Nikki Ralston

We knew we were on a hot streak, and now it’s official.

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Sentra has been named one of CRN’s 10 Hottest Cybersecurity Startups of 2025. This recognition is a direct reflection of our commitment to redefining data security for the cloud and AI era, and of the growing trust forward-thinking enterprises are placing in our unique approach.

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This milestone is more than just an award. It shows our relentless drive to protect modern data systems and gives us a chance to thank our customers, partners, and the Sentra team whose creativity and determination keep pushing us ahead.

The Market Forces Fueling Sentra’s Momentum

Cybersecurity is undergoing major changes. With 94% of organizations worldwide now relying on cloud technologies, the rapid growth of cloud-based data and the rise of AI agents have made security both more urgent and more complicated. These shifts are creating demands for platforms that combine unified data security posture management (DSPM) with fast data detection and response (DDR).

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Industry data highlights this trend: over 73% of enterprise security operations centers are now using AI for real-time threat detection, leading to a 41% drop in breach containment time. The global cybersecurity market is growing rapidly, estimated to reach $227.6 billion in 2025, fueled by the need to break down barriers between data discovery, classification, and incident response 2025 cybersecurity market insights. In 2025, organizations will spend about 10% more on cyber defenses, which will only increase the demand for new solutions.

Why Recognition by CRN Matters and What It Means

Landing a place on CRN’s 10 Hottest Cybersecurity Startups of 2025 is more than publicity for Sentra. It signals we truly meet the moment. Our rise isn’t just about new features; it’s about helping security teams tackle the growing risks posed by AI and cloud data head-on. This recognition follows our mention as a CRN 2024 Stellar Startup, a sign of steady innovation and mounting interest from analysts and enterprises alike.

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Being on CRN’s list means customers, partners, and investors value Sentra’s straightforward, agentless data protection that helps organizations work faster and with more certainty.

Innovation Where It Matters: Sentra’s Edge in Data and AI Security

Sentra stands out for its practical approach to solving urgent security problems, including:

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• Agentless, multi-cloud coverage: Sentra identifies and classifies sensitive data and AI agents across cloud, SaaS, and on-premises environments without any agents or hidden gaps.
• Integrated DSPM + DDR: We go further than monitoring posture by automatically investigating incidents and responding, so security teams can act quickly on why DSPM+DDR matters.
• AI-driven advancements: Features like domain-specific AI Classifiers for Unstructure advanced AI classification leveraging SLMs, Data Security for AI Agents and Microsoft M365 Copilot help customers stay in control as they adopt new technologies Sentra’s AI-powered innovation.

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With new attack surfaces popping up all the time, from prompt injection to autonomous agent drift, Sentra’s architecture is built to handle the world of AI.

A Platform Approach That Outpaces the Competition

There are plenty of startups aiming to tackle AI, cloud, and data security challenges. Companies like 7AI, Reco, Exaforce, and Noma Security have been in the news for their funding rounds and targeted solutions. Still, very few offer the kind of unified coverage that sets Sentra apart.

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Most competitors stick to either monitoring SaaS agents or reducing SOC alerts. Sentra does more by providing both agentless multi-cloud DSPM and built-in DDR. This gives organizations visibility, context, and the power to act in one platform. With features like Data Security for AI Agents, Sentra helps enterprises go beyond managing alerts by automating meaningful steps to defend sensitive data everywhere.

Thanks to Our Community and What’s Next

This honor belongs first and foremost to our community: customers breaking new ground in data security, partners building solutions alongside us, and a team with a clear goal to lead the industry.

If you haven’t tried Sentra yet, now’s a great time to see what we can do for your cloud and AI data security program. Find out why we’re at the forefront: schedule a personalized demo or read CRN’s full 2025 list for more insight.

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Conclusion

Being named one of CRN’s hottest cybersecurity startups isn’t just a milestone. It pushes us forward toward our vision - data security that truly enables innovation. The market is changing fast, but Sentra’s focus on meaningful security results hasn't wavered.

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Thank you to our customers, partners, investors, and team for your ongoing trust and teamwork. As AI and cloud technology shape the future, Sentra is ready to help organizations move confidently, securely, and quickly.

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The recent exposure of customer data through a compromised Gainsight integration within Salesforce environments is more than an isolated event - it’s a sign of a rapidly evolving class of SaaS supply-chain threats. Even trusted AppExchange partners can inadvertently create access pathways that attackers exploit, especially when OAuth tokens and machine-to-machine connections are involved. This post explores what happened, why today’s security tooling cannot fully address this scenario, and how data-centric visibility and identity governance can meaningfully reduce the blast radius of similar breaches.

A Recap of the Incident

In this case, attackers obtained sensitive credentials tied to a Gainsight integration used by multiple enterprises. Those credentials allowed adversaries to generate valid OAuth tokens and access customer Salesforce orgs, in some cases with extensive read capabilities. Neither Salesforce nor Gainsight intentionally misconfigured their systems. This was not a product flaw in either platform. Instead, the incident illustrates how deeply interconnected SaaS environments have become and how the security of one integration can impact many downstream customers.

Understanding the Kill Chain: From Stolen Secrets to Salesforce Lateral Movement

The attackers’ pathway followed a pattern increasingly common in SaaS-based attacks. It began with the theft of secrets; likely API keys, OAuth client secrets, or other credentials that often end up buried in repositories, CI/CD logs, or overlooked storage locations. Once in hand, these secrets enabled the attackers to generate long-lived OAuth tokens, which are designed for application-level access and operate outside MFA or user-based access controls.

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What makes OAuth tokens particularly powerful is that they inherit whatever permissions the connected app holds. If an integration has broad read access, which many do for convenience or legacy reasons, an attacker who compromises its token suddenly gains the same level of visibility. Inside Salesforce, this enabled lateral movement across objects, records, and reporting surfaces far beyond the intended scope of the original integration. The entire kill chain was essentially a progression from a single weakly-protected secret to high-value data access across multiple Salesforce tenants.

Why Traditional SaaS Security Tools Missed This

Incident response teams quickly learned what many organizations are now realizing: traditional CASBs and CSPMs don’t provide the level of identity-to-data context necessary to detect or prevent OAuth-driven supply-chain attacks.

CASBs primarily analyze user behavior and endpoint connections, but OAuth apps are “non-human identities” - they don’t log in through browsers or trigger interactive events. CSPMs, in contrast, focus on cloud misconfigurations and posture, but they don’t understand the fine-grained data models of SaaS platforms like Salesforce. What was missing in this incident was visibility into how much sensitive data the Gainsight connector could access and whether the privileges it held were appropriate or excessive. Without that context, organizations had no meaningful way to spot the risk until the compromise became public.

Sentra Helps Prevent and Contain This Attack Pattern

Sentra’s approach is fundamentally different because it starts with data: what exists, where it resides, who or what can access it, and whether that access is appropriate. Rather than treating Salesforce or other SaaS platforms as black boxes, Sentra maps the data structures inside them, identifies sensitive records, and correlates that information with identity permissions including third-party apps, machine identities, and OAuth sessions.

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One key pillar of Sentra’s value lies in its DSPM capabilities. The platform identifies sensitive data across all repositories, including cloud storage, SaaS environments, data warehouses, code repositories, collaboration platforms, and even on-prem file systems. Because Sentra also detects secrets such as API keys, OAuth credentials, private keys, and authentication tokens across these environments, it becomes possible to catch compromised or improperly stored secrets before an attacker ever uses them to access a SaaS platform.

Another area where this becomes critical is the detection of over-privileged connected apps. Sentra continuously evaluates the scopes and permissions granted to integrations like Gainsight, identifying when either an app or an identity holds more access than its business purpose requires. This type of analysis would have revealed that a compromised integrated app could see far more data than necessary, providing early signals of elevated risk long before an attacker exploited it.

Sentra further tracks the health and behavior of non-human identities. Service accounts and connectors often rely on long-lived credentials that are rarely rotated and may remain active long after the responsible team has changed. Sentra identifies these stale or overly permissive identities and highlights when their behavior deviates from historical norms. In the context of this incident type, that means detecting when a connector suddenly begins accessing objects it never touched before or when large volumes of data begin flowing to unexpected locations or IP ranges.

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Finally, Sentra’s behavior analytics (part of DDR) help surface early signs of misuse. Even if an attacker obtains valid OAuth tokens, their data access patterns, query behavior, or geography often diverge from the legitimate integration. By correlating anomalous activity with the sensitivity of the data being accessed, Sentra can detect exfiltration patterns in real time—something traditional tools simply aren’t designed to do.

The 2026 Outlook: More Incidents Are Coming

The Gainsight/Salesforce incident is unlikely to be the last of its kind. The speed at which enterprises adopt SaaS integrations far exceeds the rate at which they assess the data exposure those integrations create. OAuth-based supply-chain attacks are growing quickly because they allow adversaries to compromise one provider and gain access to dozens or hundreds of downstream environments. Given the proliferation of partner ecosystems, machine identities, and unmonitored secrets, this attack vector will continue to scale.

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Prediction:
Unless enterprises add data-centric SaaS visibility and identity-aware DSPM, we should expect three to five more incidents of similar magnitude before summer 2026.

Conclusion

The real lesson from the Gainsight/Salesforce breach is not to reduce reliance on third-party SaaS providers as modern business would grind to a halt without them. The lesson is that enterprises must know where their sensitive data lives, understand exactly which identities and integrations can access it, and ensure those privileges are continuously validated. Sentra provides that visibility and contextual intelligence, making it possible to identify the risks that made this breach possible and help to prevent the next one.

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In today's digital world, data security in the cloud is essential. You rely on popular observability tools to track availability, performance, and usage—tools that keep your systems running smoothly. However, as your data flows continuously between systems and regions, you need a layer of security that delivers granular insights without disrupting performance.

Cloud service platforms provide the agility and efficiency you expect; however, they often lack the ability to monitor real-time data movement, access, and risk across diverse environments. 

This blog post explains how cloud data monitoring strategies protect your data while addressing issues like data sprawl, data proliferation, and unstructured data challenges. Along the way, we will share practical information to help you deepen your understanding and strengthen your overall security posture.

Why Real-Time Cloud Monitoring Matters

In the cloud, data does not remain static. It shifts between environments, services, and geographical locations. As you manage these flows, a critical question arises: "Where is my sensitive cloud data stored?" 

Knowing the exact location of your data in real-time is crucial for mitigating unauthorized access, preventing compliance issues, and effectively addressing data sprawl and proliferation. 

Risk of Data Misplacement: When Data Is Stored Outside Approved Environments

Misplaced data refers to information stored outside its approved environment. This can occur when data is in unauthorized or unverified cloud instances or shadow IT systems. Such misplacement heightens security risks and complicates compliance efforts.

A simple table can clarify the differences in risk levels and possible mitigation strategies for various data storage environments:

Risk of Insufficient Monitoring: Gaps in Real-Time Visibility of Rapid Data Movements

The high velocity of data flows in vast cloud environments makes tracking data challenging, and traditional monitoring methods may fall short. 

The rapid data movement means that data proliferation often outstrips traditional monitoring efforts. Meanwhile, the sheer volume, variety, and velocity of data require risk analysis tools that are built for scale. 

Legacy systems typically struggle with these issues, making it difficult for you to maintain up-to-date oversight and achieve a comprehensive security posture. Explore Sentra's blog on data movement risks for additional details.

Limitations of Legacy Data Security Solutions

When evaluating how to manage and monitor cloud data, it’s clear that traditional security tools fall short in today’s complex, cloud-native environments.

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Older security solutions (built for the on-prem era!) were designed for static environments, while today's dynamic cloud demands modern, more scalable approaches. Legacy data classification methods, as discussed in this Sentra analysis, also fail to manage unstructured data effectively.

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Let’s take a deeper look at their limitations:

• Inadequate data classification: Traditional data classification often relies on manual processes that fail to keep pace with real-time cloud operations. Manual classification is inefficient and prone to error, making it challenging to quickly identify and secure sensitive information.
  
  • Such outdated methods particularly struggle with unstructured data management, leaving gaps in visibility.
• ‍Scalability issues: As your enterprise grows and embraces the cloud, the volume of data you must handle also grows exponentially. When this happens, legacy systems cannot keep up. They lag behind and are slow to respond to potential risks, exposing your company to possible security breaches.
  
  • Modern requirements for cloud data management and monitoring call for solutions that scale with your business.

• High operational costs: Maintaining outdated security tools can be expensive. Legacy systems often incur high operational costs due to manual oversight, taxing cloud compute consumption, and inefficient processes. 
  
  • These costs can escalate quickly, especially compared to cloud-native solutions offering automation, efficiency, and streamlined management.

To address these risks, it's essential to have a strategy that shows you how to monitor data as it moves, ensuring that sensitive files never end up in unapproved environments.

Best Practices for Cloud Data Monitoring and Protection

In an era of rapidly evolving cloud environments, implementing a cohesive cloud data monitoring strategy that integrates actionable recommendations is essential. This approach combines automated data discovery, real-time monitoring, robust access governance, and continuous compliance validation to secure sensitive cloud data and address emerging threats effectively.

Automated Data Discovery and Classification

Implementing an agentless, cloud-native solution enables you to continuously discover and classify sensitive data without any performance drawbacks. Automation significantly reduces manual errors and delivers real-time insights for robust and efficient data monitoring.

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Benefits include:

• Continuous data discovery and classification
• Fewer manual interventions
• Real-time risk assessment
• Lower operational costs through automation
• Simplified deployment and ongoing maintenance
• Rapid response to emerging risks with minimal disruption

By adopting a cloud-native data security platform, you gain deeper visibility into your sensitive data without adding system overhead.

Real-Time Data Movement Monitoring

To prevent breaches, real-time cloud monitoring is critical. Receiving real-time alerts will empower you to take action quickly and mitigate threats in the event of unauthorized transfers or suspicious activities. 

A well-designed monitoring dashboard can visually display data flows, alert statuses, and remediation actions—all of which provide clear, actionable insights. Alerts can also flow directly to remediation platforms such as ITSM or SOAR systems.

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In addition to real-time dashboards, implement automated alerting workflows that integrate with your existing incident response tools. This ensures immediate visibility when anomalies occur for a swift and coordinated response. Continuous monitoring highlights any unusual data movement, helping security teams stay ahead of threats in an environment where data volumes and velocities are constantly expanding.

Robust Access Governance

Only authorized parties should be able to access and utilize sensitive data. Maintain strict oversight by enforcing least privilege access and performing regular reviews. This not only safeguards data but also helps you adhere to the compliance requirements of any relevant regulatory standards.

A checklist for robust governance might include:

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• Implementation of role-based and attribute-based access control
• Periodic access audits
• Integration with identity management systems

Ensuring Compliance and Data Privacy

Adhering to data privacy regulations that apply to your sector or location is a must. Continuous monitoring and proactive validation will help you identify and address compliance gaps before your organization is hit with a security breach or legal violation. Sentra offers actionable steps related to various regulations to solidify your compliance posture.

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Integrating automated compliance checks into your security processes helps you meet regulatory requirements. To learn more about scaling your security infrastructure, refer to Sentra’s guide to achieving exabyte-scale enterprise data security.

Beyond tools and processes, cultivating a security-minded culture is critical. Conduct regular training sessions and simulated breach exercises so that everyone understands how to handle sensitive data responsibly. Encouraging active participation and accountability across the organization solidifies your security posture, bridging the gap between technical controls and human vigilance.

Sentra Addresses Cloud Data Monitoring Challenges

Sentra's platform complements your current observability tools, enhancing them with robust data security capabilities. Let’s explore how Sentra addresses common challenges in cloud data monitoring.

Exabyte-Scale Mastery: Navigating Expansive Data Ecosystems

Sentra’s platform is designed to handle enormous data volumes with ease. Its distributed architecture and elastic scaling provide comprehensive oversight and ensure high performance as data proliferation intensifies. The platform's distributed architecture and elastic scaling capabilities guarantee high performance, regardless of data volume.

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Key features:

• Distributed architecture for high-volume data
• Elastic scaling for dynamic cloud environments
• Integration with primary cloud services

Seamless Automation: Transforming Manual Workflows into Continuous Security

By automating data discovery, classification, and monitoring, Sentra eliminates the need for extensive manual intervention. This streamlined approach provides uninterrupted protection and rapid threat response. 

Automation is essential for addressing the challenges of data sprawl without compromising system performance.

Deep Insights & Intelligent Validation: Harnessing Context for Proactive Risk Detection

Sentra distinguishes itself by providing deep contextual analysis of your data. Its intelligent validation process efficiently detects anomalies and prioritizes risks, enabling precise and proactive remediation. 

This capability directly addresses the primary concern of achieving continuous, real-time monitoring and ensuring precise, efficient data protection.

Unified Security: Integrating with your Existing Systems for Enhanced Protection

One of the most significant advantages of Sentra's platform is its seamless integration with your current SIEM and SOAR tools. This unified approach allows you to maintain excellent observability with your trusted systems while benefiting from enhanced security measures without any operational disruption.

Conclusion

Effective cloud data monitoring is achieved by blending the strengths of your trusted observability tools with advanced security measures. By automating data discovery and classification, establishing real-time monitoring, and enforcing robust access governance, you can safeguard your data against emerging threats. 

Elevate your operations with an extra layer of automated, cloud-native security that tackles data sprawl, proliferation, and compliance challenges. After carefully reviewing your current security and identifying any gaps, invest in modern tools that provide visibility, protection, and resilience.

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Maintaining cloud security is a continuous task that demands vigilance, innovation, and proactive decision-making. Integrating solutions like Sentra's platform into your security framework will offer robust, scalable protection that evolves with your business needs. The future of your data security is in your hands, so take decisive steps to build a safer, more secure cloud environment.

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As organizations scale their use of Google Cloud, sensitive data is rapidly expanding across cloud storage, data lakes, and analytics platforms, often without clear visibility or consistent control. Native cloud security tools focus on infrastructure and configuration risk, but they do not provide a reliable understanding of what sensitive data actually exists inside cloud environments, or how that data is being accessed and used.

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Sentra secures Google Cloud by delivering deep, AI-driven data discovery and classification across cloud-native services, unstructured data stores, and shared environments. With continuous visibility into where sensitive data resides and how exposure evolves over time, security teams can accurately assess real risk, enforce data governance, and reduce the likelihood of data leaks, without slowing cloud adoption.

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As data extends into Google Workspace and powers Gemini AI, Sentra ensures sensitive information remains governed and protected across collaboration and AI workflows. When integrated with Cloud Security Posture Management (CSPM) solutions, Sentra enriches cloud posture findings with trusted data context, transforming cloud security signals into prioritized, actionable insight based on actual data exposure.

The Challenge:
Cloud, Collaboration, and AI Without Data Context

Modern enterprises face three converging challenges:

• Massive data sprawl across cloud infrastructure, SaaS collaboration tools, and data lakes
• Unstructured data dominance, representing ~80% of enterprise data and the hardest to classify
• AI systems like Gemini that ingest, transform, and generate sensitive data at scale

While CSPMs, like Wiz, excel at identifying misconfigurations, attack paths, and identity risk, they cannot determine what sensitive data actually exists inside exposed resources. Lightweight or native DSPM signals lack the accuracy and depth required to support confident risk decisions.

Security teams need more than posture - they need data truth.

Data Security Built for the Google Ecosystem

Sentra secures sensitive data across Google Cloud, Google Workspace, and AI-driven environments with accuracy, scale, and control -going beyond visibility to actively reduce data risk.

Key Sentra Capabilities

• AI-Driven Data Discovery & Classification
  Precisely identifies PII, PCI, credentials, secrets, IP, and regulated data across structured and unstructured sources—so teams can trust the results.
• Best-in-Class Unstructured Data Coverage
  Accurately classifies long-form documents and free text, addressing the largest source of enterprise data risk.
• Petabyte-Scale, High-Performance Scanning
  Fast, efficient scanning designed for cloud and data lake scale without operational disruption.
• Unified, Agentless Coverage
  Consistent visibility and classification across Google Cloud, Google Workspace, data lakes, SaaS, and on-prem.
• Enabling Intelligent Data Loss Prevention (DLP)
  Data-aware controls prevent oversharing, public exposure, and misuse—including in AI workflows—driven by accurate classification, not static rules.‍
• Continuous Risk Visibility
  Tracks where sensitive data lives and how exposure changes over time, enabling proactive governance and faster response.

Strengthening Security Across Google Cloud & Workspace

Google Cloud

Sentra enhances Google Cloud security by:

• Discovering and classifying sensitive data in GCS, BigQuery, and data lakes
• Identifying overexposed and publicly accessible sensitive data
• Detecting toxic combinations of sensitive data and risky configurations
• Enabling policy-driven governance aligned to compliance and risk tolerance

Google Workspace

Sentra secures the largest source of unstructured data by:

• Classifying sensitive content in Docs, Sheets, Drive, and shared files
• Detecting oversharing and external exposure
• Identifying shadow data created through collaboration
• Supporting audit and compliance with clear reporting

Enabling Secure and Responsible Gemini AI

Gemini AI introduces a new class of data risk. Sensitive information is no longer static, it is continuously ingested and generated by AI systems.

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Sentra enables secure and responsible AI adoption by:

• Providing visibility into what sensitive data feeds AI workflows
• Preventing regulated or confidential data from entering AI systems
• Supporting governance policies for responsible AI use
• Reducing the risk of AI-driven data leakage

Wiz + Sentra: Comprehensive Cloud and Data Security

Wiz identifies where cloud risk exists.
Sentra determines what data is actually at risk.

Together, Sentra + Wiz Deliver:

• Enrichment of Wiz findings with accurate, context-rich data classification
• Detection of real exposure, not just theoretical misconfiguration
• Better alert prioritization based on business impact
• Clear, defensible risk reporting for executives and boards

Security teams add Sentra because Wiz alone is not enough to accurately assess data risk at scale, especially for unstructured and AI-driven data.

Business Outcomes

With Sentra securing data across Google Cloud, Google Workspace, and Gemini AI—and enhancing Wiz—organizations achieve:

• Reduced enterprise risk through data-driven prioritization
• Improved compliance readiness beyond minimum regulatory requirements
• Higher SOC efficiency with less noise and faster response
• Confident AI adoption with enforceable governance
• Clearer executive and board-level risk visibility

“Wiz shows us cloud risk. Sentra shows us whether that risk actually impacts sensitive data. Together, they give us confidence to move fast with Google and Gemini without losing control.”
— CISO, Enterprise Organization

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As cloud, collaboration, and AI converge, security leaders must go beyond infrastructure-only security. Sentra provides the data intelligence layer that makes Google Cloud security stronger, Google Workspace safer, Gemini AI responsible, and Wiz actionable.

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Sentra helps organizations secure what matters most, their critical data.

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Data Loss Prevention (DLP) is a keystone of enterprise security, yet traditional DLP solutions continue to suffer from high rates of both false positives and false negatives, primarily because they struggle to accurately identify and classify sensitive data in cloud-first environments.

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New advanced data discovery and contextual classification technology directly addresses this gap, transforming DLP from an imprecise, reactive tool into a proactive, highly effective solution for preventing data loss.

Why DLP Solutions Can’t Work Alone

DLP solutions are designed to prevent sensitive or confidential data from leaving your organization, support regulatory compliance, and protect intellectual property and reputation. A noble goal indeed.  Yet DLP projects are notoriously anxiety-inducing for CISOs. On the one hand,  they often generate a high amount of false positives that disrupt legitimate business activities and further exacerbate alert fatigue for security teams.

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What’s worse than false positives? False negatives. Today traditional DLP solutions too often fail to prevent data loss because they cannot efficiently discover and classify sensitive data in dynamic, distributed, and ephemeral cloud environments.

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Traditional DLP faces a twofold challenge: 

• High False Positives: DLP tools often flag benign or irrelevant data as sensitive, overwhelming security teams with unnecessary alerts and leading to alert fatigue.
  
  
• High False Negatives: Sensitive data is frequently missed due to poor or outdated classification, leaving organizations exposed to regulatory, reputational, and operational risks.
  
  

These issues stem from DLP’s reliance on basic pattern-matching, static rules, and limited context. As a result, DLP cannot keep pace with the ways organizations use, store, and share data, resulting in the dual-edged sword of both high false positives and false negatives. Furthermore, the explosion of unstructured data types and shadow IT creates blind spots that traditional DLP solutions cannot detect. As a result, DLP often can’t  keep pace with the ways organizations use, store, and share data. It isn’t that DLP solutions don’t work, rather they lack the underlying discovery and classification of sensitive data needed to work correctly.

AI-Powered Data Discovery & Classification Layer

Continuous, accurate data classification is the foundation for data security. An AI-powered data discovery and classification platform can act as the intelligence layer that makes DLP work as intended. Here’s how Sentra complements the core limitations of DLP solutions:

1. Continuous, Automated Data Discovery

• Comprehensive Coverage: Discovers sensitive data across all data types and locations - structured and unstructured sources, databases, file shares, code repositories, cloud storage, SaaS platforms, and more.
  
  
• Cloud-Native & Agentless: Scans your entire cloud estate (AWS, Azure, GCP, Snowflake, etc.) without agents or data leaving your environment, ensuring privacy and scalability.
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• Shadow Data Detection: Uncovers hidden or forgotten (“shadow”) data sets that legacy tools inevitably miss, providing a truly complete data inventory.

2. Contextual, Accurate Classification

• AI-Driven Precision: Sentra proprietary LLMs and hybrid models achieve over 95% classification accuracy, drastically reducing both false positives and false negatives.
  
  
• Contextual Awareness: Sentra goes beyond simple pattern-matching to truly understand business context, data lineage, sensitivity, and usage, ensuring only truly sensitive data is flagged for DLP action.
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• Custom Classifiers: Enables organizations to tailor classification to their unique business needs, including proprietary identifiers and nuanced data types, for maximum relevance.

3. Real-Time, Actionable Insights

• Sensitivity Tagging: Automatically tags and labels files with rich metadata, which can be fed directly into your DLP for more granular, context-aware policy enforcement.
  
  
• API Integrations: Seamlessly integrates with existing DLP, IR, ITSM, IAM, and compliance tools, enhancing their effectiveness without disrupting existing workflows.
• Continuous Monitoring: Provides ongoing visibility and risk assessment, so your DLP is always working with the latest, most accurate data map.

How Sentra Supercharges DLP Solutions

Better Classification Means Less Noise, More Protection

• Reduce Alert Fatigue: Security teams focus on real threats, not chasing false alarms, which results in better resource allocation and faster response times.
  
  
• Accelerate Remediation: Context-rich alerts enable faster, more effective incident response, minimizing the window of exposure.
  
  
• Regulatory Compliance: Accurate classification supports GDPR, PCI DSS, CCPA, HIPAA, and more, reducing audit risk and ensuring ongoing compliance.
  
  
• Protect IP and Reputation: Discover and secure proprietary data, customer information, and business-critical assets, safeguarding your organization’s most valuable resources.
  
  

Why Sentra Outperforms Legacy Approaches

Sentra’s hybrid classification framework combines rule-based systems for structured data with advanced LLMs and zero-shot learning for unstructured and novel data types.

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This versatility ensures:

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• Scalability: Handles petabytes of data across hybrid and multi-cloud environments, adapting as your data landscape evolves.
  
• Adaptability: Learns and evolves with your business, automatically updating classifications as data and usage patterns change.
  
• Privacy: All scanning occurs within your environment - no data ever leaves your control, ensuring compliance with even the strictest data residency requirements.

Use Case: Where DLP Alone Fails, Sentra Prevails

A financial services company uses a leading DLP solution to monitor and prevent the unauthorized sharing of sensitive client information, such as account numbers and tax IDs, across cloud storage and email. The DLP is configured with pattern-matching rules and regular expressions for identifying sensitive data.

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What Goes Wrong:

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An employee uploads a spreadsheet to a shared cloud folder. The spreadsheet contains a mix of client names, account numbers, and internal project notes. However, the account numbers are stored in a non-standard format (e.g., with dashes, spaces, or embedded within other text), and the file is labeled with a generic name like “Q2_Projects.xlsx.” The DLP solution, relying on static patterns and file names, fails to recognize the sensitive data and allows the file to be shared externally. The incident goes undetected until a client reports a data breach.

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How Sentra Solves the Problem:

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To address this, the security team set out to find a solution capable of discovering and classifying unstructured data without creating more overhead. They selected Sentra for its autonomous ability to continuously discover and classify all types of data across their hybrid cloud environment. Once deployed, Sentra immediately recognizes the context and content of files like the spreadsheet that enabled the data leak. It accurately identifies the embedded account numbers—even in non-standard formats—and tags the file as highly sensitive.

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This sensitivity tag is automatically fed into the DLP, which then successfully enforces strict sharing controls and alerts the security team before any external sharing can occur. As a result, all sensitive data is correctly classified and protected, the rate of false negatives was dramatically reduced, and the organization avoids further compliance violations and reputational harm.

Getting Started with Sentra is Easy

1. Deploy Agentlessly: No complex installation. Sentra integrates quickly and securely into your environment, minimizing disruption.
   
   
2. Automate Discovery & Classification: Build a living, accurate inventory of your sensitive data assets, continuously updated as your data landscape changes.
   
   
3. Enhance DLP Policies: Feed precise, context-rich sensitivity tags into your DLP for smarter, more effective enforcement across all channels.
   
   
4. Monitor Continuously: Stay ahead of new risks with ongoing discovery, classification, and risk assessment, ensuring your data is always protected.
   
   

“Sentra’s contextual classification engine turns DLP from a reactive compliance checkbox into a proactive, business-enabling security platform.”

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Fuel DLP with Automatic Discovery & Classification

DLP is an essential data protection tool, but without accurate, context-aware data discovery and classification, it’s incomplete and often ineffective. Sentra supercharges your DLP with continuous data discovery and accurate classification, ensuring you find and protect what matters most—while eliminating noise, inefficiency, and risk. 

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Ready to see how Sentra can supercharge your DLP? Contact us for a demo today.

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