Transforming Data Security with Large Language Models (LLMs): Sentra’s Innovative Approach

Over the past year, we’ve seen an incredible surge in enterprise AI adoption. Companies across industries are integrating AI agents and generative AI into their operations to move faster, work smarter, and unlock innovation. But behind every AI breakthrough lies a foundational truth: AI is only as secure as the data behind it.

At Sentra, securing that data has always been our mission, not just to prevent breaches and data leaks, but to empower prosperity and innovation with confidence and control.

Data Security: The Heartbeat of Your Organization

‍As organizations push forward with AI, massive volumes of data, often sensitive, regulated, or business-critical are being used to train models or power AI agents. Too often, this happens without full visibility or governance. 

The explosion of the data security market reflects how critical this challenge has become. At Sentra, we’ve long believed that a Data Security Platform (DSP) must be cloud-native, scalable, and adaptable to real-world enterprise environments. We’ve been proud to lead the way, and our continued growth, especially among Fortune 500 customers, is a testament to the urgency and relevance of our approach.

Scaling for What's Next

‍With the announcement of our $50 million Series B funding round, bringing our total funding to over $100 million, we’re scaling Sentra to meet the moment. We're counting on strong customer momentum and more than tripling revenue year-over-year, and we’re using this investment to grow our team, strengthen our platform, and continue defining what modern data security looks like.

We’ve always said security shouldn’t slow innovation - it should fuel it. And that’s exactly what we’re enabling.

It's All About the People

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At the end of the day, it’s people who build it, scale it, and believe in it. I want to extend a heartfelt thank you to our investors, customers, and, most importantly, our team. It’s all about you! Your belief in Sentra and your relentless execution make everything possible. We couldn’t make it without each and every one of you.

We’re not just building a product, we’re setting the gold standard for data security, because securing your data is the heartbeat of your organization!

Innovation without security isn’t progress. Let’s shape a future where both go together!

Privacy regulations such as GDPR (EU), CCPA/CPRA (California), and others are not just about legal checkboxes, they’re about building trust. In today’s data-driven world, customers expect organizations to be transparent about how their personal information is collected, used, and protected. When companies take privacy seriously, they demonstrate respect for their users, which in turn fosters loyalty and long-term engagement.

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But among the many privacy requirements, Data Subject Access Requests (DSARs) can be the most complex to support. DSARs give individuals the right to request access to the personal data that an organization holds about them—often with a firm deadline of just 30 days to respond. For large enterprises with data scattered across multiple systems, both in the cloud and on-premises, even a single request can trigger a chaotic search across different platforms, manual reviews and legal oversight—it quickly becomes a race against the clock, with compliance, trust, and reputation on the line.

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Key Challenges in Responding to DSARs

Data Discovery & Inventory
For large organizations, pinpointing where personal data resides across a diverse ecosystem of information systems, including databases, SaaS applications, data lakes, and legacy environments, is a complex challenge. The presence of fragmented IT infrastructure and third-party platforms often leads to limited visibility, which not only slows down the DSAR response process but also increases the likelihood of missing or overlooking critical personal data.

Linking Identities Across Systems
A single individual may appear in multiple systems under different identifiers, especially if systems have been acquired or integrated over time. Accurately correlating these identities to compile a complete DSAR response requires sophisticated identity resolution and often manual effort.

Unstructured Data Handling
Unlike structured databases, where data is organized into labeled fields and can be efficiently queried, unstructured data (like PDFs, documents, and logs) is free-form and lacks consistent formatting. This makes it much harder to search, classify, or extract relevant personal information.

Response Timeliness
Regulatory deadlines force organizations to respond quickly, even when data must be gathered from multiple sources and reviewed by legal teams. Manual processes can lead to delays, risking non-compliance and fines.

Volume & Scalability
While most organizations can handle an occasional DSAR manually, spikes in request volume — driven by events like regulatory campaigns or publicized incidents — can overwhelm privacy and legal teams. Without scalable automation, organizations face mounting operational costs, missed deadlines, and an increased risk of inconsistent or incomplete responses.

The Role of Data Security Platforms in DSAR Automation

Sentra is a modern data security platform dedicated to helping organizations gain complete visibility and control over their sensitive data. By continuously scanning and classifying data across all environments (including cloud, SaaS, and on-premises systems) Sentra maintains an always up-to-date data map, giving organizations a clear understanding of where sensitive data resides, how it flows, and who has access to it. This data map forms the foundation for efficient DSAR automation, enabling Sentra’s DSAR module to search for user identifiers only in locations where relevant data actually exists - ensuring high accuracy, completeness, and fast response times.

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Another key factor in managing DSAR requests is ensuring that sensitive customer PII doesn’t end up in unauthorized or unintended environments. When data is copied between systems or environments, it’s essential to apply tokenization or masking to prevent unintentional sprawl of PII. Sentra helps identify misplaced or duplicated sensitive data and alerts when it isn’t properly protected. This allows organizations to focus DSAR processing within authorized operational environments, significantly reducing both risk and response time.

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Smart Search of Individual Data

To initiate the generation of a Data Subject Access Request (DSAR) report, users can submit one or more unique identifiers—such as email addresses, Social Security numbers, usernames, or other personal identifiers—corresponding to the individual in question. Sentra then performs a targeted scan across the organization’s data ecosystem, focusing on data stores known to contain personally identifiable information (PII). This includes production databases, data lakes, cloud storage services, file servers, and both structured and unstructured data sources.

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Leveraging its advanced classification and correlation capabilities, Sentra identifies all relevant records associated with the provided identifiers. Once the scan is complete, it compiles a comprehensive DSAR report that consolidates all discovered personal data linked to the data subject that can be downloaded as a PDF for manual review or securely retrieved via Sentra’s API.

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Establishing a DSAR Processing Pipeline
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Large organizations that receive a high volume of DSAR (Data Subject Access Request) submissions typically implement a robust, end-to-end DSAR processing pipeline. This pipeline is often initiated through a self-service privacy portal, allowing individuals to easily submit requests for access or deletion of their personal data. Once a request is received, an automated or semi-automated workflow is triggered to handle the request efficiently and in compliance with regulatory timelines.

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1. Requester Identity Verification: Confirm the identity of the data subject to prevent unauthorized access (e.g., via email confirmation or secure login).
   
   
2. Mapping Identifiers: Collect and map all known identifiers for the individual across systems (e.g., email, user ID, customer number).
   
   
3. Environment-Wide Data Discovery (via Sentra): Use Sentra to search all relevant environments — cloud, SaaS, on-prem — for personal data tied to the individual. By using Sentra’s automated discovery and classification, Sentra can automatically identify where to search for.
   
   
4. DSAR Report Generation (via Sentra): Compile a detailed report listing all personal data found and where it resides.
   
   
5. Data Deletion & Verification: Remove or anonymize personal data as required, then rerun a search to verify deletion is complete.
   
   
6. Final Response to Requester: Send a confirmation to the requester, outlining the actions taken and closing the request.

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Sentra plays a key role in the DSAR pipeline by exposing a powerful API that enables automated, organization-wide searches for personal data. The search results can be programmatically used to trigger downstream actions like data deletion. After removal, the API can initiate a follow-up scan to verify that all data has been successfully deleted.

Benefits of DSAR Automation 

With privacy regulations constantly growing, and DSAR volumes continuing to rise, building an automated, scalable pipeline is no longer a luxury - it’s a necessity.

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• Automated and Cost-Efficient: Replaces costly, error-prone manual processes with a streamlined, automated approach.
  
• High-Speed, High-Accuracy: Sentra leverages its knowledge of where PII resides to perform targeted searches across all environments and data types, delivering comprehensive reports in hours—not days.
  
• Seamless Integration: A powerful API allows integration with workflow systems, enabling a fully automated, end-to-end DSAR experience for end users.

By using Sentra to intelligently locate PII across all environments, organizations can eliminate manual bottlenecks and accelerate response times. Sentra’s powerful API and deep data awareness make it possible to automate every step of the DSAR journey - from discovery to deletion - enabling privacy teams to operate at scale, reduce costs, and maintain compliance with confidence. 

Turning DSAR Compliance into a Scalable Advantage

As privacy expectations grow and regulatory pressure intensifies, DSARs are no longer just a checkbox. They are a reflection of how seriously an organization takes user trust. Manual, reactive processes simply can’t keep up with the scale and complexity of modern data environments.

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By automating DSAR workflows with tools like Sentra, organizations can achieve faster response times, lower operational costs, and sustained compliance - while freeing up teams to focus on higher-value privacy initiatives.

Recently there has been a significant shift from standalone Data Security Posture Management (DSPM) solutions to comprehensive Data Security Platforms (DSPs). These platforms integrate DSPM functionality, but also encompass access governance, threat detection, and data loss prevention capabilities to provide a more holistic data protection solution. Additionally, the critical role of data in AI and LLM training requires holistic data security platforms that can manage data sensitivity, ensure security and compliance, and maintain data integrity.

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This consolidation will improve security effectiveness and help organizations manage the growing complexity of their IT environments. Originally more of a governance/compliance tool, DSPs have evolved into a critical necessity for organizations managing sensitive data in sprawling cloud environments. With the explosion of cloud adoption, stricter regulatory landscapes, and the increasing sophistication of cyber threats, DSPs will continue to evolve to address the monumental data scale expected.

DSP Addressing Modern Challenges in 2025

As the threat landscape evolves, DSP is shifting to address modern challenges. New trends such as AI integration, real-time threat detection, and cloud-native architectures are transforming how organizations approach data security. DSPM is no longer just about assuring compliance and proper data governance, it’s about mitigating all data risks, monitoring for new threats, and proactively resolving them in real time.

Must-Have DSP Features for 2025

Over the years, Data Security Platforms (DSPs) have evolved significantly, with a range of providers emerging to address the growing need for robust data security in cloud environments. Initially, smaller startups began offering innovative solutions, and in 2024, several of these providers were acquired, signaling the increasing demand for comprehensive data protection. As organizations continue to prioritize securing their cloud data, it's essential to carefully evaluate DSP solutions to ensure they meet key security needs. When assessing DSP options for 2025, certain features stand out as critical for ensuring a comprehensive and effective approach to data security.

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Below are outlined the must-have features for any DSP solution in the coming year:

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1. Cloud-Native Architecture

Modern DSPs are built for the cloud and address vast data scale with cloud-native technologies that leverage provider APIs and functions. This allows data discovery and classification to occur autonomously, within the customer cloud environment leveraging existing compute resources. Agentless approaches reduce administrative burdens as well.
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2. AI-Based Classification

AI has revolutionized data classification, providing context-aware accuracy exceeding 95%. By understanding data in its unique context, AI-driven DSP solutions ensure the right security measures are applied without overburdening teams with false positives.
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3. Anomaly Detection and Real-Time Threat Detection

Anomaly detection, powered by Data Detection and Response (DDR), identifies unusual patterns in data usage to spotlight risks such as ransomware and insider threats. Combined with real-time, data-aware detection of suspicious activities, modern DSP solutions proactively address cloud-native vulnerabilities, stopping breaches before they unfold and ensuring swift, effective action.
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4. Automatic Labeling

Manual tagging is too cumbersome and time consuming. When choosing DSP solutions, it’s critical to make sure that you choose ones that automate data tagging and labeling, seamlessly integrating with Data Loss Prevention (DLP), Secure Access Service Edge (SASE), and governance platforms. This reduces errors and accelerates compliance processes.
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5. Data Zones and Perimeters

As data moves across cloud environments, maintaining control is paramount. Leading DSP solutions monitor data movement, alerting teams when data crosses predefined perimeters or storage zones, ensuring compliance with internal and external policies.
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6. Automatic Remediation and Enforcement

Automation extends to remediation, with DSPs swiftly addressing data risks like excessive permissions or misconfigurations. By enforcing protection policies across cloud environments, organizations can prevent breaches before they occur.

The Business Case for DSP in 2025

Proactive Security

Cloud-native DSP represents a shift from reactive to proactive security practices. By identifying and addressing risks early, and across their entire data estate from cloud to on-premises, organizations can mitigate potential threats and strengthen their security posture.
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Regulatory Compliance

As regulations such as GDPR and CCPA continue to evolve, DSPM solutions play a crucial role in simplifying compliance by automating data discovery and labeling. This automation reduces the manual effort required to meet regulatory requirements. In fact, 84% of security and IT professionals consider data protection frameworks like GDPR and CCPA to be mandatory for their industries, emphasizing the growing need for automated solutions to ensure compliance.
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The Rise of Gen AI

The rise of Gen AI is expected to be a main theme in 2025. Gen AI is a driver for data proliferation in the cloud and for a transition between legacy data technologies and modern ones that require an updated data security program.
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Operational Efficiency

By automating repetitive tasks, DSPM significantly reduces the workload for security teams. This efficiency allows teams to focus on strategic initiatives rather than firefighting. According to a 2024 survey, organizations using DSPM reported a 40% reduction in time spent on manual data management tasks, demonstrating its impact on operational productivity.

Future-Proofing Your Organization with Cloud-Native DSP

To thrive in the evolving security landscape, organizations must adopt forward-looking strategies. Cloud-native DSP tools integrate seamlessly with broader security frameworks, ensuring resilience and adaptability. As technology advances, features like predictive analytics and deeper AI integration will further enhance capabilities.

Conclusion

Data security challenges are only becoming more complex, but new Data Security Platforms (DSPs) provide the tools to meet them head-on. Now is the time for organizations to take a hard look at their security posture and consider how DSPs can help them stay protected, compliant, and trusted. DSPs are quickly becoming essential to business operations, influencing strategic decisions and enabling faster, more secure innovation.
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Ready to see it in action?
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Request a demo to discover how a modern DSP can strengthen your security and support your goals.