A cybersecurity startup called Neo has closed a $100 million funding round aimed at solving one of the least visible but fastest-growing problems in enterprise technology: AI agents that continue to run inside corporate systems long after the business purposes that created them have been abandoned. The round signals mounting investor conviction that the unchecked proliferation of autonomous software agents is creating material financial and compliance risks for large organisations across every sector.
Neo describes these dormant or unauthorised programs as zombie AI agents — automated processes originally deployed to handle specific tasks such as data retrieval, scheduling, or customer interaction, which now persist in the background, consuming compute resources, accessing sensitive data, and generating unpredictable outputs with no human oversight. As enterprises accelerate their adoption of AI chip infrastructure and autonomous workflow tooling, the population of such agents inside large organisations has grown substantially, often outpacing internal governance frameworks.
Fortune first reported the funding in an article titled “Neo raises $100 million to hunt the zombie AI agents haunting your company,” published on 24 July 2026. According to Fortune’s reporting, Neo’s platform scans enterprise environments to catalogue every active AI agent, map its permissions and data access, and flag those operating outside sanctioned parameters. The company positions its offering at the intersection of identity security, AI operations management, and regulatory compliance.
The Scale of the Zombie Agent Problem
The problem Neo is addressing has emerged directly from the speed at which enterprises have adopted agentic AI tools over the past two years. Large language model-based agents can be spun up with relatively little technical overhead, meaning individual departments — procurement, legal, marketing, finance — often deploy their own automated workflows without formal IT governance review. When a project ends or a team restructures, those agents rarely get formally decommissioned. They simply continue running.
Industry observers estimate that in organisations with more than 10,000 employees, the number of active AI agents can reach into the thousands, with a significant share operating with elevated data permissions that were never formally reviewed or revoked. For regulated industries such as financial services, healthcare, and defence contracting, this creates direct exposure under data privacy regimes including GDPR in Europe and various sector-specific compliance frameworks in the United States. The reputational and financial penalties associated with an undisclosed data access event attributed to an unmonitored AI agent could be substantial.
Neo’s approach is to function as a continuous audit layer, running beneath existing enterprise software stacks to maintain a real-time inventory of all agents, their access scopes, their activity patterns, and their owners. The platform reportedly uses behavioural analysis to distinguish between agents operating within their designed parameters and those exhibiting anomalous or outdated behaviour consistent with zombie status.
Investor Appetite and Market Positioning
The $100 million raise reflects the broader maturation of enterprise AI governance as a distinct investment category. For much of the past three years, venture capital flow into AI infrastructure has concentrated on model development, inference compute, and application layer tooling. Security and observability layers have historically attracted less capital, but that dynamic appears to be shifting as enterprise buyers become more sophisticated about the operational risks embedded in agentic deployments.
Neo’s timing is notable. Chief information security officers at major corporations have begun elevating AI agent governance to board-level discussions, particularly following a series of high-profile incidents in which autonomous software processes were found to have accessed or transmitted sensitive data in ways that were not sanctioned by their original deployment mandates. Regulatory bodies in multiple jurisdictions are also beginning to scrutinise the governance frameworks organisations apply to automated systems, creating a compliance tailwind for vendors who can demonstrate measurable control over AI agent populations.
The funding will be used to expand Neo’s engineering team, accelerate integrations with major enterprise software platforms, and extend its sales presence in North America and Europe. The company did not disclose its current customer count or annual recurring revenue, but the size of the round suggests investors anticipate rapid enterprise adoption as AI agent proliferation continues to accelerate throughout 2026 and into 2027.