Better Together – How Privaclave and DSPM Unite Visibility and Protection

Seeing is Not Securing

In cybersecurity, seeing the problem isn’t the same as solving it. Data Security Posture Management (DSPM) platforms have been a tremendous leap forward, helping enterprises discover where sensitive data lives, who has access to it, how it moves, and how much risk it carries.

But visibility alone doesn’t close the loop. For many organizations, the gap between knowing and acting remains painfully wide. Security teams are flooded with dashboards and alerts, yet the process of analyzing metadata, prioritizing risks, deploying controls, and implementing data sanitization remains largely manual and fragmented.

In that time, the data keeps moving, being shared, copied, migrated, and fed into AI pipelines. The insight is there, but the protection isn’t.

The Chasm Between Discovery and Defense

Today’s data protection stack looks like a jigsaw puzzle, with each piece important but few fitting together naturally. DSPMs uncover and surface risks. DLP tools are plugged at the edges and user endpoints, alerting or blocking traffic, and limited to few use cases, and analysts are triaging alerts with false positives, creating business disruption. Encryption & Tokenization tools provide SDKs and APIs for business teams to incorporate those into their applications and services that require expensive, time-consuming, complex and invasive redesigns and redeployment. Data Encryption at Rest and In-Transit (TLS) check the compliance boxes. Compliance platforms track adherence to each of the fragmented policies. Yet, the continuum is missing.

Too often, remediation becomes a series of human-driven steps: assess metadata, quantify exposure, pick a tool, buy licenses, and then wait for business teams to spend huge cycles, and millions of dollars to integrate and implement.

That process can take months or years, if it happens at all. As they say: if it’s not automated, it’s broken.

Building the Bridge – Privaclave + DSPM (The Microsoft Purview story!!)

At Privaclave, we believe that visibility and protection are two sides of the same coin, and they work best together. When a regional hospital, using Purview for data discovery and classification, and some other capabilities such as DLP, shared their concern about finding quite a few sensitive files containing patient information exposed to 3rd parties, they expressed the interest in de-identifying the PHI on those files easily and quickly. That way, their business processes and agreements with partners for clinical research and patient analytics don’t get affected, yet the risk of PHI sprawl across a network of integrated partners is addressed effectively.

That’s why we have built a native integration with Microsoft Purview and are inviting other DSPM platforms to join in building a Better Together ecosystem.

Here’s how this synergy works:

Discovery: Microsoft Purview scans enterprise data stores, identifies sensitive data, and exposes detailed metadata.
Analysis: Privaclave exports and consumes this metadata through Purview’s APIs, runs its own runtime classification to confirm context and sensitivity, and pinpoints exactly where sensitive elements reside.
Action: Based on policy, Privaclave automatically de-identifies or desensitizes that data, replacing originals with secure, sanitized versions.
Enrichment: Purview’s metadata is updated with accurate contextual insights and the remediation status, thus closing the loop between detection and protection.

The result: risks discovered by Purview are remediated by Privaclave – automatically, seamlessly, and continuously. Connect with us to see a quick demo for this integration.

No code rewrites. No new infrastructure. No business disruption. Just realtime, automated, and frictionless protection.

Beyond File Stores – Extending to Databases and Data Warehouses

The Privaclave–DSPM integration extends well beyond unstructured data or file stores. When DSPMs identify risks in databases, data lakes, or data warehouses (such as Snowflake, Databricks, BigQuery, Redshift, or SQL Server), Privaclave can automatically onboard users, services, AI applications or agents ingesting and consuming these into its runtime protection framework, without requiring any changes to them.

Here’s what that means in practice:

On Ingest: As data pipelines write sensitive records into databases or migrate into warehouses, Privaclave intercepts and automatically desensitizes the data, ensuring sensitive fields like PII or PHI are persistently secured before storage.
On Access: When users, analytics platforms, or AI agents query those same datasets, Privaclave dynamically determines, based on IAM roles, policies, and permissions, which fields can be exposed in the clear and which remain protected or masked.
For Analytics: Reports, dashboards, and AI models can still run seamlessly on sanitized data, maintaining referential integrity and analytical fidelity while ensuring compliance and privacy.
For Unsanitized Data: If the underlying data is not yet desensitized, Privaclave automatically sanitizes it in real time for authorized consumers, ensuring that no sensitive data is ever exposed unintentionally, even to AI applications, LLMs, or autonomous agents.

This capability transforms data protection from a static, storage-level exercise into a living runtime shield, enforcing contextual, runtime protection wherever data moves or is accessed.

Together, DSPMs and Privaclave bring end-to-end coverage – from discovering sensitive data to ensuring it’s always protected, everywhere it lives.

Why “Better Together” Matters

This is more than an integration – it’s a mindset. Data protection is a collective challenge. No single platform can solve it end-to-end, and no enterprise should have to juggle disconnected tools, and require a massive overhaul of services to stay secure.

The DSPM category is well crowded and some of the tools such as Microsoft Purview, BigID, Varonis, Sentra, OneTrust, Symmetry Systems, Concentric AI, Cyera, Securiti, Dig Security, Laminar, Normalyze, Fortra, Open Raven, Flow Security, Eureka Security, etc. bring incredible strengths in discovery, mapping, and governance. Privaclave complements that with automated, runtime, zero-touch data protection, eliminating the need for code changes, proxies, or agents.

Together, they transform how organizations approach data security – from a reactive exercise into a continuous, collaborative workflow.

Because ultimately, better security is something we build together, not in silos. We deliver value for businesses when we collaborative, not compete.

From Insight to Action – Instantly

As data expands across clouds, AI models, and analytics platforms, the pace of risk is outpacing the capacity of human response, even with AI-powered detection. The path forward isn’t more tools – it’s smarter, connected ones.

Privaclave’s collaboration with DSPMs shows what’s possible when visibility and protection operate in unison. It’s a future where risks are not just identified but instantly remediated – where enterprises move from posture awareness and management, to posture assurance and elevation.

Better Together isn’t just a slogan – it’s the new architecture of trust. And it starts with turning insights into action, automatically.

Closing Thought

Data protection doesn’t need another silo – it needs runtime connection to cross the chasm that has existed forever. By unifying DSPM’s visibility with Privaclave’s runtime protection, enterprises finally gain a living, adaptive layer of defense that works across environments and at the speed of business.

If enterprises are currently using DSPMs, and obtaining insights across their data stores, they know that the job is half done. Lots of effort, time, and money spent on dashboards, identifying risks, and compliance reporting – but very little risk has been reduced. And the path to risk reduction that requires a whole new set of security controls implementations, applications and infrastructure redesigns and deployments, would take another few years to complete. You DON’T have that luxury – You have build that continuum between risk identification to risk remediation, in an automated, runtime, and frictionless way. The old playbook is no longer applicable in the age of AI and Quantum.

If you are a DSPM company, helping enterprises to manage their data security posture, let’s talk and explore opportunities for synergies and collaboration, where together we could offer a better solution to enable enterprises to move from posture management to posture elevation.