Sentra Launches Breakthrough AI Classification Capabilities!
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Transforming Data Security with Large Language Models (LLMs): Sentra’s Innovative Approach

September 12, 2023
5
Min Read
AI and ML

In today's data-driven world, the success of any data security program hinges on the accuracy, speed, and scalability of its data classification efforts. Why? Because not all data is created equal, and precise data classification lays the essential groundwork for security professionals to understand the context of data-related risks and vulnerabilities. Armed with this knowledge, security operations (SecOps) teams can remediate in a targeted, effective, and prioritized manner, with the ultimate aim of proactively reducing an organization's data attack surface and risk profile over time.

Sentra is excited to introduce Large Language Models (LLMs) into its classification engine. This development empowers enterprises to proactively reduce the data attack surface while accurately identifying and understanding sensitive unstructured data such as employee contracts, source code, and user-generated content at scale.

Many enterprises today grapple with a multitude of data regulations and privacy frameworks while navigating the intricate world of cloud data. Sentra's announcement of adding LLMs to its classification engine is redefining how enterprise security teams understand, manage, and secure their sensitive and proprietary data on a massive scale. Moreover, as enterprises eagerly embrace AI's potential, they must also address unauthorized access or manipulation of Language Model Models (LLMs) and remain vigilant in detecting and responding to security risks associated with AI model training. Sentra is well-equipped to guide enterprises through this multifaceted journey.

A New Era of Data Classification 

Identifying and managing unstructured data has always been a headache for organizations,  whether it's legal documents buried in email attachments, confidential source code scattered across various folders, or user-generated content strewn across collaboration platforms. Imagine a scenario where an enterprise needs to identify all instances of employee contracts within its vast data repositories. Previously, this would have involved painstaking manual searches, leading to inefficiency, potential oversight, and increased security risks.

Sentra’s LMM-powered classification engine can now comprehend the context, sentiment, and nuances of unstructured data, enabling it to classify such data with a level of accuracy and granularity that was previously unimaginable. The model can analyze the content of documents, emails, and other unstructured data sources, not only identifying employee contracts but also providing valuable insights into their context. It can understand contract clauses, expiration dates, and even flag potential compliance issues. Similarly, for source code scattered across diverse folders, Sentra can recognize programming languages, identify proprietary code, and ensure that sensitive code is adequately protected.

When it comes to user-generated content on collaboration platforms, Sentra can analyze and categorize this data, making it easier for organizations to monitor and manage user interactions, ensuring compliance with their policies and regulations. This new classification approach not only aids in understanding the business context of unstructured customer data but also aligns seamlessly with compliance standards such as GDPR, CCPA, and HIPAA. Ensuring the highest level of security, Sentra exclusively scans data with LLM-based classifiers within the enterprise's cloud premises. The assurance that the data never leaves the organization’s environment reduces an additional layer of risk.

Quantifying Risk: Prioritized Data Risk Scores 

Automated data classification capabilities provide a solid foundation for data security management practices. What’s more, data classification speed and accuracy are paramount when striving for an in-depth comprehension of sensitive data and quantifying risk. 

Sentra offers data risk scoring that considers multiple layers of data, including sensitivity scores, access permissions, user activity, data movement, and misconfigurations. This unique technology automatically scores the most critical data risks, providing security teams and executives with a clear, prioritized view of all their sensitive data at-risk, with the option to drill down deeply into the root cause of the vulnerability (often at a code level). 

Having a clear, prioritized view of high-risk data at your fingertips empowers security teams to truly understand, quantify, and prioritize data risks while directing targeted remediation efforts.

The Power of Accuracy and Efficiency

One of the most significant advantages of Sentra's LLM-powered data classification is the unprecedented accuracy it brings to the table. Inaccurate or incomplete data classification can lead to costly consequences, including data breaches, regulatory fines, and reputational damage. With LLMs, Sentra ensures that your data is classified with  precision, reducing the risk of errors and omissions. Moreover, this enhanced accuracy translates into increased efficiency. Sentra's LLM engine can process vast volumes of data in a fraction of the time it would take a human workforce. This not only saves valuable resources but also enables organizations to proactively address security and compliance challenges.

Key developments of Sentra's classification engine encompass:

  • Automatic classification of proprietary customer data with additional context to comply with regulations and privacy frameworks.
  • LLM-powered scanning of data asset content and analysis of metadata, including file names, schemas, and tags.
  • The capability for enterprises to train their LLMs and seamlessly integrate them into Sentra's classification engine for improved proprietary data classification.

We are excited about the possibilities that this advancement will unlock for our customers as we continue to innovate and redefine cloud data security. To learn more about Sentra’s LMM-powered classification engine, request a demo today.

Discover Ron’s expertise, shaped by over 20 years of hands-on tech and leadership experience in cybersecurity, cloud, big data, and machine learning. As a serial entrepreneur and seed investor, Ron has contributed to the success of several startups, including Axonius, Firefly, Guardio, Talon Cyber Security, and Lightricks, after founding a company acquired by Oracle.

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Ward Balcerzak
Ward Balcerzak
December 11, 2025
3
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US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

By 2026, American data privacy will look very different as a wave of new state laws redefines what it means to protect sensitive information. Organizations face a regulatory maze: more than 20 states will soon require not only “reasonable security” but also Data Protection Impact Assessments (DPIAs), explicit limits on data collection, and, in some cases, detailed data inventories. These requirements are quickly becoming standard, and ignoring them simply isn’t an option. The risk of penalties and enforcement actions is climbing fast.

But through all these changes, one major question remains: How can any organization comply if it doesn’t even know where its most sensitive data is? Data Security Posture Management (DSPM) has become the solution, making data visibility and automation central for meeting ongoing compliance needs.

Mapping the New Wave of State Privacy Mandates

Several state privacy laws going into effect in 2025 and 2026 are raising the stakes for compliance. Kentucky, Indiana, and Rhode Island’s new laws, effective January 1, 2026, require both security measures and DPIAs for handling high-risk or sensitive data. Minnesota’s law stands out even more: it moves past earlier vague “reasonable” security language and mandates comprehensive data inventories.

Other key states include Minnesota, which explicitly requires data inventories, Maryland with strict data minimization rules, and Tennessee, which gives organizations an affirmative defense if they’ve adopted a NIST-aligned privacy program. These requirements mean organizations now need to track what data they collect, know exactly where it’s stored, and show evidence of compliance when asked. If your organization operates in more than one state, keeping up with this web of laws will soon become impossible without dedicated solutions (US consumer privacy laws 2025 update).

Why Data Visibility is Now Foundational to Compliance

To meet DPIA, minimization, and security safeguard rules, you need full visibility into where sensitive or regulated data lives - and how it moves across your environment. Recent privacy laws are moving closer to GDPR-like standards, with DPIAs required not only for biometric data but also for broad categories like targeted advertising and profiling. Minnesota leads with its clear requirement for full data inventories, setting the standard that you can’t prove compliance unless you understand your data (US cybersecurity and data privacy review and outlook 2025).

This shift puts DSPM front and center: you now need ongoing discovery and classification of your entire sensitive data footprint. Without a strong data foundation, organizations will find it hard to complete DPIAs, handle audits, or defend themselves in investigations.

Automation: The Only Viable Path for Assessment and Audit Readiness

State privacy rules are getting more complicated, and many enforcement authorities are shortening or removing 'right-to-cure' periods. That means manual compliance simply won’t keep up. Automation is now the only way to manage compliance as regulations tighten (5 trends to watch: 2025 US data privacy & cybersecurity).

With DSPM and automation, organizations get ongoing discovery, real-time data classification, and instant evidence collection - all required for fast DPIAs and responsive audits. For companies facing regulators or preparing for multi-state oversight, this means you already have the proof and documentation you need. Relying on spreadsheets or one-time assessments at this point only increases your risk.

Sentra: Your Strategic Bridge to Privacy Law Compliance

Sentra’s DSPM platform is built to tackle these expanding privacy law requirements. The agentless platform covers AWS, Azure, GCP, SaaS, and hybrid environments, removing both visibility gaps and the hassle found in older solutions (Sentra: DSPM for compliance use cases).

With continuous, automated discovery and data classification, you always know exactly where your sensitive data is, how it moves, and how it’s being protected. Sentra’s integrated Data Detection & Response (DDR) catches and fixes risks or policy violations early, closing gaps before regulators - or attackers - can take advantage (Sensitive data exposure insight). Combined with clear reporting and on-demand audit documentation, Sentra helps you meet new state privacy laws and stay audit-ready, even as your business or data needs change.

Conclusion

The arrival of new state privacy laws in 2025 and 2026 is changing how organizations must handle sensitive data. Security safeguards, DPIAs, minimization, and full inventories are now required - not just nice-to-have.

DSPM is now a compliance must-have. Without complete data visibility and automation, following the web of state rules isn’t difficult - it’s impossible. Sentra’s agentless, multi-cloud platform keeps your organization continuously informed, giving compliance, security, and privacy teams the control they need to keep up with new regulations.

Want to see how your organization stacks up for 2026 laws? Book a DSPM Compliance Readiness Assessment or check out Sentra’s automated DPIA tools today.

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David Stuart
David Stuart
Gilad Golani
Gilad Golani
December 4, 2025
3
Min Read

Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Cloud adoption and the explosion of data have boosted business agility, but they’ve also created new headaches for security teams. As companies move sensitive information into multi-cloud and hybrid environments, old security models start to break down. Shuffling data for scanning and classification adds risk, piles on regulatory complexity, and drives up operational costs.

Zero Data Movement (ZDM) offers a new architectural approach, reshaping how advanced Data Security Posture Management (DSPM) platforms provide visibility, protection, and compliance. This post breaks down what makes ZDM unique, why it matters for security-focused enterprises, and how Sentra provides an innovative agentless and scalable design that is genuinely a zero data movement DSPM .

Defining Zero Data Movement Architecture

Zero Data Movement (ZDM) sets a new standard in data security. The premise is straightforward: sensitive data should stay in its original environment for security analysis, monitoring, and enforcement. Older models require copying, exporting, or centralizing data to scan it, while ZDM ensures that all security actions happen directly where data resides.

ZDM removes egress risk -shrinking the attack surface and reducing regulatory issues. For organizations juggling large cloud deployments and tight data residency rules, ZDM isn’t just an improvement - it's essential. Groups like the Cloud Security Alliance and new privacy regulations are moving the industry toward designs that build in privacy and non-stop protection.

Risks of Data Movement: Compliance, Cost, and Egress Exposure

Every time data is copied, exported, or streamed out of its native environment, new risks arise. Data movement creates challenges such as:

  • Egress risk: Data at rest or in transit outside its original environment  increases risk of breach, especially as those environments may be less secure.
  • Compliance and regulatory exposure: Moving data across borders or different clouds can break geo-fencing and privacy controls, leading to potential violations and steep fines.
  • Loss of context and control: Scattered data makes it harder to monitor everything, leaving gaps in visibility.
  • Rising total cost of ownership (TCO): Scanning and classification can incur heavy cloud compute costs - so efficiency matters.  Exporting or storing data, especially shadow data, drives up storage, egress, and compliance costs as well.

As more businesses rely on data, moving it unnecessarily only increases the risk - especially with fast-changing cloud regulations.

Legacy and Competitor Gaps: Why Data Movement Still Happens

Not every security vendor practices true zero data movement, and the differences are notable. Products from Cyera, Securiti, or older platforms still require temporary data exporting or duplication for analysis. This might offer a quick setup, but it exposes users to egress risks, insider threats, and compliance gaps - problems that are worse in regulated fields.

Competitors like Cyera often rely on shortcuts that fall short of ZDM’s requirements. Securiti and similar providers depend on connectors, API snapshots, or central data lakes, each adding potential risks and spreading data further than necessary. With ZDM, security operations like monitoring and classification happen entirely locally, removing the need to trust external storage or aggregation. For more detail on how data movement drives up risk.

The Business Value of Zero Data Movement DSPM

Zero data movement DSPM changes the equation for businesses:

  • Designed for compliance: Data remains within controlled environments, shrinking audit requirements and reducing breach likelihood.
  • Lower TCO and better efficiency: Eliminates hidden expenses from extra storage, duplicate assets, and exporting to external platforms.
  • Regulatory clarity and privacy: Supports data sovereignty, cross-border rules, and new zero trust frameworks with an egress-free approach.

Sentra’s agentless, cloud-native DSPM provides these benefits by ensuring sensitive data is never moved or copied. And Sentra delivers these benefits at scale - across multi-petabyte enterprise environments - without the performance and cost tradeoffs others suffer from. Real scenarios show the results: financial firms keep audit trails without data ever leaving allowed regions. Healthcare providers safeguard PHI at its source. Global SaaS companies secure customer data at scale, cost-effectively while meeting regional rules.

Future-Proofing Data Security: ZDM as the New Standard

With data volumes expected to hit 181 zettabytes in 2025, older protection methods that rely on moving data can’t keep up. Zero data movement architecture meets today's security demands and supports zero trust, metadata-driven access, and privacy-first strategies for the future.

Companies wanting to avoid dead ends should pick solutions that offer unified discovery, classification and policy enforcement without egress risk. Sentra’s ZDM architecture makes this possible, allowing organizations to analyze and protect information where it lives, at cloud speed and scale.

Conclusion

Zero Data Movement is more than a technical detail - it's a new architectural standard for any organization serious about risk control, compliance, and efficiency. As data grows and regulations become stricter, the old habits of moving, copying, or centralizing sensitive data will no longer suffice.

Sentra stands out by delivering a zero data movement DSPMplatform that's agentless, real-time, and truly multicloud. For security leaders determined to cut egress risk, lower compliance spending, and get ahead in privacy, ZDM is the clear path forward.

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Charles Garlow
Charles Garlow
December 3, 2025
3
Min Read

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

As organizations scramble to secure their sprawling cloud environments and deploy AI, many are facing a stark realization: handling petabyte-scale data is now a basic security requirement. With sensitive information multiplying across multiple clouds, SaaS, and AI-driven platforms, security leaders can't treat true data security at scale as a simple add-on or upgrade.

At the same time, speeding up digital transformation means higher and less visible operational costs for handling this data surge. Older Data Security Posture Management (DSPM) tools, especially those boasting broad, indiscriminate scans as evidence of their scale, are saddling organizations with rising cloud bills, slowdowns, and dangerous gaps in visibility. The costs of securing petabyte-scale data are now economic and technical, demanding efficiency instead of just scale. Sentra solves this with a highly-efficient cloud-native design, delivering 10x lower cloud compute costs.

Why Petabyte Scale is a Security Requirement

Data environments have exploded in both size and complexity. For Fortune 500 companies, fast-growing SaaS providers, and global organizations, data exists across public and hybrid clouds, business units, regions, and a stream of new applications.

Regulations such as GDPR, HIPAA, and rules from the SEC now demand current data inventories and continuous proof of risk management. In this environment, defending data at the petabyte level is now essential. Failing to classify and monitor this data efficiently means risking compliance and losing business trust. Security teams are feeling the strain. I meet security teams everyday and too many of them still struggle with data visibility and are already seeing the cracks forming in their current toolset as data scales.

The Hidden Cost of Inefficient DSPM: API Calls and Egress Bills

How DSPM tools perform scanning and discovery drives the real costs of securing petabyte-scale data. Some vendors highlight their capacity to scan multiple petabytes daily. But here's the reality: scanning everything, record by record, relying on huge numbers of API calls, becomes very expensive as your data estate grows.

Every API call can rack up costs, and all the resulting data egress and compute add up too. Large organizations might spend tens of thousands of dollars each month just to track what’s in their cloud. Even worse, older "full scan" DSPM strategies jam up operations with throttling, delays, and a flood of alerts that bury real risk. These legacy approaches simply don’t scale, and organizations relying on them end up paying more while knowing less.

 

Cyera’s "Petabyte Scale" Claims: At What Cloud Cost?

Cyera promotes its tool as an AI-native, agentless DSPM that can scan as much as 2 petabytes daily . While that’s an impressive technical achievement, the strategy of scanning everything leads directly to massive cloud infrastructure costs: frequent API hits, heavy egress, and big bills from AWS, Azure, and GCP.

At scale, these charges don’t just appear on invoices, they can actually stop adoption and limit security’s effectiveness. Cloud operations teams face API throttling, slow results, and a surge in remediation tickets as risks go unfiltered. In these fast-paced environments, recognizing the difference between a real threat and harmless data comes down to speed. The Bedrock Security blog points out how inefficient setups buckle under this weight, leaving teams stuck with lagging visibility and more operational headaches.

Sentra’s 10x Efficiency: Optimized Scanning for Real-World Scale

Sentra takes another route to manage the costs of securing petabyte-scale data. By combining agentless discovery with scanning guided by context and metadata, Sentra uses pattern recognition and an AI-driven clustering algorithm designed to detect machine-generated content—such as log files, invoices, and similar data types. By intelligently sampling data within each cluster, Sentra delivers efficient scanning while reducing scanning costs.

This approach enables data scanning to be prioritized based on risk and business value, rather than wasting time and money scanning the same data over and over again, skipping unnecessary API calls, lowering egress, and keeping cloud bills in check.

Large organizations gain a 10x efficiency edge: quicker classification of data, instant visibility into actual threats, lower operational expenses, and less demand on the network. By focusing attention only where it matters, Sentra matches data security posture management to the demands of current cloud growth and regulatory requirements.

This makes it possible for organizations to hit regulatory and audit targets without watching expenses spiral or opening up security gaps.Sentra offers multiple sampling levels, Quick (default), Moderate, Thorough, and Full, allowing customers to tailor their scanning strategy to balance cost and accuracy. For example, a highly regulated environment can be configured for a full scan, while less-regulated environments can use more efficient sampling. Petabyte-scale security gives the user complete control of their data enterprise and turns into something operationally and financially sustainable, rather than a technical milestone with a hidden cost. 

Efficiency is Non-Negotiable

Fortune 500 companies and digital-first organizations can’t treat efficiency as optional. Inefficient DSPM tools pile on costs, drain resources, and let vulnerabilities slip through, turning their security posture into a liability once scale becomes a factor. Sentra’s platform shows that efficiency is security: with targeted scanning, real context, and unified detection and response, organizations gain clarity and compliance while holding down expenses.

Don’t let your data protection approach crumble under petabyte-scale pressure. See what Sentra can do, reduce costs, and keep essential data secure - before you end up responding to breaches or audit failures.

Conclusion

Securing data at the petabyte level isn't some future aspiration - it's the standard for enterprises right now. Treating it as a secondary feature isn’t just shortsighted; it puts your company at risk, financially and operationally.

The right DSPM architecture brings efficiency, not just raw scale. Sentra delivers real-time, context-rich security posture with far greater efficiency, so your protection and your cloud spending can keep up with your growing business. Security needs to grow along with scale. Rising costs and new risks shouldn’t grow right alongside it.

Want to see how your current petabyte security posture compares? Schedule a demo and see Sentra’s efficiency for yourself.

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