Nucleus Security has launched Helix, a new agentic AI engine designed to help security teams turn fragmented vulnerability and exposure data into faster, more consistent remediation decisions. The move comes as MSPs and MSSPs look for ways to reduce manual security operations work while managing increasingly complex customer environments.
Helix targets exposure discovery and remediation workflows
Helix is designed to help organizations monitor the evolving threat landscape, uncover gaps in their exposure management programs, and create workflows to address identified risks.
Specifically, Nucleus announced three new capabilities within the Helix engine:
- Nucleus Discover bridges the gap between vulnerability scans and published scanner signatures, using passive exposure detection to provide early warning of emerging and zero-day threats.
- Nucleus Helix AI Agent lets teams search data, analyze trends, and build exposure management programs in plain language.
- Nucleus Insights expands Nucleus’ agentic vulnerability intelligence capabilities with a data-collection agent that accelerates and scales in-the-wild threat intelligence collection, while new operational datasets improve remediation accuracy and efficiency.
“We brought AI engineering and security expertise to a problem that has always taken hours of manual work,” said Scott Kuffer, co-founder and chief product officer of Nucleus Security. “The result is Nucleus Helix: an engine that pairs the best of modern AI with fast, accurate, reliable execution, so teams remediate faster at enterprise-scale.”
The launch is one of many recent product announcements that aim to leverage agentic AI within existing security workflows, as the industry races to keep pace with the speed and quantity of attacks and risks affecting businesses worldwide.
Nucleus expands automation across exposure management
Nucleus supports more than 200 connectors across security and IT systems. Its existing automation capabilities can process assets and findings, assign ownership, establish due dates, generate notifications, and create tickets in external platforms such as Jira and ServiceNow.
With Helix, the company is applying AI to the design and operation of those processes. Rather than requiring users to construct every workflow manually, the engine is positioned to help teams build autonomous workflows based on their exposure data and program requirements.
“Nucleus is taking a pragmatic approach to AI in exposure management: using AI to shape and improve processes while preserving deterministic execution for actions that affect production environments,” said Michelle Abraham, research vice president in IDC’s Security and Trust Group. “That distinction matters because security teams need AI’s speed and insight without uncertainty in remediation and operational decision-making.”
The announcement follows the late-2025 introduction of Nucleus 3.0, which added the Nucleus Query Language, customer-defined risk scoring, AI-powered vulnerability intelligence, and a Model Context Protocol (MCP) server for governed natural-language interaction with platform data.
Why Helix matters to MSPs and MSSPs
For MSPs and MSSPs, the potential value of an exposure management engine lies less in producing another stream of alerts and more in making existing security data operational across multiple customer environments.
Providers frequently collect findings from vulnerability scanners, endpoint platforms, cloud security tools, code scanners, and asset-management systems. Those products may assign different scores to the same issue, create duplicate findings, or lack the customer-specific context needed to determine what should be remediated first.
A platform that normalizes those findings and uses intelligence and business context to guide workflows could help service providers reduce analyst workload, standardize service delivery, and demonstrate measurable risk reduction to customers.
“The opportunity for practitioners is to use AI to help make sense of enormous amounts of security and threat data, identify what requires attention, and turn that intelligence into action,” said Theresa Lanowitz, principal analyst, cybersecurity at Omdia.
“The organizations that get this right will be the ones that combine AI’s speed and analytical capabilities with the controls and predictability required to operate safely at enterprise scale.”