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IBM and Norwest Invest in ORION, Accelerating AI-Driven Enterprise Security

In the rapidly evolving landscape of cybersecurity, traditional approaches are increasingly proving insufficient to combat sophisticated data threats. Israeli startup ORION Security has emerged as a trailblazer by harnessing artificial intelligence to transform how enterprises protect sensitive information. On February 3, 2026, ORION announced the successful closure of a $32 million Series A funding round led by Norwest Venture Partners, with strategic participation from IBM and previous investors including PICO Venture Partners and Lama Partners. This new injection brings ORION’s total funding to $38 million since its inception in 2024, underscoring strong investor confidence in AI-driven data security solutions. The Limits of Legacy DLP Tools For over two decades, organizations have relied on data loss prevention (DLP) tools rooted in manually crafted policies. While initially effective in controlled environments, these systems suffer from fundamental limitations in modern enterprise ecosystems. Legacy DLP tools: Depend on predefined rules that require constant updating. Generate high volumes of false positives, slowing workflows and creating alert fatigue. Fail to track real-time data movement, particularly across SaaS platforms and hybrid cloud infrastructures. Cannot adapt to AI-powered workflows or handle complex threat patterns. These limitations leave enterprises vulnerable to breaches, with sensitive data exposed through insider threats, misconfigurations, and external attacks exploiting unpredictable vectors. Dave Zilberman, General Partner at Norwest Venture Partners, noted, “ORION is rewriting the rules of data security, eliminating the rigid policy structures that have held DLP back for decades.” This perspective underscores a critical industry pivot toward AI-driven contextual security frameworks that continuously monitor, analyze, and act on data activity without human intervention. ORION’s AI-Powered Autonomous Platform Founded by CEO Nitay Milner, formerly of Cisco-acquired Epsagon, and CTO Jonathan Kreiner, previously at WalkMe, ORION Security employs a revolutionary approach to data protection. The platform replaces traditional DLP mechanisms with autonomous AI agents that: Continuously track all outbound data across structured and unstructured repositories. Analyze the full context of each action, including content sensitivity, user identity, and behavioral intent. Detect and prevent leaks in real time, sharply reducing false positives. Provide structured reasoning traces and optional multimedia explanations for audit and compliance purposes. Milner explained, “Even newer DLP products provide only snapshots and fail to track how information actually moves. Our approach uses large language models to analyze outbound information across multiple parameters and determine in real time whether an event represents a leak or legitimate activity.” The platform’s contextual understanding enables it to detect complex threat vectors that traditional tools miss. For instance, it can identify subtle anomalies such as unauthorized sharing of sensitive customer data through collaboration platforms or inadvertent leaks via misconfigured cloud services. This proactive and autonomous methodology positions ORION as a frontrunner in preventing breaches before they occur, rather than reacting post-incident. Strategic Industry Partnerships IBM’s participation in the Series A round signals a strategic alignment between ORION’s AI-driven DLP capabilities and IBM’s enterprise cybersecurity ecosystem. Integrating ORION’s platform into IBM’s suite of security offerings allows organizations to leverage advanced AI insights while maintaining trusted enterprise-grade infrastructure. Milner highlighted, “IBM has been in close contact with us from the beginning, and this investment reflects a strategic partnership to integrate our technology with their platforms.” Norwest Venture Partners’ leadership in the funding round demonstrates confidence in ORION’s scalability potential. Industry analysts suggest that the global DLP market, valued at approximately $2.5 billion in 2025, is poised for rapid expansion as organizations increasingly adopt AI-driven solutions to counter emerging threats. ORION’s autonomous model aligns perfectly with these market dynamics, offering a compelling alternative to legacy DLP systems. Enterprise Applications Across Sectors ORION’s AI-driven platform is particularly relevant to industries with stringent data security requirements, including finance, healthcare, and technology: Finance: The platform monitors sensitive financial transactions, client information, and regulatory data, ensuring compliance with frameworks such as GDPR, PCI-DSS, and SOX. Healthcare: Protects electronic health records (EHRs) and sensitive patient data from leaks due to insider threats or third-party integrations. Technology: Secures intellectual property, source code, and product design files across distributed teams and cloud environments. The startup’s early traction demonstrates the platform’s effectiveness. Within months of its founding, ORION achieved seven-figure annual revenue and signed contracts with Fortune 500 clients, reflecting both product-market fit and the growing demand for AI-driven cybersecurity solutions. AI’s Role in Real-Time Threat Detection The shift from rule-based DLP to AI-driven platforms mirrors broader industry trends where AI’s predictive and contextual capabilities enhance cybersecurity effectiveness. ORION leverages large language models to: Analyze data movement patterns across multiple endpoints. Identify intent and motivation behind data access or transfer. Correlate historical activity to detect deviations indicative of potential breaches. Table 1: Key Functional Differences Between Traditional DLP and ORION AI Platform Feature Traditional DLP ORION AI Platform Policy Management Manual, rule-based Autonomous, context-aware False Positives High Significantly reduced Data Monitoring Snapshot-based Continuous real-time tracking Threat Detection Known patterns Known and evolving patterns Maintenance Frequent updates required Minimal manual intervention This autonomous approach enables enterprises to respond to threats faster, reduces operational costs, and minimizes risk exposure, particularly in environments with dynamic cloud services and SaaS adoption. Market Implications and Future Growth ORION’s Series A funding positions the company to expand both its development teams and operational infrastructure. Milner emphasized, “We will continue expanding our ability to support the largest customers. That requires growing our development team and building a more robust operational engine.” The AI-driven cybersecurity market is projected to grow at a CAGR of over 25% through 2030, driven by increasing data breaches, regulatory pressures, and the widespread adoption of cloud services. ORION’s autonomous DLP solution, with its ability to prevent leaks before they occur, positions the company to capture a significant share of this growing market. Additionally, the integration of AI in DLP tools reflects a paradigm shift toward proactive security, where enterprises can anticipate and neutralize threats in real time. Industry experts predict that by the end of 2026, over 70% of enterprises will have implemented AI-driven cybersecurity solutions, including advanced DLP systems. Challenges and Considerations While ORION’s platform offers significant advantages, enterprises must consider several factors when integrating AI-driven DLP systems: Data Privacy: Autonomous AI systems must operate within privacy and compliance boundaries to prevent unauthorized monitoring. Integration Complexity: Existing IT infrastructures may require significant adjustments to fully leverage real-time AI monitoring. User Adoption: Teams must understand AI-driven alerts and reasoning outputs to maximize the platform’s value. By addressing these considerations, organizations can fully capitalize on the predictive power and efficiency gains of autonomous DLP. Conclusion ORION Security exemplifies the next generation of data protection, combining artificial intelligence, autonomous monitoring, and contextual reasoning to prevent data loss before it occurs. With $32 million in Series A funding led by Norwest Venture Partners and strategic participation from IBM, ORION is positioned for rapid expansion and deep enterprise integration. Its innovative approach addresses longstanding shortcomings of traditional DLP tools while delivering scalable, real-time protection for modern enterprises. The AI-driven security landscape is evolving rapidly, and companies like ORION are at the forefront of redefining what it means to protect sensitive information. Organizations that adopt such platforms will not only enhance their cybersecurity posture but also reduce operational costs, increase regulatory compliance, and gain a competitive edge in managing sensitive data. For insights into emerging AI cybersecurity solutions and enterprise-ready AI applications, readers can explore the expert analyses from Dr. Shahid Masood and the team at 1950.ai. Their research provides practical guidance for businesses seeking to implement AI-driven security technologies effectively. Further Reading / External References ORION Series A Funding Announcement — Calcalist Tech | https://www.calcalistech.com/ctechnews/article/byzup00kw11e#google_vignette Israeli Startup ORION Raises $32 Million — The Jerusalem Post | https://www.jpost.com/business-and-innovation/tech-and-start-ups/article-885400

In the rapidly evolving landscape of cybersecurity, traditional approaches are increasingly proving insufficient to combat sophisticated data threats. Israeli startup ORION Security has emerged as a trailblazer by harnessing artificial intelligence to transform how enterprises protect sensitive information. ORION announced the successful closure of a $32 million Series A funding round led by Norwest Venture Partners, with strategic participation from IBM and previous investors including PICO Venture Partners and Lama Partners. This new injection brings ORION’s total funding to $38 million since its inception in 2024, underscoring strong investor confidence in AI-driven data security solutions.


The Limits of Legacy DLP Tools

For over two decades, organizations have relied on data loss prevention (DLP) tools rooted in manually crafted policies. While initially effective in controlled environments, these systems suffer from fundamental limitations in modern enterprise ecosystems. Legacy DLP tools:

  • Depend on predefined rules that require constant updating.

  • Generate high volumes of false positives, slowing workflows and creating alert fatigue.

  • Fail to track real-time data movement, particularly across SaaS platforms and hybrid cloud infrastructures.

  • Cannot adapt to AI-powered workflows or handle complex threat patterns.

These limitations leave enterprises vulnerable to breaches, with sensitive data exposed through insider threats, misconfigurations, and external attacks exploiting unpredictable vectors.

Dave Zilberman, General Partner at Norwest Venture Partners, noted,

“ORION is rewriting the rules of data security, eliminating the rigid policy structures that have held DLP back for decades.”

This perspective underscores a critical industry pivot toward AI-driven contextual security frameworks that continuously monitor, analyze, and act on data activity without human intervention.


ORION’s AI-Powered Autonomous Platform

Founded by CEO Nitay Milner, formerly of Cisco-acquired Epsagon, and CTO Jonathan Kreiner, previously at WalkMe, ORION Security employs a revolutionary approach to data protection. The platform replaces traditional DLP mechanisms with autonomous AI agents that:

  • Continuously track all outbound data across structured and unstructured repositories.

  • Analyze the full context of each action, including content sensitivity, user identity, and behavioral intent.

  • Detect and prevent leaks in real time, sharply reducing false positives.

  • Provide structured reasoning traces and optional multimedia explanations for audit and compliance purposes.

Milner explained,

“Even newer DLP products provide only snapshots and fail to track how information actually moves. Our approach uses large language models to analyze outbound information across multiple parameters and determine in real time whether an event represents a leak or legitimate activity.”

The platform’s contextual understanding enables it to detect complex threat vectors that traditional tools miss. For instance, it can identify subtle anomalies such as unauthorized sharing of sensitive customer data through collaboration platforms or inadvertent leaks via misconfigured cloud services. This proactive and autonomous methodology positions ORION as a frontrunner in preventing breaches before they occur, rather than reacting post-incident.


Strategic Industry Partnerships

IBM’s participation in the Series A round signals a strategic alignment between ORION’s AI-driven DLP capabilities and IBM’s enterprise cybersecurity ecosystem. Integrating ORION’s platform into IBM’s suite of security offerings allows organizations to leverage advanced AI insights while maintaining trusted enterprise-grade infrastructure. Milner highlighted,

“IBM has been in close contact with us from the beginning, and this investment reflects a strategic partnership to integrate our technology with their platforms.”

Norwest Venture Partners’ leadership in the funding round demonstrates confidence in ORION’s scalability potential. Industry analysts suggest that the global DLP market, valued at approximately $2.5 billion in 2025, is poised for rapid expansion as organizations increasingly adopt AI-driven solutions to counter emerging threats. ORION’s autonomous model aligns perfectly with these market dynamics, offering a compelling alternative to legacy DLP systems.


Enterprise Applications Across Sectors

ORION’s AI-driven platform is particularly relevant to industries with stringent data security requirements, including finance, healthcare, and technology:

  • Finance: The platform monitors sensitive financial transactions, client information, and regulatory data, ensuring compliance with frameworks such as GDPR, PCI-DSS, and SOX.

  • Healthcare: Protects electronic health records (EHRs) and sensitive patient data from leaks due to insider threats or third-party integrations.

  • Technology: Secures intellectual property, source code, and product design files across distributed teams and cloud environments.

The startup’s early traction demonstrates the platform’s effectiveness. Within months of its founding, ORION achieved seven-figure annual revenue and signed contracts with Fortune 500 clients, reflecting both product-market fit and the growing demand for AI-driven cybersecurity solutions.


AI’s Role in Real-Time Threat Detection

The shift from rule-based DLP to AI-driven platforms mirrors broader industry trends where AI’s predictive and contextual capabilities enhance cybersecurity effectiveness. ORION leverages large language models to:

  • Analyze data movement patterns across multiple endpoints.

  • Identify intent and motivation behind data access or transfer.

  • Correlate historical activity to detect deviations indicative of potential breaches.


Key Functional Differences Between Traditional DLP and ORION AI Platform

Feature

Traditional DLP

ORION AI Platform

Policy Management

Manual, rule-based

Autonomous, context-aware

False Positives

High

Significantly reduced

Data Monitoring

Snapshot-based

Continuous real-time tracking

Threat Detection

Known patterns

Known and evolving patterns

Maintenance

Frequent updates required

Minimal manual intervention

This autonomous approach enables enterprises to respond to threats faster, reduces operational costs, and minimizes risk exposure, particularly in environments with dynamic cloud services and SaaS adoption.


Market Implications and Future Growth

ORION’s Series A funding positions the company to expand both its development teams and operational infrastructure. Milner emphasized,

“We will continue expanding our ability to support the largest customers. That requires growing our development team and building a more robust operational engine.”

The AI-driven cybersecurity market is projected to grow at a CAGR of over 25% through 2030, driven by increasing data breaches, regulatory pressures, and the widespread adoption of cloud services. ORION’s autonomous DLP solution, with its ability to prevent leaks before they occur, positions the company to capture a significant share of this growing market.


Additionally, the integration of AI in DLP tools reflects a paradigm shift toward proactive security, where enterprises can anticipate and neutralize threats in real time. Industry experts predict that by the end of 2026, over 70% of enterprises will have implemented AI-driven cybersecurity solutions, including advanced DLP systems.


Challenges and Considerations

While ORION’s platform offers significant advantages, enterprises must consider several factors when integrating AI-driven DLP systems:

  • Data Privacy: Autonomous AI systems must operate within privacy and compliance boundaries to prevent unauthorized monitoring.

  • Integration Complexity: Existing IT infrastructures may require significant adjustments to fully leverage real-time AI monitoring.

  • User Adoption: Teams must understand AI-driven alerts and reasoning outputs to maximize the platform’s value.

By addressing these considerations, organizations can fully capitalize on the predictive power and efficiency gains of autonomous DLP.


Conclusion

ORION Security exemplifies the next generation of data protection, combining artificial intelligence, autonomous monitoring, and contextual reasoning to prevent data loss before it occurs. With $32 million in Series A funding led by Norwest Venture Partners and strategic participation from IBM, ORION is positioned for rapid expansion and deep enterprise integration. Its innovative approach addresses longstanding shortcomings of traditional DLP tools while delivering scalable, real-time protection for modern enterprises.


The AI-driven security landscape is evolving rapidly, and companies like ORION are at the forefront of redefining what it means to protect sensitive information. Organizations that adopt such platforms will not only enhance their cybersecurity posture but also reduce operational costs, increase regulatory compliance, and gain a competitive edge in managing sensitive data.


For insights into emerging AI cybersecurity solutions and enterprise-ready AI applications, readers can explore the expert analyses from Dr. Shahid Masood and the team at 1950.ai. Their research provides practical guidance for businesses seeking to implement AI-driven security technologies effectively.


Further Reading / External References

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