Data Security Platform for Enterprise Cloud, Hybrid, and On-Prem Environments
Sensitive data is moving faster than most security teams can track: across cloud platforms, SaaS apps, databases, files, analytics tools, legacy systems, and AI workflows. DataStealth gives you one platform to find sensitive data everywhere, protect it at the field level, and enforce access policies in real time.
See DataStealth in ActionCore Functionality
Data Discovery
Find data sources that contain sensitive information across on-premise, cloud, SaaS apps, legacy environments, and AI.
Learn more →02Data Classification
Automatically classify sensitive data in every application, database, file share, or anywhere else it exists.
Learn more →03Data Protection
Protect sensitive data using tokenization, encryption, and masking to safeguard your data without disrupting applications or workflows.
Learn more →Don't Just Find Data Risk. Shrink and Eliminate It.
Move to fully controlling your data by combining discovery, classification, data-layer protection, and real-time enforcement.
Locate sensitive information across cloud accounts, SaaS, and legacy/on-prem data stores, then reduce exposure with policy-driven remediation. Improve security posture across distributed cloud environments without slowing delivery.
Identify over-permissioned access and enforce least-privilege policies to reduce insider and accidental exposure. Centralize access control decisions around what data is accessed, by whom, and why.
When an event happens, move from "we got an alert" to "we know what’s exposed and confirm it’s protected and unusable to the attacker."
How Our Data Security Platform Supports Data Protection
Find Sensitive Data Everywhere
See where regulated, confidential, and high-risk data lives across cloud, SaaS, on-prem, and hybrid environments.
02Shrink Exposure Before It Causes an Incident
Apply tokenization, encryption, and dynamic data masking to limit what users, apps, and systems can see.
03Stop Over-Permissioned Access
Enforce least privilege around the data itself, not just the application or network layer.
04Reduce Risk Without Disrupting Workflows
Avoid the "security vs productivity" tradeoff by protecting data while keeping systems usable, so protection sticks instead of being bypassed.
05Integrate into Security Operations
Seamless integration with existing tools (SIEM/SOAR/ITSM/IdP) so alerts become actions, actions become evidence, and security teams stay in one workflow.
06Make Audits Easier
Generate evidence that sensitive data is protected, policies are enforced, and risk is being reduced.
What You'll Get
Find the Data You're Most Worried About
Discover sensitive, regulated, and business-critical data across cloud, SaaS, on-prem, and hybrid environments.
Know What Data Needs Protection First
Classify data with context so your team can prioritize the highest-risk stores, users, systems, and workflows.
Reduce Exposure Without Rewriting Apps
Apply tokenization, encryption, and masking in ways that protect data while keeping business systems usable.
Control Who Sees Sensitive Information
Enforce policies based on user, role, context, and data type, reducing reliance on broad application-level access.
Frequently Asked Questions
What is a data security platform?+−
A data security platform is a unified system that combines data discovery, classification, protection, and governance capabilities into a single solution. It replaces the traditional approach of managing separate tools for DLP, encryption, database security, and access control. The platform provides centralized visibility into where sensitive data exists across an organization’s infrastructure and applies consistent protection policies regardless of where that data resides.
How does DataStealth approach enterprise encryption and compliance?+−
DataStealth uses proxy-based tokenization and encryption to protect data across hybrid environments without application rewrites, sitting inline between applications and data stores rather than requiring code changes or agents. For PCI or HIPAA workloads, this can reduce the number of systems in compliance scope, though actual scope reduction depends on your architecture and is ultimately determined by your QSA or assessor.
How do data security platforms differ from traditional DLP solutions?+−
Traditional DLP solutions focus primarily on preventing data exfiltration by monitoring and blocking data transfers at network egress points and endpoints. Data security platforms take a broader approach: they discover where sensitive data exists, classify it based on content and context, protect it through encryption or tokenization, and govern access based on policies.
How do I evaluate data security platforms for my organization?+−
Start by mapping your data landscape: where does sensitive data exist today, and where is it flowing? Identify your compliance requirements (PCI, HIPAA, GDPR) and determine which systems need to remain in or out of scope. Evaluate platforms against coverage, architecture, and integration, then run a proof-of-concept on your highest-risk data stores.
Can data security platforms protect data in AI and machine learning workflows?+−
Yes, and this capability is increasingly critical. Modern data security platforms can identify when sensitive data is being fed into AI systems, classify prompts and training data for PII, PHI, or proprietary information, and either block the request, redact sensitive elements, or alert security teams.
What is the difference between DSPM and a data security platform?+−
Data Security Posture Management (DSPM) is a subset of the broader data security platform category, focused on discovering data across cloud environments and identifying posture risks. A full data security platform combines DSPM capabilities with active protection mechanisms like encryption, tokenization, and real-time access controls.
What happens if DataStealth fails or becomes unreachable?+−
DataStealth fails closed. If an inline component can't reach the policy engine or vault, it blocks the traffic rather than passing it through unprotected, so a failure never results in sensitive data being exposed in the clear.
See the Platform on Your Own Data
Get a quick look at how DataStealth can work in your environment.