are using the product. **What do you dislike about Matters.AI - AI Security Engineer for Data?** There is very little to flag here. If anything, the platform keeps getting better with each update, which means there is always something new to explore. Not really a complaint. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** We had our compliance program sorted out. Certifications were current, policies were documented, and audits were passing. But none of that answered the question that kept coming up internally: do we actually know where customer data sits across our cloud and SaaS stack, and are the permissions on that data what we think they are? The honest answer was no. We had assumptions and documentation, but not evidence. Matters.AI gave us the evidence. Within the first week, the platform mapped sensitive data across storage and applications that had never been part of any formal inventory. It showed us access permissions that had drifted from what our policies described. It assigned a risk score we could track over time. We now pull up live posture data when auditors or customers ask about data protection. That is a fundamentally different conversation than handing over a policy document and hoping nobody asks a follow-up question. The shift from assumption-based to evidence-based data security has been the most valuable operational change we have made this year. ### 4. Replaced manual audits with continuous AI-driven data visibility that just works **Rating:** 5.0/5.0 stars **Reviewed by:** Shashi Kiran K. | GRC Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 25, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** I manage both the DevOps function and project delivery at Dice, so I look at any new tool through two lenses: does it fit into our infrastructure workflows without creating toil, and can I predict its delivery timelines and outcomes reliably. Matters.AI scores well on both. On the DevOps side, the onboarding was clean. We connected our AWS account, the platform picked up our S3 buckets and RDS instances automatically, and scans started running without us having to write custom scripts or deploy sidecar agents. That matters when you are running a lean infrastructure team. The scans do not compete for compute resources on production, which was a concern I had going in. They run independently and the performance overhead is effectively zero. The classification results are where I stopped comparing this to other tools. We had previously tried building internal scripts to tag sensitive data across our storage layer. The coverage was maybe 60% on a good day, and maintaining those scripts was a project in itself. Matters.AI replaced all of that. The platform picks up user PII, payment identifiers, device data, and session tokens across both structured database tables and unstructured file stores. It does this without us feeding it custom rules for every data type. The accuracy has been high enough that our security team stopped running validation checks on the output after the first month. The second thing that stood out from a project management perspective is the guided remediation. Every finding comes with a risk score and a specific action to take. That means I can assign remediation tasks to team members directly from the findings view with clear priority and scope. No ambiguity, no back-and-forth on what needs to happen. For someone tracking sprint deliverables, that clarity is valuable. The exposure scoring dashboard has also become part of our monthly reporting cadence. Leadership gets a single number that reflects our data security posture, and they can see it trending over time. I did not have to build a custom dashboard or pull data into a BI tool. It was there out of the box. **What do you dislike about Matters.AI - AI Security Engineer for Data?** The platform is evolving quickly with new features and capabilities being added regularly. It would be helpful to have a brief in-app changelog or "what's new" summary so that users can stay current with improvements without having to check separately. This is more of a wish-list item than an actual gap. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** Our gaming platform collects user behavioral data, device information, session data, and payment details. As the user base grew, so did the number of places that sensitive data ended up. Cloud storage buckets created for temporary ETL jobs that never got cleaned up. Database replicas provisioned for analytics with the same PII as production. Log aggregation pipelines capturing more than they should. We did not have a systematic way to find and classify all of this. Our compliance posture said we were covered, but operationally I knew there were blind spots we had not mapped. Matters.AI gave us that map. The first scan surfaced sensitive data in storage locations that were not part of any formal data inventory. The entitlement view showed service accounts with broader access than their function required. Since then, we run continuous scans and track our exposure score as a standing agenda item in our security review. The time I used to spend coordinating manual data audits across teams is now spent on actual remediation. From a project delivery standpoint, the platform reduced our mean time from finding to fix by a significant margin because the findings come pre-prioritized and pre-scoped. ### 5. The DSPM platform that outperforms in every evaluation: proven results across industries **Rating:** 5.0/5.0 stars **Reviewed by:** Madhulika k. | Enterprise Sales Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** April 06, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** I work in cybersecurity advisory and spend a significant part of my time helping organizations evaluate and shortlist data security solutions. Having assessed several DSPM platforms in the market, Matters.AI is the one that consistently delivers during proof-of-value engagements. The difference becomes clear within the first scan cycle itself. Most DSPM tools I have seen rely heavily on static rule sets and regex-based classification. Matters.AI takes a fundamentally different approach with its AI Security Engineer model. The platform uses contextual AI to understand the nature of data rather than just matching patterns. This means the classification results are accurate from day one, with significantly fewer false positives compared to alternatives I have benchmarked it against. The breadth of the platform is another factor that sets it apart. DSPM, Database Activity Monitoring, and endpoint security are typically three separate line items in a security budget. Matters.AI brings all three together. For the organizations I work with, particularly in the Indian BFSI and payments space, this consolidation translates directly into faster deployment, lower total cost, and a single pane of glass for data risk. The engagement model deserves specific mention. The team does not operate like a typical vendor. They participate actively in solution scoping, deployment planning, and post-deployment optimization. Every interaction is technically productive rather than sales-driven, which is refreshing in the cybersecurity space. The outcomes I have observed across organizations using the platform have been uniformly strong. Teams consistently report that Matters.AI identified sensitive data and access risks that their existing tools had completely missed. That kind of first-scan impact is what turns an evaluation into a long-term adoption decision. **What do you dislike about Matters.AI - AI Security Engineer for Data?** The customer-facing ROI reporting templates could be more polished for presenting business value to non-technical leadership. The underlying metrics and data are comprehensive, but having a few more executive-ready report formats would help security teams build the internal case for continued investment more efficiently. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** The most common gap I see across organizations is the disconnect between security tooling and data-level visibility. Companies invest heavily in firewalls, SIEM, EDR, and CSPM, but when you ask them where their most sensitive customer data sits and who can access it, the answer is usually incomplete or outdated. Matters.AI closes that gap directly. The AI-driven discovery identifies sensitive data across cloud infrastructure, databases, and SaaS applications. The classification is accurate enough that teams trust the findings without manual re-validation. The entitlement analysis catches over-permissioned access and toxic combinations that accumulate silently over time. The exposure scoring gives leadership a single metric to track posture improvement. For organizations in regulated industries handling Indian financial data, the native support for Aadhaar, PAN, UPI identifiers, and banking data eliminates the custom configuration overhead that other tools require. This accelerates time-to-value and reduces the engineering effort needed during onboarding. The feedback from every organization I have seen adopt the platform has reinforced my confidence in recommending it. Matters.AI consistently delivers measurable results regardless of the industry, data scale, or cloud architecture involved. ### 6. Finally a data security tool that understands context not noise **Rating:** 5.0/5.0 stars **Reviewed by:** Amol G. | Lead Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** What I like most is that Matters.AI actually feels like it understands data instead of just yelling “sensitive data found” 500 times a day. As a security architect, that signal-to-noise ratio matters a lot, and here the AI-driven context around sensitivity, access patterns, and behavior makes alerts feel far more usable. The AI Security Engineer concept is honestly what clicked for me. It feels less like another dashboard I have to babysit and more like a junior analyst who does not get tired, surfaces real issues, and even nudges toward remediation instead of just dumping findings. UI and UX are refreshingly clean. I did not have to dig through five menus to figure out what is going on, which is rare in this space. Integrations are not massive yet, but enough to get started across key cloud and SaaS systems without too much friction. Performance has been solid so far, and since it tries to bring DSPM, DLP-style visibility, and insider risk into one place, it cuts down the usual tool hopping, which is a quiet win for both efficiency and ROI. On support and onboarding, it feels like working with a startup in a good way. Quick responses, open to feedback, and not stuck in rigid processes. Overall, it feels like a modern data security tool built for how data actually behaves today, not just for ticking compliance boxes. **What do you dislike about Matters.AI - AI Security Engineer for Data?** From a security architect's lens, the biggest gaps are mostly around maturity, which is expected but still noticeable. Some features feel like they are still evolving, especially when you compare them to more established DSPM or DAM tools. The vision is clear, but in a few places, you can see it is still catching up in terms of depth. Integrations are another area that could improve. The basics are there, but in a typical enterprise setup, you end up wanting broader and deeper coverage, especially across edge cases and less common data sources. There is also a bit of a balancing act between breadth and depth. It tries to cover DSPM, DLP-style controls, and insider risk in one platform, which is great, but naturally, some areas feel lighter than specialized tools. On the UI side, while it is clean overall, I did run into moments where I wanted more advanced filtering or quicker drill-downs when investigating something specific. You may also need some initial tuning to consistently get high signal alerts. It is definitely better than legacy noise-heavy tools, but not completely hands-off yet. Support and onboarding are responsive, but still have that startup feel where documentation and structured guidance can improve over time. None of these are deal breakers, just typical growing phase gaps. The foundation is solid, but it is still in that phase where you see both the potential and the rough edges. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** The biggest problem it solves for me is the lack of visibility and context around sensitive data. In most environments, data is scattered across cloud, SaaS, and endpoints, and traditional tools either give partial visibility or flood you with low-quality alerts. Matters.AI brings that into a more unified view and adds context, so I can actually understand what data exists, where it is, and who is interacting with it. Another major gap it addresses is the signal-to-noise problem. Instead of static rules or basic pattern matching, it uses context around behavior and access patterns to highlight what actually matters. That directly reduces time spent triaging false positives and lets me focus on real risks. It also helps bridge the usual disconnect between detection and action. Most tools stop at telling you something is wrong. Here, the AI Security Engineer approach pushes toward remediation, which means less back and forth between teams and faster resolution. From an operational standpoint, it reduces the need to juggle multiple tools for DSPM, DLP, and insider risk. That consolidation simplifies workflows, improves efficiency, and makes it easier to manage data security as a whole rather than in silos. Overall, the benefit is pretty straightforward. I spend less time chasing alerts and more time addressing actual risk, with better visibility and context driving decisions. ### 7. Matters.ai Mapped Our Sensitive Data Fast with AI-Driven Classification & DSPM **Rating:** 5.0/5.0 stars **Reviewed by:** Surya Harsha N. | Co-Founder, Information Technology and Services, Mid-Market (51-1000 emp.) **Reviewed Date:** March 24, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** We started with compliance program and it served the purpose well. But as we scaled, we realised compliance frameworks alone do not tell you where your actual sensitive data lives or how it is being accessed. Matters.ai filled that gap completely. The AI driven classification accurately mapped our data across Microsoft Azure, Google Workspace, Linear and Notion. The DSPM module gives us a real time posture view that compliance checklists never could. The agentic approach to remediation is a genuine differentiator. **What do you dislike about Matters.AI - AI Security Engineer for Data?** The platform is feature rich which means there is a steep learning curve for new team members. More guided onboarding walkthroughs would help, however, their customer support is very active and extended to help us onboard. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** Compliance gave us a framework and certifications like ISO 27001:2022 and SOC 2 Type II. But it did not answer the fundamental questions like where our sensitive data actually resides, and who can access it? Matters.ai answers that question comprehensively. The AI classification covers data across cloud storage, SaaS apps, and collaboration tools. The risk scoring lets us prioritise action. This became our default visibility layer on top of our compliance stack. ### 8. A CISO's best investment: AI-powered data visibility that actually works **Rating:** 5.0/5.0 stars **Reviewed by:** Prajal K. | Chief Information Security Officer, Enterprise (> 1000 emp.) **Reviewed Date:** March 23, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** The AI Security Engineer from Matters.AI gives us something no other DSPM tool has delivered: actual clarity on where our sensitive data lives across cloud and SaaS. The automated classification is highly accurate, covering Indian PII patterns (Aadhaar, PAN, UPI IDs) out of the box. The risk-based exposure scoring lets me prioritize what matters instead of drowning in alerts. The agentic remediation capabilities reduce our mean time to respond to data exposure from days to hours. As a fintech CISO, the level of visibility this platform provides into data sprawl across AWS, GCP, and Google Workspace is exactly what we needed. **What do you dislike about Matters.AI - AI Security Engineer for Data?** The reporting dashboard could use a few more customization options for board-level presentations. Minor, but it would save time when preparing quarterly reviews. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** As a regulated fintech, we needed complete visibility into where customer PII and financial data resides across our cloud infrastructure. Before Matters.AI, we had fragmented views and no single pane of glass for data risk. Now, we can map every sensitive data store, identify over-permissioned access, and take action before an incident occurs. The AI-driven classification has reduced manual audit effort significantly, and the posture scoring gives my leadership team a clear metric to track over time. ### 9. Matters.AI Delivers Fast, Low-Noise AI Insights and Strong Data Security **Rating:** 5.0/5.0 stars **Reviewed by:** Wafa A. | Security Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 06, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** What we like best about Matters.AI is how effectively it secures our data at fastn.ai by providing contextual, AI-driven insights with minimal noise. It helps us quickly identify real risks, automate responses, and maintain strong data visibility across our environment. **What do you dislike about Matters.AI - AI Security Engineer for Data?** What we dislike about Matters.AI is that some workflows and configurations can take time to fully understand at the beginning, especially for first-time users. While the platform is powerful, a bit more onboarding guidance or simplification in certain areas could make the initial setup smoother. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** Matters.AI addresses this by providing a single, context-rich view of data activity and automatically highlighting real risks instead of overwhelming us with noise and false alerts. This has significantly reduced the time spent on manual investigation and alert triage. ### 10. Data visibility layer that compliance frameworks cannot provide **Rating:** 5.0/5.0 stars **Reviewed by:** James A. | Security Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 02, 2026 **What do you like best about Matters.AI - AI Security Engineer for Data?** I like that it actually understands the data it finds. Matters.AI works like an automated engineer. It can fix risks on its own so I don't have to do it manually. It also watches data as it moves in real-time, which is much safer than just checking a database once a day. **What do you dislike about Matters.AI - AI Security Engineer for Data?** The platform has so many features that it can be a bit confusing at first. It takes a while for a new person to learn how everything works. **What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you?** Compliance provides frameworks and certifications but doesn’t show where sensitive data lives or who can access it. Matters.AI fills that gap with AI-driven data classification and risk scoring, giving the visibility needed to prioritize action. - [View Matters.AI - AI Security Engineer for Data pricing details and edition comparison](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-19+06%3A52%3A46+-0500&secure%5Bsession_id%5D=975c3509-b28d-444d-ac9a-8e42be0c9ed9&secure%5Btoken%5D=843703d130fe878b83bbc7a2eea73f7868b22369c8c0328401f7d4d7e57cdd26&format=llm_user) ## Matters.AI - AI Security Engineer for Data Integrations - [Amazon AWS Platform](https://www.g2.com/products/amazon-aws-platform/reviews) - [Azure Portal](https://www.g2.com/products/azure-portal/reviews) - [Confluence](https://www.g2.com/products/confluence/reviews) - [Couchbase](https://www.g2.com/products/couchbase/reviews) - [CouchDB](https://www.g2.com/products/couchdb/reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - [GitLab](https://www.g2.com/products/gitlab/reviews) - [Google Workspace](https://www.g2.com/products/google-workspace/reviews) - [Jira](https://www.g2.com/products/jira/reviews) - [Microsoft 365](https://www.g2.com/products/microsoft365/reviews) - [MongoDB Atlas](https://www.g2.com/products/mongodb-atlas/reviews) - [MySQL](https://www.g2.com/products/mysql/reviews) - [PostgreSQL](https://www.g2.com/products/postgresql/reviews) - [Slack](https://www.g2.com/products/slack/reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) ## Matters.AI - AI Security Engineer for Data Features **Discovery & Classification - Data Security Posture Management (DSPM)** - Continuous real‑time monitoring - Discover & classify sensitive data - Custom classification support **Compliance** - Access Management - At-Risk Analysis - DLP Configuration - Sensitive Data Compliance **Risk Prioritization - Data Security Posture Management (DSPM)** - Detect excessive entitlements & toxic combinations - Compliance posture assessment - Risk‑based exposure scoring **Administration** - Database Management - Deduplication - Backup - API / integrations **Remediation & Governance - Data Security Posture Management (DSPM)** - Guided remediation actions - Integration with enforcement tools - Track remediation progress & trends **Security ** - Multi-Factor Authentication - Data Transport - Data Types - Security Tools ## Top Matters.AI - AI Security Engineer for Data Alternatives - [Wiz](https://www.g2.com/products/wiz-wiz/reviews) - 4.7/5.0 (773 reviews) - [SailPoint](https://www.g2.com/products/sailpoint/reviews) - 4.5/5.0 (170 reviews) - [Rubrik](https://www.g2.com/products/rubrik/reviews) - 4.5/5.0 (155 reviews)