ORION Security
Data loss prevention can use contextual intelligence about how information moves, reducing dependence on security teams continually defining and tuning rules.
Company snapshot
- Stage
- Unknown
- Status
- published
- Updated
- Nov 8, 2026
- Views
- Website
- orionsec.io
What they're building
Data loss prevention can use contextual intelligence about how information moves, reducing dependence on security teams continually defining and tuning rules. ORION Security uses AI agents to detect and prevent sensitive data leaks by understanding data movement and business context across enterprise systems.
Founders
Nitay Milner
Co-founder
Jonathan Kreiner
Co-founder
Foundation model usage
Editorial estimates from product descriptions. Model providers and actual usage are not confirmed.
- Inferred architecture
- Agentic loops, Embeddings & semantic search
- Estimated model demand
- High intensity
NYC footprint
- NYC presence
- NYC company or team supported by public sources. Street address has not been verified.
Funding
Public funding details are not disclosed yet.
Sources & location evidence
Open research desk ↗Profile source review: 2026-11-04. Company identity, product and named founders only. Existing funding stage and NYC presence need separate verification. Synthesized; technical doctrine route. Original homepage line: 'Agentic DLP for Data in Motion.' September 30, 2026 official announcement describes contextual analysis across channels and explicitly names the two founders. Correct orionsecurity.com, which belongs to an unrelated physical-security business, to orionsec.io. Do not normalize Jonathan to Yonatan from secondary coverage. Blurb word count: 22; thesis word count: 21.
- https://www.orionsec.io/ ↗
- https://www.orionsec.io/blog/orion-security-selected-to-icons-sv101-batch-19 ↗
- https://www.orionsec.io/blog/orion-closes-32-million-in-funding-building-dlp-beyond-policies ↗
- https://www.orionsec.io/blog/orion-security-announces-accelerated-growth-with-new-enterprise-customers ↗
Notes
ORION Security is tagged clear buyer pull based on buyer clarity, repeat workflow activity, public activity, and fit with the AI Atlas map.
