For decades, data loss prevention has meant writing enough rules to cover every threat you can already name — a model that collapses the moment work moves into AI tools, SaaS, and autonomous agents. ORION Security rebuilt DLP from the ground up as an AI-native platform that reasons over data in motion, not just data at rest.
Rather than using AI only to classify content while leaving detection to static policy, ORION uses AI as the primary detection engine. It follows every data movement (copy, upload, paste, prompt submission) end to end, connecting source, identity, destination, and behavior into a single “data story” instead of siloed alerts from disconnected endpoint, browser, SaaS, and email tools. This shifts DLP from a rule engine bolted onto network exits to an intelligence layer that understands data the way an analyst would.
The results:
–Detections begin within 30 minutes of deployment, with no policy library or pre-classification required.
–Roughly 90% of detections are generated automatically by AI, with false-positive rates near 5%, against an industry norm of 80–90%.
–The same architecture now extends to AI agents and MCP-driven workflows, governing not just what employees send to AI, but what AI does on their behalf.
One ORION customer evaluated Forcepoint, Cyberhaven, and Microsoft Purview before choosing ORION for 50,000 endpoints. Rollout to full blocking took six weeks, with under 5% false positives and less than one FTE required to operate it. As the customer’s project lead put it: “ORION is the first platform that paints the complete picture of enterprise data flows, enabling real-time risk assessment with extremely high confidence.”
Founded by Nitay Milner and Jonathan Kreiner in 2024, ORION has raised $38 million, including a $32 million Series A led by Norwest Venture Partners with IBM Ventures’ participation, with customers including LinkedIn, American Express, Alera Group, and Coursera.
Legacy DLP was built to observe data loss. ORION was built to prevent it.
About this category: Data Loss Prevention (DLP)
The Cybersecurity Excellence Awards recognize data loss prevention products. The category covers products that stop sensitive data from leaving an organization through email, endpoints, web, cloud apps or AI tools.
An independent jury of security practitioners, analysts and CISOs scores each nomination on leadership, innovation and impact. Each nomination competes in its category against organizations of similar size and region. Entry packages, sponsorship and public votes do not affect the jury's scores.
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