Data Loss Prevention (DLP): What It Means in 2026 and Why Traditional Approaches Fall Short
Data loss prevention has been around for years. Most security teams recog...
Concentric AI has turned the page on 2025, and what a year of growth and innovation it was. We continued to receive industry and analyst recognition, expanded the capabilities of our Semantic Intelligence™ platform, and strengthened our leadership team, including adding seasoned Fortune 500 Cybersecurity and Risk Executive Lane Sullivan as our new Chief Information Security and Strategy Officer.
The biggest event of the year was, without question, our acquisition of not one but two cutting-edge data security technologies to amplify the capabilities of our platform and deliver the industry’s first truly end-to-end data security governance solution. Our acquisitions of Swift Security and Acante brought together data security posture management (DSPM), data loss prevention (DLP), and GenAI governance, dramatically expanding our protections to secure enterprise data at rest, in motion, and across all the GenAI applications users interact with.
We won multiple awards, including the 2025 SC Award for the industry’s Best Data Security Solution and were ranked as a Leader in the 2025 GigaOm Radar for Data Loss Prevention. In addition to this, we were recognized in multiple other analyst reports: the 2025 Gartner® Market Guides for Data Security Posture Management and for AI Trust, Risk, and Security Management, the Gartner Hype Cycle for Data Security (across five key categories), the Omdia Universe for Data Security Posture Management (DSPM) 2025, and the Forrester Sensitive Data Discovery and Classification Solutions Landscape, Q4 2025.
We demonstrated our commitment to leading the way in AI-driven data security and furthered our lead over the competition with a total of seven new patents and added Texas Risk and Authorization Management Program (TX-RAMP) Level 2 certification to our extensive list of security validations and certifications.
We announced support for private scanning across both AWS and Microsoft Azure environments, enabling compliance and comprehensive GenAI data security for highly regulated organizations required to process their data on-prem. New, context-driven User Behavior Data Analytics (UBDA) capabilities in our platform uniquely enable organizations to identify abnormal user-level activity in relation to data.
We continued our mission of enabling customers to leverage our industry-leading data security across multiple data sources in their cloud and on-premises environments by building out new integrations and expanding on existing ones. These include Salesforce, GitHub, NetApp ONTAP, MongoDB, Google Cloud Storage, Azure Data Lake, and ServiceNow as well as integrations with the rest of the security ecosystem, such as Wiz. Our new integration with OpenAI’s ChatGPT Enterprise Compliance API allows organizations to safely benefit from its innovation and productivity.
We have customers today in 12 different verticals across the globe from ANZ to EMEA to North America. We have production deployments across customers from 100s of TBs to 100s of PBs in manufacturing, high-tech, financial services, energy, higher ed, legal, insurance, and state and local governments, to name a few.
As we roll into 2026, the biggest market opportunity for Concentric AI is helping organizations adopt generative AI without expanding their attack surface. Data security governance is an essential first step for any meaningful GenAI rollout. Concentric AI’s Semantic Intelligence™ data security governance platform addresses this need across three critical GenAI use cases:
- GenAI assistants (e.g., Microsoft Copilot): Prevent sensitive data from being exposed to unauthorized users through precise data categorization and built-in remediation. The platform also provides details into what data Copilot shares, with full user and timestamp tracking.
- Public GenAI tools (e.g., ChatGPT, Perplexity, Claude): Deliver visibility into public GenAI usage and enable guardrails that warn, block, or redact sensitive data before it is shared—powered by highly accurate data classification.
- Proprietary GenAI models: Ensure models built on platforms like Databricks and Snowflake are trained only on approved data and return sensitive information only to authorized users. Tagging, data masking, and remediation capabilities provide full lifecycle data governance.
I expect 2026 to be our best year yet as we go full throttle on advancing our capabilities to protect data—wherever it lives and however it travels—and I look forward to working closely with our partners as we empower our customers to safely, confidently, and responsibly embrace GenAI without compromising their data security risk posture.