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Securing Your Microsoft 365 Environment with Sentra

May 6, 2024
3
Min Read
Data Security

Picture this scenario: a senior employee at your organization has access to a restricted folder in SharePoint that contains sensitive data. Another employee needs access to a specific document in the folder and asks the senior employee for help. To save time, the senior employee simply copies the entire document and drops it into a folder with less stringent access controls so the other employee can easily access it. Because of this action taken by the senior employee, which only took seconds to complete, there’s now a copy of sensitive data — outside a secure folder and unknown to the data security team. 

The Sentra team hears repeatedly that Microsoft 365 services, like SharePoint, are a pressing concern for data security teams because this type of data proliferation is so common. While Microsoft services like OneDrive, SharePoint, Office Online, and Teams drive productivity and collaboration, they also pose a unique challenge for data security teams: identifying and securing the constantly changing data landscape without inhibiting collaboration or slowing down innovation. 

Today’s hybrid environments — including Microsoft 365 services — present many new security challenges. Teams must deal with vast and dynamic data within SharePoint, coupled with explosive cloud growth and data movement between environments (cloud to on prem or vice versa). They must also find ways to find and secure the unstructured sensitive data stored within Microsoft 365 services.

Legacy, connector- and agent-based solutions can’t fit the bill — they face performance and scaling constraints and are an administrative nightmare for teams trying to keep pace. Instead, teams need a data security solution that can automatically comprehend unstructured data in several formats and is more responsive and reliable than legacy tools. 

A cloud-native approach is one viable, scalable solution to address the multitude of security challenges that complex, modern environments create. It provides versatile, agile protection for the multi-cloud, hybrid, SaaS (i.e., Microsoft), and on-prem environments that comprise a business’s operations. 

The Challenge of Protecting Your Microsoft 365 Environment

When employees use Microsoft 365, they can copy, move, or delete data instantly, making it challenging to keep track of where sensitive data resides and who has access to it. For instance, sensitive data can easily be stored improperly or left behind in a OneDrive after an employee leaves an organization. This is commonplace when using Teams and/or SharePoint for document collaborations. This misplaced sensitive data can become ammunition for an insider threat, such as a disgruntled employee who wants to cause company damage.

Assets contain plain text credit card numbers

Defending your Microsoft 365 environment against these risks can be difficult because Microsoft 365 stores data, such as Teams messages or OneDrive documents, in a free-form layout. It’s far more challenging to classify this unstructured data than it is to classify structured data because it doesn’t follow a clear schema and formatting protocol. For instance, in a structured database, sensitive information like names and birthdates would be stored in neighboring columns labeled “names” and “birthdates.” However, in an unstructured data environment like Microsoft 365, someone might share their birthdate or other PII in a quick Teams message to an HR staff member, which is then stored in SharePoint behind the scenes. 

In addition, unstructured data lacks context. Some data is only considered sensitive under certain conditions. For example, 9-digit passport numbers alone wouldn’t pose a significant risk if exposed, while a combination of passport numbers and the identity of the passport holders would. Structured databases make it easy to see these relationships, as they likely contain column titles (e.g., “passport number,” “passport holder name”) or other clear schemas. Unstructured file repositories, on the other hand, might have all of this information buried in documents with a free-form block of text, making it especially difficult for teams to understand the context of each data asset fully.

Protection Measures to Address Microsoft 365 Data Risks

Today’s businesses must get ahead of these challenges by instituting best practices such as least privilege access, or else face consequences such as violating compliance regulations or putting sensitive data at risk of exposure

Since sensitive data is far more nuanced and complex to discern in Microsoft 365, businesses need a cloud-native solution that identifies the subtle signs associated with sensitive data in unstructured cloud environments and takes appropriate action to protect it. 

Sentra’s Integration with Microsoft 365

Sentra’s data security posture management (DSPM) platform enables secure collaboration and file sharing across services such as SharePoint, OneDrive, Teams, OneNote, and Office Online.

Its new integration with Microsoft 365 offers unmatched discovery and classification capabilities for security, data owners and risk management teams to secure data — not stopping activity but allowing it to happen securely. Here are a few of the features we offer teams using Microsoft 365: 

Advanced ML/AI analysis for accurate data discovery.

Sentra’s data security platform can autonomously discover data across your entire environment, including shadow data (i.e., misplaced, abandoned, or unknown data) or migrated data (data that may have sprawled to a lesser protected environment). It can then accurately rank data sensitivity levels by conducting in-depth analysis based on nuanced contextual information such as metadata, location, neighboring assets, and file path.

Sensitive data that is stored on-premise was found in a cloud environment

This contextual approach differs from traditional security methods, which rely on very prescriptive data formats and overlook unstructured data that doesn’t fit into these formats. Sentra’s high level of accuracy minimizes the number of false positives, requiring less hands-on validation from your team.

Use case scenario: An employee has set up their company OneDrive account to be directly accessible through their personal computer’s central file system. While working on personal tasks on their computer, this employee accidentally saves their child’s medical paperwork inside the company OneDrive rather than a personal file. To prevent this situation, Sentra can discover and notify the appropriate users if PII is residing in a OneDrive business account and violating company policy.

Precise data classification to support remediation. 

After discovering sensitive data, Sentra classifies the data using data context classes. This granular classification level provides rich usage context and enables teams to perform better risk prioritization, sensitivity analysis, and control actioning. Its data context classes can identify very specific types of data: configuration, log, tabular, image, etc. By labeling their resources with this level of precision and context, businesses can better understand usage and which files are more likely to contain sensitive information and which are not. 

In addition, Sentra consolidates classified data security findings from across your entire data estate into a single platform. This includes insights from multiple cloud environments, SaaS platforms, and on-premises data stores. Sentra offers a centralized, always-up-to-date data catalog and visualizations of data movement between environments.

Use case scenario: An employee requests access to a SharePoint folder containing a nonsensitive document. A senior employee authorizes access without realizing that sensitive documents are also stored within this folder. To prevent this type of excessive privileged access, Sentra labels sensitive documents, emails, and other Microsoft file formats so your team can enforce access policies and take the correct actions to secure these assets. 

Guardrails to enforce data hygiene across your environment.

Sentra also enforces data hygiene best practices across your Microsoft 365. environment, proactively preventing staff from taking risky actions or going against company policies.

For instance, it can determine excessive access permission and alert on these violations. Sentra can also monitor sharing permissions to enforce least privilege access on sensitive files. 

Use case scenario: During onboarding, a new junior employee is given access permissions across Microsoft 365 services. By default, they now have access to confidential intellectual property stored in SharePoint, even though they’ll never need this information in their daily work. To prevent this type of excessive access control, Sentra can enforce more stringent access controls for sensitive SharePoint folders.

Automation to accelerate incident response.

Sentra also supports automated incident response with early breach detections. It can identify data similarities to instigate an investigation of potentially risky data proliferation. In addition, it provides real-time alerting when any anomalous activity occurs within the environment and supports incident investigation and breach impact analysis with automated remediation and in-product guidance. Sentra also integrates with data catalogs and other incident response/ITSM tools to quickly alert the proper teams and kick off the right response processes. 

Use case example: An employee who was just laid off feels disgruntled with the company. They decide to go into SharePoint and start a large download of several files containing intellectual property. To protect your data from these types of internal threats, Sentra can immediately detect and alert you to suspicious activities, such as unusual activity, within your Microsoft 365 environment.

DSPM, the Key to Securing Microsoft 365

After talking with many customers and prospects facing challenges securing Microsoft 365, the Sentra team has seen the significance of a DSPM platform compatible with services like SharePoint, OneDrive, and Office Online. We prioritize bringing all data, including assets buried in your Microsoft 365 environment, into view so you can better safeguard it without slowing down innovation and collaboration. 

Dive deeper into the world of Data Security Posture Management (DSPM) and discover how it helps organizations secure their entire data estate, including cloud, on-prem, and SaaS data stores (like Microsoft 365).

To learn more about Sentra's DSPM, and how you can secure your entire data estate, visit Sentra's demo page.

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David Stuart is Senior Director of Product Marketing for Sentra, a leading cloud-native data security platform provider, where he is responsible for product and launch planning, content creation, and analyst relations. Dave is a 20+ year security industry veteran having held product and marketing management positions at industry luminary companies such as Symantec, Sourcefire, Cisco, Tenable, and ZeroFox. Dave holds a BSEE/CS from University of Illinois, and an MBA from Northwestern Kellogg Graduate School of Management.

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Ward Balcerzak
Ward Balcerzak
November 12, 2025
4
Min Read
Data Security

Best DSPM Tools: Top 9 Vendors Compared

Best DSPM Tools: Top 9 Vendors Compared

Enhanced DSPM Adoption Is the Most Important Data Security Trend of 2026

Over the past few years, organizations have realized that traditional security tools can’t keep pace with how data moves and grows today. Exploding volumes of sensitive data now flourish across multi-cloud environments, SaaS platforms, and AI systems, often without full visibility by the teams responsible for securing it. Unstructured data presents the greatest risk - representing over 80% of corporate data.

That’s why Data Security Posture Management (DSPM) has become a critical part of the modern security stack. DSPM tools help organizations automatically discover, classify, monitor, and protect sensitive data - no matter where it lives or travels.

But in 2026, the data security game is changing. Many DSPMs can tell you what your data is,  but more is needed. Leading DSPM platforms are going beyond visibility. They’re delivering real-time AI-enhanced contextual business insights, automated remediation, and AI-aware accurate protection that scales with your dynamic data.

AI-enhanced DSPM Capabilities in 2026

Not all DSPM tools are built the same. The top platforms share a few key traits that define the next generation of data security posture management:

Capability Why It Matters
Continuous discovery and classification at scale Real-time visibility into all sensitive data across cloud, SaaS, and on-prem systems. Efficiency, at petabyte scale, to allow for scanning frequency commensurate with business risk.
Contextual risk analysis Understanding what data is sensitive, who can access it, and how it’s being used. Understanding the business context around data so that appropriate actions can be taken.
Automated remediation Native capabilities and Integration with systems that correct risky configurations or excessive access automatically.
Integration and scalability Seamless connections to CSPM, SIEM, IAM, ITSM, and SOAR tools to unify data risk management and streamline workflows.
AI and model governance Capabilities to secure data used in GenAI agents, copilot assistants, and pipelines.

Top DSPM Tools to Watch in 2026

Based on recent analyst coverage, market growth, and innovation across the industry, here are the top DSPM platforms to watch this year, each contributing to how data security is evolving.

1. Sentra

As a cloud-native DSPM platform, Sentra focuses on continuous data protection, not just visibility. It discovers and accurately classifies sensitive data in real time across all cloud environments, while automatically remediating risks through policy-driven automation.

What sets Sentra apart:

  • Continuous, automated discovery and classification across your entire data estate - cloud, SaaS, and on-premises.
  • Business Contextual insights that understand the purpose of data, accurately linking data, identity, and risk.
  • Automatic learning to discern customer unique data types and continuously improve labeling over time.
  • Petabyte scaling and low compute consumption for 10X cost efficiency.
  • Automated remediation workflows and integrations to fix issues instantly.
  • Built-in coverage for data flowing through AI and SaaS ecosystems.

Ideal for: Security teams looking for a cloud-native DSPM platform built for scalability in the AI era with automation at its core.

2. BigID

A pioneer in data discovery and classification, BigID bridges DSPM and privacy governance, making it a good choice for compliance-heavy sectors.


Ideal for: Organizations prioritizing data privacy, governance, and audit readiness.

3. Prisma Cloud (Palo Alto Networks)

Prisma’s DSPM offering integrates closely with CSPM and CNAPP components, giving security teams a single pane of glass for infrastructure and data risk.


Ideal for: Enterprises with hybrid or multi-cloud infrastructures already using Palo Alto tools.

4. Microsoft Purview / Defender DSPM

Microsoft continues to invest heavily in DSPM through Purview, offering rich integration with Microsoft 365 and Azure ecosystems. Note: Sentra integrates with Microsoft Purview Information Protection (MPIP) labeling and DLP policies.

Ideal for: Microsoft-centric organizations seeking native data visibility and compliance automation.

5. Securiti.ai

Positioned as a “Data Command Center,” Securiti unifies DSPM, privacy, and governance. Its strength lies in automation and compliance visibility and SaaS coverage.


Ideal for: Enterprises looking for an all-in-one governance and DSPM solution.

6. Cyera

Cyera has gained attention for serving the SMB segment with its DSPM approach. It uses LLMs for data context, supplementing other classification methods, and provides integrations to IAM and other workflow tools.


Ideal for: Small/medium growing companies that need basic DSPM functionality.

7. Wiz

Wiz continues to lead in cloud security, having added DSPM capabilities into its CNAPP platform. They’re known for deep multi-cloud visibility and infrastructure misconfiguration detection.

Ideal for: Enterprises running complex cloud environments looking for infrastructure vulnerability and misconfiguration management.

8. Varonis

Varonis remains a strong player for hybrid and on-prem data security, with deep expertise in permissions and access analytics and focus on SaaS/unstructured data.


Ideal for: Enterprises with legacy file systems or mixed cloud/on-prem architectures.

9. Netwrix

Netwrix’s platform incorporates DSPM-related features into its auditing and access control suite.

Ideal for: Mid-sized organizations seeking DSPM as part of a broader compliance solution.

Emerging DSPM Trends to Watch in 2026

  1. AI Data Security: As enterprises adopt GenAI, DSPM tools are evolving to secure data used in training and inference.

  2. Identity-Centric Risk: Understanding and controlling both human and machine identities is now central to data posture.

  3. Automation-Driven Security: Remediation workflows are becoming the differentiator between “good” and “great.”

Market Consolidation: Expect to see CNAPP, legacy security, and cloud vendors acquiring DSPM startups to strengthen their coverage.

How to Choose the Right DSPM Tool

When evaluating a DSPM solution, align your choice with your data landscape and goals:

  • Cloud-Native Company Choose tools designed for cloud-first environments (like Sentra, Securiti, Wiz).
  • Compliance Priority Platforms like Sentra, BigID or Securiti excel in privacy and governance.
  • Microsoft-Heavy Stack Purview and Sentra DSPM offer native integration.
  • Hybrid Environment Consider Varonis, Prisma Cloud, or Sentra for extended visibility.
  • Enterprise Scalability Evaluate deployment ease, petabyte scalability, cloud resource consumption, scanning efficiency, etc. (Sentra excels here)

*Pro Tip: Run a proof of concept (POC) across multiple environments to test scalability, accuracy, and operational cost effectiveness before full deployment.

Final Thoughts: DSPM Is About Action

The best DSPM tools in 2026 share one core principle, they help organizations move from visibility to action.

At Sentra, we believe that the future of DSPM lies in continuous, automated data protection:

  • Real-time discovery of sensitive data @ scale
  • Context-aware prioritization for business insight
  • Automated remediation that reduces risk instantly

As data continues to power AI, analytics, and innovation, DSPM ensures that innovation never comes at the cost of security. See how Sentra helps leading enterprises protect data across multi-cloud and SaaS environments.

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Gilad Golani
Gilad Golani
November 6, 2025
4
Min Read

How SLMs (Small Language Models) Make Sentra’s AI Faster and More Accurate

How SLMs (Small Language Models) Make Sentra’s AI Faster and More Accurate

The LLM Hype, and What’s Missing

Over the past few years, large language models (LLMs) have dominated the AI conversation. From writing essays to generating code, LLMs like GPT-4 and Claude have proven that massive models can produce human-like language and reasoning at scale.

But here's the catch: not every task needs a 70-billion-parameter model. Parameters are computationally expensive - they require both memory and processing time.

At Sentra, we discovered early on that the work our customers rely on for accurate, scalable classification of massive data flows - isn’t about writing essays or generating text. It’s about making decisions fast, reliably, and cost-effectively across dynamic, real-world data environments. While large language models (LLMs) are excellent at solving general problems, it creates a lot of unnecessary computational overhead.

That’s why we’ve shifted our focus toward Small Language Models (SLMs) - compact, specialized models purpose-built for a single task - understanding and classifying data efficiently. By running hundreds of SLMs in parallel on regular CPUs, Sentra can deliver faster insights, stronger data privacy, and a dramatically lower total cost of AI-based classification that scales with their business, not their cloud bill.

What Is an SLM?

An SLM is a smaller, domain-specific version of a language model. Instead of trying to understand and generate any kind of text, an SLM is trained to excel at a particular task, such as identifying the topic of a document (what the document is about or what type of document it is), or detecting sensitive entities within documents, such as passwords, social security numbers, or other forms of PII.

In other words: If an LLM is a generalist, an SLM is a specialist. At Sentra, we use SLMs that are tuned and optimized for security data classification, allowing them to process high volumes of content with remarkable speed, consistency, and precision. These SLMs are based on standard open source models, but trained with data that was curated by Sentra, to achieve the level of accuracy that only Sentra can guarantee.

From LLMs to SLMs: A Strategic Evolution

Like many in the industry, we started by testing LLMs to see how well they could classify and label data. They were powerful, but also slow, expensive, and difficult to scale. Over time, it became clear: LLMs are too big and too expensive to run on customer data for Sentra to be a viable, cost effective solution for data classification.

Each SLM handles a focused part of the process: initial categorization, text extraction from documents and images, and sensitive entity classification. The SLMs are not only accurate (even more accurate than LLMs classifying using prompts) - they can run on standard CPUs efficiently, and they run inside the customer’s environment, as part of Sentra’s scanners.

The Benefits of SLMs for Customers

a. Speed and Efficiency

SLMs process data faster because they’re lean by design. They don’t waste cycles generating full sentences or reasoning across irrelevant contexts. This means real-time or near-real-time classification, even across millions of data points.

b. Accuracy and Adaptability

SLMs are pre-trained “zero-shot” language models that can categorize and classify generically, without the need to pre-train on a specific task in advance. This is the meaning of “zero shot” - it means that regardless of the data it was trained on, the model can classify an arbitrary set of entities and document labels without training on each one specifically. This is possible due to the fact that language models are very advanced, and they are able to capture deep natural language understanding at the training stage.

Regardless of that, Sentra fine tunes these models to further increase the accuracy of the classification, by curating a very large set of tagged data that resembles the type of data that our customers usually run into.

Our feedback loops ensure that model performance only gets better over time - a direct reflection of our customers’ evolving environments.

c. Cost and Sustainability

Because SLMs are compact, they require less compute power, which means lower operational costs and a smaller carbon footprint. This efficiency allows us to deliver powerful AI capabilities to customers without passing on the heavy infrastructure costs of running massive models.

d. Security and Control

Unlike LLMs hosted on external APIs, SLMs can be run within Sentra’s secure environment, preserving data privacy and regulatory compliance. Customers maintain full control over their sensitive information - a critical requirement in enterprise data security.

A Quick Comparison: SLMs vs. LLMs

The difference between SLMs and LLMs becomes clear when you look at their performance across key dimensions:

Factor SLMs LLMs
Speed Fast, optimized for classification throughput Slower and more compute-intensive for large-scale inference
Cost Cost-efficient Expensive to run at scale
Accuracy (for simple tasks) Optimized for classification Comparable but unnecessary overhead
Deployment Lightweight, easy to integrate Complex and resource-heavy
Adaptability (with feedback) Continuously fine-tuned, ability to fine tune per customer Harder to customize, fine-tuning costly
Best Use Case Classification, tagging, filtering Reasoning and analysis, generation, synthesis

Continuous Learning: How Sentra’s SLMs Grow

One of the most powerful aspects of our SLM approach is continuous learning. Each Sentra customer project contributes valuable insights, from new data patterns to evolving classification needs. These learnings feed back into our training workflows, helping us refine and expand our models over time.

While not every model retrains automatically, the system is built to support iterative optimization: as our team analyzes feedback and performance, models can be fine-tuned or extended to handle new categories and contexts.

The result is an adaptive ecosystem of SLMs that becomes more effective as our customer base and data diversity grow, ensuring Sentra’s AI remains aligned with real-world use cases.

Sentra’s Multi-SLM Architecture

Sentra’s scanning technology doesn’t rely on a single model. We run many SLMs in parallel, each specializing in a distinct layer of classification:

  1. Embedding models that convert data into meaningful vector representations
  2. Entity Classification models that label sensitive entities
  3. Document Classification models that label documents by type
  4. Image-to-text and speech-to-text models that are able to process non-textual data into textual data

This layered approach allows us to operate at scale - quickly, cheaply, and with great results. In practice, that means faster insights, fewer errors, and a more responsive platform for every customer.

The Future of AI Is Specialized

We believe the next frontier of AI isn’t about who can build the biggest model, it’s about who can build the most efficient, adaptive, and secure ones.

By embracing SLMs, Sentra is pioneering a future where AI systems are purpose-built, transparent, and sustainable. Our approach aligns with a broader industry shift toward task-optimized intelligence - models that do one thing extremely well and can learn continuously over time.

Conclusion: The Power of Small

At Sentra, we’ve learned that in AI, bigger isn’t always better. Our commitment to SLMs reflects our belief that efficiency, adaptability, and precision matter most for customers. By running thousands of small, smart models rather than a single massive one, we’re able to classify data faster, cheaper, and with greater accuracy - all while ensuring customer privacy and control.

In short: Sentra’s SLMs represent the power of small, and the future of intelligent classification.

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Aarti Gadhia
Aarti Gadhia
October 27, 2025
3
Min Read
Data Security

My Journey to Empower Women in Cybersecurity

My Journey to Empower Women in Cybersecurity

Finding My Voice: From Kenya to the Global Stage

I was born and raised in Kenya, the youngest of three and the only daughter. My parents, who never had the chance to finish their education, sacrificed everything to give me opportunities they never had. Their courage became my foundation.

At sixteen, my mother signed me up to speak at a community event, without telling me first! I stood before 500 people and spoke about something that had long bothered me: there were no women on our community board. That same year, two women were appointed for the first time in our community’s history. This year, I was given the recognition for being a Community Leader at the Global Gujrati Gaurav Awards in BC for my work in educating seniors on cyber safety and helping many immigrants secure jobs.

I didn’t realize it then, but that moment would define my purpose: to speak up for those whose voices aren’t always heard.

From Isolation to Empowerment

When I moved to the UK to study Financial Economics, I faced a different kind of challenge - isolation. My accent made me stand out, and not always in a good way. There were times I felt invisible, even rejected. But I made a promise to myself in those lonely moments that no one else should feel the same way.

Years later, as a founding member of WiCyS Western Affiliate, I helped redesign how networking happens at cybersecurity events. Instead of leaving it to chance, we introduced structured networking that ensured everyone left with at least one new connection. It was a small change, but it made a big difference. Today, that format has been adopted by organizations like ISC2 and ISACA, creating spaces where every person feels they belong. 

Breaking Barriers and Building SHE

When I pivoted into cybersecurity sales after moving to Canada, I encountered another wall. I applied for a senior role and failed a personality test, one that unfairly filtered out many talented women. I refused to accept that. I focused on listening, solving real customer challenges, and eventually became the top seller. That success helped eliminate the test altogether, opening doors for many more women who came after me. That experience planted a seed that would grow into one of my proudest initiatives: SHE (Sharing Her Empowerment).

It started as a simple fireside chat on diversity and inclusion - just 40 seats over lunch. Within minutes of sending the invite, we had 90 people signed up. Executives moved us into a larger room, and that event changed everything. SHE became our first employee resource group focused on empowering women, increasing representation in leadership, and amplifying women’s voices within the organization. Even with just 19% women, we created a ripple effect that reached the boardroom and beyond.

SHE showed me that when women stand together, transformation happens.

Creating Pathways for the Next Generation

Mentorship has always been close to my heart. During the pandemic, I met incredible women, who were trying to break into cybersecurity but kept facing barriers. I challenged hiring norms, advocated for fair opportunities, and helped launch internship programs that gave women hands-on experience. Today, many of them are thriving in their cyber careers, a true reflection of what’s possible when we lift as we climb.

Through Standout to Lead, I partnered with Women Get On Board to help women in cybersecurity gain board seats. Watching more women step into decision-making roles reminds me that leadership isn’t about titles, it’s about creating pathways for others.

Women in Cybersecurity: Our Collective Story

This year, I’m deeply honored to be named among the Top 20 Cybersecurity Women of the World by the United Cybersecurity Alliance. Their mission - to empower women, elevate diverse voices, and drive equity in our field, mirrors everything I believe in.

I’m also thrilled to be part of the upcoming documentary premiere, “The WOMEN IN SECURITY Documentary,” proudly sponsored by Sentra, Amazon WWOS, and Pinkerton among others. This film shines a light on the fearless women redefining what leadership looks like in our industry.

As a member of Sentra’s community, I see the same commitment to visibility, inclusion, and impact that has guided my journey. Together, we’re not just securing data, we’re securing the future of those who will lead next.

Asante Sana – Thank You

My story, my safari, is still being written. I’ve learned that impact doesn’t come from perfection, but from purpose. Whether it’s advocating for fairness, mentoring the next generation, or sharing our stories, every step we take matters.

To every woman, every underrepresented voice in STEM, and everyone who’s ever felt unseen - stay authentic, speak up, and don’t be afraid of the outcome. You might just change the world.

Join me and the Sentra team at The WOMEN IN SECURITY Documentary Premiere, a celebration of leadership, resilience, and the voices shaping the future of our industry.

Save your seat at The Women in Security premiere here (spots are limited).

Follow Sentra on LinkedIn and YouTube for more updates on the event and stories that inspire change.

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