April 6, 2026

Onit Security: Decision-based Exposure Management, an AI-native Approach Eliminating Vulnerability Backlogs at Enterprise Scale

By:
Jamil Mneimneh
Brightmind invested in Onit Security, founded by Ofer Amitai, Elad Ben Meir, and Tom Winter, with Amitai's firsthand experience watching a vulnerability backlog lead to the compromise of his prior company Portnox serving as the driving force behind an entirely new approach to exposure management. Traditional vulnerability management has been fragmented across siloed scanners and homegrown workarounds, consistently failing enterprises due to limited asset context, inconsistent prioritization, and the inability to act without unintended consequences. Onit's decision-based, AI-native platform unifies business context with risk signals across the enterprise, embedding operator feedback directly into the engine to ensure autonomous, context-aware remediation that closes gaps at machine speed. With adversaries achieving breakout times as short as 27 seconds using AI, Brightmind sees Onit as the foundational layer for autonomous vulnerability management while also delivering meaningful productivity gains for IT and engineering teams.

At Brightmind Partners we look for founders with lived experiences that drive them to take on large, complex problems. Onit Security founder, Ofer Amitai , experienced the significant consequences of an unmanageable vulnerability backlog that resulted in the compromise of his prior company, Portnox. With the weight of that experience, the Onit team aggressively pursued a new approach to exposure management, utilizing AI to unify true business context with risk signals across the enterprise and close the gap at unprecedented speed and scale.

A Challenge Built for the AI-era

Traditional vulnerability and exposure management has been focused on silos, utilizing scanners to identify risk within domains. In talking with operators, we saw a significant trend towards homegrown solutions to tackle the unification challenge. Despite the presence of tools in RBVM and UVM over the past half decade, we found considerable levels of supplementation to engineer a business process compatible with the needs of the enterprises. With enormous tool sprawl and increasing IT complexity. No two customer environments truly look the same. Efforts to manage the holistic vulnerability pipeline historically have been nearly impossible due to three primary factors 1) limited business context regarding the underlying assets 2) the ability to define prioritization consistently 3) the ability to take action seamlessly without generating unintended consequences.

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AI has fundamentally shifted this paradigm, enabling business context and reasoning to drive each decision in the vulnerability management lifecycle at machine speed.

The Onit platform enables customers to embed their feedback into the engine, ensuring that the actions that are driven by the platform align to their unique concept of risk. This is a decision-based architecture, an AI-native approach that allows operators to autonomously respond to threats as they emerge, closing the gaps as they open. With adversaries driving breakout times in as little as 27 seconds using AI, it is critical that we build the foundation for autonomous vulnerability management today.

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Beyond the risk profile, there are also significant productivity gains to be realized by automation in this domain, and we expect that forward-looking operators will heavily value the time and focus their IT and engineering teams recover as a result.

We could not be happier to partner with Elad Ben Meir , Ofer Amitai , Tom Winter and the Onit Security team! Their relentless desire to reshape this market motivated us from day one to be a part of their journey.

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