ORION Security

Name: ORION Security
Brand: ORION Security

AI Native

ORION Security prevents data loss by analyzing data in motion with intelligent, context-aware AI agents.

Est 2024|Raised $38M

LinkedIn 4K|Web traffic 2K|FTEs 50|HQ Tel Aviv, Israel

MarketsData Security Platforms

Published Sep 26, 2026

01Common complaints

- If your procurement requires a large set of independent third-party reviews and long-term market validation, the limited public review signal increases adoption risk. - If you are prioritizing a single broad SSE/SASE suite and prefer to consolidate multiple security modules (SWG, CASB, ZTNA, DLP) with a single incumbent vendor, consider vendors that provide that consolidated stack. - If you require publicly posted pricing and a self-serve buying motion; this vendor operates a demo-led engagement model. - If your environment has strict constraints on any external model processing of sensitive content and you cannot accept ambiguity around model governance, retention, and training use; verify contractual and technical controls in gated security documentation. - Public documentation of specific operational issues and bug lists is limited. - The vendor has stated plans to expand coverage to additional environments; the roadmap lacks public, dated feature commitments. - Some third-party posts reference CVEs or vulnerabilities associated with components named "Orion." Buyers must validate whether any referenced vulnerability maps to this vendor’s commercial offering before treating it as applicable.

02Why they buy

A context-focused approach to DLP that emphasizes correlating data classification, data lineage, identity signals, and environmental context to identify risky data movement patterns.
Public signaling of security posture via a Trust Center listing SOC 2 Type 2 and ISO 27001:2022; buyers should verify scope and supporting documentation.
Focus on addressing modern exfiltration patterns associated with distributed SaaS and AI-driven workflows.

03Field reports

- **Public case studies:** Detailed public case studies with independent verification and hard metrics were not located in publicly accessible sources beyond vendor-published claims. - **Vendor-published metrics:** The vendor presents claims such as rapid time-to-detection and reduced false positives on its product pages; these are vendor-provided and lack publicly available methodology or independent validation. - **Partnership announcements:** The vendor has announced partnerships described as complementary to its data protection capabilities. Such announcements can indicate integration pathways and go-to-market alignment but do not substitute for independently validated customer outcomes.

What’s available publicly

- **Vendor-selected testimonials:** The vendor website includes vendor-provided quotes attributed to CISOs at organizations such as AMEX Global Business Travel, Elastic, and Incode. These are promotional testimonials selected by the vendor and should be treated as marketing material. - Example (vendor-provided quote): "ORION’s approach finally produces trustworthy, meaningful DLP alerts…" (attributed to a CISO at AMEX Global Business Travel). - Example (vendor-provided quote): "Traditional DLP has been broken for years…" (attributed to a CISO at Elastic). - **Independent review platforms:** Public listings or user reviews on platforms such as G2, TrustRadius, Capterra, and Gartner Peer Insights were not identified in the searches conducted for this report. The absence of independent platform reviews reduces the publicly accessible user signal.

Community / social discussion

Social media posts and community mentions: Limited community discussion was identified. Example: a community post sharing the vendor’s funding announcement; this does not provide hands-on product evaluation.

What’s missing (important)

Independent user reviews and references addressing product quality, support responsiveness, false positive rates in production, and deployment experiences were not readily available in public sources during this research window. This is a notable due-diligence gap.

04Best fit

- **Company sizes:** Mid-market to enterprise (larger mid-market and enterprise organizations) with complex SaaS, cloud, and endpoint data flows; organizations handling regulated data (finance, healthcare) are plausible targets. - **Industries:** Finance, healthcare, technology, and other sectors with sensitive data or complex data movement patterns. - **Roles/personas:** CISOs, VP Security, Head of SecOps, Head of Data Security, DLP program owners, SOC analysts, insider-risk teams, and security engineering teams responsible for integrations. - **Pain points addressed:** High DLP false positives and policy maintenance burdens; need to detect new exfiltration patterns and complex workflows that are not well served by static rules. - **Deal qualifiers:** Willingness to evaluate a newer vendor, ability to run reference checks, and willingness to engage in a security review to validate certifications and controls. - **Deal disqualifiers:** Need for extensive public, independent reviews and a long vendor track record; requirement for deterministic, policy-only DLP logic without probabilistic/AI reasoning.

05The pitch

- **What the product does (core value proposition):** ORION Security describes its platform as an automated data loss prevention (DLP) solution focused on preventing data exfiltration by using contextual intelligence (data lineage, content understanding, identity, and environment signals) rather than relying primarily on large sets of static DLP policies. - **Target market & positioning:** Enterprise security teams (CISO organization / SecOps) experiencing high false positives from traditional DLP, substantial operational tuning burdens, and new data movement patterns related to emerging AI workflows. ORION positions a context-focused DLP approach rather than a policy-centric model. - **Company background:** ORION Security reports it was founded in 2024, with offices in New York City and Tel Aviv. Key leadership includes CEO/co-founder Nitay Milner (former Epsagon product leader) and CTO/co-founder Jonathan Kreiner (former WalkMe application security leader). - **Funding and growth:** - Vendor disclosure: a Series A funding round announced in early 2026 (company press release and blog). - Earlier seed funding was reported in press coverage. - Some coverage aggregates seed + Series A into a combined total; buyers should confirm exact totals via primary databases or the company’s filings. - **Pricing model (tiers and costs):** - Pricing is not posted on the public website; the vendor uses a demo/quote-based engagement model. - Procurement is likely to follow enterprise quote-based pricing patterns common for DLP/SSE tools, with costs influenced by endpoints/users, environments covered (SaaS, endpoint, cloud), and compliance/security add-ons. - **Total cost of ownership (TCO) considerations:** - The vendor states rapid initial setup metrics and significant false-positive reductions; these statements require verification of methodology, baselines, and sample sizes. - Typical hidden costs for DLP programs apply: data classification efforts, incident response workflows, integrations (SIEM/SOAR/IdP/HRIS/CRM), and ongoing model governance. - **Key competitors (4–6 direct alternatives):** - Netskope (SSE/SASE with DLP) - Zscaler (DLP as part of a broader security platform) - Symantec/Broadcom DLP (legacy enterprise DLP) - Forcepoint DLP - Microsoft Purview DLP - Proofpoint (email-centric DLP and insider risk tools)

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