--- title: Matters.AI - AI Security Engineer for Data Reviews meta\_title: 'Matters.AI - AI Security Engineer for Data Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 14 reviews by the users' company size, role or industry to find out how Matters.AI - AI Security Engineer for Data works for a business like yours. aggregate\_rating: rating\_value: 5.0 review\_count: 14 scale: '5' date\_modified: '2026-08-20' parent\_category: name: Data Security url: https://www.g2.com/categories/data-security --- # Matters.AI - AI Security Engineer for Data Reviews & Product Details Visit Website 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. * * * Product Website Matters.AI - AI Security Engineer for Data Seller [Matters.AI](https://www.g2.com/sellers/matters-ai) Discussions [Matters.AI - AI Security Engineer for Data Community](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/discuss) Languages Supported English Overview by Hemant Warier Show More ## Matters.AI - AI Security Engineer for Data Integrations (15) What do users say about integrations? Verified by Matters.AI - AI Security Engineer for Data [Show More Integrations](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/integrations) BS Biswajit S. Senior Cybersecurity Solution Architect Small-Business (50 or fewer emp.) 8/19/2026 "Worked across our AWS and SaaS stack without drama" 5/5 What do you like best about Matters.AI - AI Security Engineer for Data? 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. What do you dislike about Matters.AI - AI Security Engineer for Data? 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. What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you? 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. Show More Current UserValidated ReviewerSource: Organic AP 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. Show More Current UserValidated ReviewerSource: Organic SG sameer G. National Presales Manager- Cyber Security Enterprise (\> 1000 emp.) 8/18/2026 "Data SecurityThe platform behind our most successful audit cycle yet" 5/5 What do you like best about Matters.AI - AI Security Engineer for Data? 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. What do you dislike about Matters.AI - AI Security Engineer for Data? 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. What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you? The core problem we needed to solve was a lack of clear visibility into where sensitive data actually lives across our environment. Running data security for a payments platform means dealing with regulatory scrutiny, card data, and a constantly changing cloud footprint. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic AC Angeline C. Technical Executive Small-Business (50 or fewer emp.) 8/18/2026 "Gave us back time the team needed elsewhere" 5/5 What do you like best about Matters.AI - AI Security Engineer for Data? 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. What do you dislike about Matters.AI - AI Security Engineer for Data? 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. What problems is Matters.AI - AI Security Engineer for Data solving and how is that benefiting you? The core problem we needed to solve was a lack of clear visibility into where sensitive data actually lives across our environment. Our consumer platform scales fast, and the data footprint grows weekly with new partners and product launches. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic GV Gaurav V. CTO Small-Business (50 or fewer emp.) 4/14/2026 "The data visibility layer that compliance frameworks cannot provide" 4.5/5 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. Review collected by and hosted on G2.com. 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. 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? 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. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic ![Kamalakannan C.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Kamalakannan C.") KC Kamalakannan C. Chief Technologist and Security Officer Small-Business (50 or fewer emp.) 3/24/2026 "Strong Partner and Innovative AI-Powered Data Classification" 5/5 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. Review collected by and hosted on G2.com. 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. 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? 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. Review collected by and hosted on G2.com. Show More 4/8/2026 Current UserValidated ReviewerSource: Organic ![Nashiha A.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Nashiha A.") NA Nashiha A. Project Manager Mid-Market (51-1000 emp.) 4/7/2026 "Matters.AI Makes Sensitive Data Discovery and Remediation Effortless" 5/5 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. Review collected by and hosted on G2.com. 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. 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? 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. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic ![Shashi Kiran K.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shashi Kiran K.") SK Shashi Kiran K. GRC Engineer Mid-Market (51-1000 emp.) 3/25/2026 "Replaced manual audits with continuous AI-driven data visibility that just works" 5/5 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. Review collected by and hosted on G2.com. 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. 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 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. Review collected by and hosted on G2.com. Show More 4/7/2026 Current UserValidated ReviewerSource: Organic MK Madhulika k. Enterprise Sales Manager Mid-Market (51-1000 emp.) 4/6/2026 "The DSPM platform that outperforms in every evaluation: proven results across industries" 5/5 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. Review collected by and hosted on G2.com. 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. 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? 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. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic ![Amol G.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Amol G.") AG Amol G. Lead Software Engineer Enterprise (\> 1000 emp.) 3/27/2026 "Finally a data security tool that understands context not noise" 5/5 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. Review collected by and hosted on G2.com. 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. 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? 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. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: Organic ##### Pricing Pricing details for this product isn’t currently available. Visit the vendor’s website to learn more. [ View More Pricing Information ](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/pricing) ##### ##### Matters.AI - AI Security Engineer for Data Features Discovery & Classification - Data Security Posture Management (DSPM) Continuous real‑time monitoring Discover & classify sensitive data Risk Prioritization - Data Security Posture Management (DSPM) Detect excessive entitlements & toxic combinations Risk‑based exposure scoring Remediation & Governance - Data Security Posture Management (DSPM) Guided remediation actions [ View More Features ](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/features) ## Top-Rated Alternatives [ ![Wiz](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Wiz") Wiz 4.7/5(845) ](https://www.g2.com/products/wiz-wiz/reviews) [ ![Rubrik](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Rubrik") Rubrik 4.5/5(289) ](https://www.g2.com/products/rubrik/reviews) [ ![SailPoint](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "SailPoint") SailPoint 4.5/5(199) ](https://www.g2.com/products/sailpoint/reviews) [ View All Alternatives ](https://www.g2.com/products/matters-ai-ai-security-engineer-for-data/competitors/alternatives) ##### Categories on G2 [Data Security Posture Management (DSPM)](https://www.g2.com/categories/data-security-posture-management-dspm) ##### Explore More [Best platforms for automating cloud compliance audits](https://www.g2.com/discussions/what-are-the-best-platforms-for-automating-cloud-compliance-audits)[Observe.AI vs Cyara Platform for a contact center running on Genesys or Five9 comparing Contact Center AI Observability tools: which gives better unified visibility across AI model performance and compliance monitoring?](https://www.g2.com/discussions/observe-ai-vs-cyara-platform-for-a-contact-center-running-on-genesys-or-five9-comparing-contact-center-ai-observability-tools-which-gives-better-unified-visibility-across-ai-model-performance-and-compliance-monitoring)[Which affiliate marketing platforms are reliable enough that a growing mid-market program can scale to hundreds of partners without things breaking?](https://www.g2.com/discussions/which-affiliate-marketing-platforms-are-reliable-enough-that-a-growing-mid-market-program-can-scale-to-hundreds-of-partners-without-things-breaking) [Best Remote Desktop Software](https://www.g2.com/discussions/what-is-your-favorite-remote-desktop-software)[Top Employer of Record software for small app development companies](https://www.g2.com/discussions/top-employer-of-record-software-for-small-app-development-companies)[Best software for managing parallel builds](https://www.g2.com/discussions/best-software-for-managing-parallel-builds) [Show MoreShow Less](javascript:void(0);)