Unifying Multi-Cloud Data Security with Sentra: How Valenz Health Scaled PHI Protection Post-Merger
The Challenge: Post-Merger Complexity Meets Cloud-Scale Risk
The merger of two healthcare entities brought together diverse teams, tools, and data security requirements. While both organizations were focused on strong privacy, security, and compliance, post-merger they sought an efficient way to centralize data security management across multiple cloud platforms and SaaS applications.
"Our merger brought together two companies with IT Infrastructure and Security teams, each with a large amount of data that everyone was now interested in understanding and securing. Sentra allowed us to quickly scan and analyze all of our cloud and SaaS data resources and present them in a single platform that each team could easily view and ingest as needed ."
— Kerry Knopp, VP, Cloud Operations, Valenz Health
Why Sentra: Unified, Automated, and Built for Healthcare
The healthcare provider selected Sentra’s Data Security Posture Management (DSPM) platform to unify and automate data security. Sentra was chosen because it delivers:
- Healthcare-aware classification to accurately identify and protect PHI
- Unified visibility across multiple cloud providers and SaaS applications
- Policy-based controls to enforce consistent governance and compliance
- Policy-based controls to enforce consistent governance and compliance
- Easy analysis of post-merger data with a unified view
Sentra’s ability to normalize security controls across disparate cloud systems, and its rapid integration with AI and data analytics platform, made it the clear choice.
Turning Insight Into Action
Deployment was fast and non-disruptive. The organization also extended Sentra’s protections to its content collaboration platforms and integrated security policies with its broader data analytics tools - ensuring consistent, HIPAA-aligned governance across the enterprise.
Real Business Impact: Compliance, Clarity, and Confidence
By partnering with Sentra, Valenz Health transformed data security into proactive AI-powered governance at scale to secure data without overburdening security teams.
More relevant Case Studies
How a Consumer App Company Secured Over 130 Petabytes in Weeks
How a Consumer App Company Secured Over 130 Petabytes in Weeks
A global Consumer App company manages vast, complex cloud environments spanning multiple continents and hundreds of petabytes of sensitive customer and operational data. But their legacy data classification tools were not designed for the massive scale and speed of their cloud data, especially when it came to identifying sensitive information buried deep in complex file formats like JSON and Parquet.
Faced with multiple, complex compliance requirements and ballooning data security costs, the company turned to Sentra.
By adopting Sentra’s AI-powered Data Security Posture Management (DSPM) platform, they accelerated and scaled their data security strategy, achieving 98% classification accuracy and full visibility across cloud-scale infrastructure, and enabling faster compliance - all while reducing operational overhead and cutting cloud costs.
The Challenge: Massive Data, Complex Formats, and Untenable Costs
The data security team’s existing classification tools were never built for the scale and complexity of a data estate over 130 petabytes. As regulatory requirements increased, and data structures became more nested and dynamic, manual tagging and legacy solutions became expensive, inaccurate, and unsustainable.
The team also faced an immense data security challenge: how to accurately classify sensitive information across an enormous cloud environment, while keeping operational costs in check. Their existing legacy tools lacked the precision and scalability to handle complex, nested file formats like JSON and Parquet, which are common in modern data engineering pipelines. Manual tagging was not only time-consuming but also inaccurate, resulting in low coverage and high compliance risk. With regulatory deadlines rapidly approaching, the security team needed a way to gain complete visibility into sensitive data, improve classification accuracy, and implement a scalable architecture that wouldn’t break the budget.
"Our previous solutions simply couldn't keep pace with the sheer volume and complexity of our cloud data. We needed a robust, cloud-native approach that was both effective and economically sound across our entire digital footprint."
— Deputy CISO
After evaluating multiple vendors, the company selected Sentra for its unique combination of deep technical sophistication and practical efficiency.
What stood out:
AI-Driven Classification at Scale: Sentra’s multi-model architecture, including GLiNER for Named Entity Recognition and embedding-based contextual detection, enabled granular, column-level classification, even inside deeply nested Parquet structures.
Cost-Efficient Ephemeral Scanning: Unlike always-on tools, Sentra’s ephemeral EC2 architecture scales to zero when not scanning. Combined with S3 inventory-based change detection and AI- driven smart sampling, it enables fast classification across hundreds of petabytes, at a fraction of the time and cost, and without impacting performance.
Seamless Terraform Deployment: Rapid deployment via infrastructure-as-code made it easy to scale Sentra across multiple environments while enforcing least-privilege access through dual-role AWS authentication.
Why Sentra: Accuracy and Efficiency at Cloud-Native Scale
"Sentra accurately uncovered mislabeled sensitive customer data, enabling rapid validation and remediation. It is now an indispensable element of our data protection strategy allowing us to stay compliant and keep our data protection promise to millions of customers around the world."
— Deputy CISO
Sentra was deployed and delivering results in the customer’s environment in just 12 days. During the initial proof of concept, the data security team was able to select where they wanted scanning to begin and easily configure the platform, allowing the solution to scan 1 terabyte of high-risk data across complex file formats to achieve over 98% classification accuracy. Sentra’s smart sampling approach prioritized the most sensitive and high-impact datasets, optimizing performance without sacrificing precision. The platform was deployed seamlessly using Terraform, integrating directly into the customer’s existing AWS architecture. A secure two-role access model, one for metadata access and another for scanning, ensured strict least-privilege control throughout the process.
Following the successful POC, the security team decided to continue scaling Sentra’s coverage across their vast data estate to cover hundreds of petabytes. The data security team was able to easily roll out Sentra according to their data priorities and leverage automation to minimize manual effort and dramatically accelerate risk remediation.
Protect Your Secret Sauce: Safeguard Critical IP in the Cloud
Protect Your Secret Sauce: Safeguard Critical IP in the Cloud
The Risk: Leveraging IP Creates Exposure
For manufacturers, intellectual property is everything. Formulas, patents, designs, and recipes are the secret sauce that fuel competitiveness. This critical data must flow through R&D teams, testing labs, and production lines to keep the business moving and thriving.
But in the cloud, this same accessibility that fuels innovation becomes a liability. Blueprints get duplicated in public OneDrives, recipes are stored in shared folders, and patents are over-permissioned to contractors or partners. A single accidental exposure can mean stolen IP, lost contracts, and potentially catastrophic business, financial, or reputational damage.
Security leaders need an accurate, efficient way to know exactly where intellectual property lives across their entire environment, who has access, and when and where it is copied or moved.
How Sentra Helps Security Teams Protect Critical IP
Sentra is built to transform how enterprises safeguard the data that matters most, at the speed and scale of modern cloud enterprises. The AI-powered platform automatically and continuously discovers, classifies, and protects both proprietary intellectual property and regulated customer data across multi-cloud and on-premises environments.
- Automatically discovers and classifies critical data, finding intellectual property everywhere it lives, including patents, designs, CAD files, formulas, communications, images, audio, and video files.
- Alerts about over-exposed IP to enforce least-privilege access so only the right teams and partners can access sensitive files.
- Automatically apply DLP labels for consistent controls across Microsoft 365 Purview, Google Drive, and AWS resource tagging.
- Continuously monitor in real time when files containing IP are overshared or moved and
automatically detect similar sensitive data. - Securely adopt AI while preventing privacy and compliance violations and sensitive corporate data
leakage. - Reduce risk at scale with agentless scanning that avoids outages, API throttling, or compute spikes.
With Sentra, organizations can embrace cloud and AI with confidence; securing their most valuable IP assets without slowing down innovation or production.
Why Security Teams Choose Sentra to Stop Insider Threats Faster
- Detect and mitigate insider-driven data loss in real-time
- Block risky sharing and apply encryption in SaaS tools like Google Drive and Microsoft 365
- Gain continuous visibility across multi-cloud and SaaS with a cloud-native architecture
- Automate least-privilege access control for unstructured and sensitive data
- Prioritize threats using context-aware insights from identity, behavior, and sensitivity
- Enhance DLP tools like MicrosoftPurview to extend coverage and control
How an Aerospace Firm Secured Proprietary Designs
An aerospace manufacturer used Sentra to discover, classify and remediate exposure risk to proprietary data such as; patents, algorithms, and CAD designs across Microsoft 365 and Google Workspace. Sentra quickly discovered duplicate blueprints in employee OneDrives and flagged overshared design files that could have leaked via collaboration. They also used Sentra to enforce their policy of masking all data stored on Snowflake by accurately identifying data as masked or unmasked. Finally, they created a ticketing workflow to automate and streamline remediation of urgent issues. The company cut exposed IP by over 80% in the first month. Deploying Sentra was simple and the scan quickly found exposed proprietary data, IP, and other critical data that if compromised or exfiltrated could cause catastrophic business, financial, or reputational damage.
