The security problem Neo is solving is one that crept up on most enterprise security teams quietly and then became urgent very fast. AI capabilities didn't arrive in our environment through a single approved deployment, they arrived through Salesforce adding an autonomous agent feature, through employees installing browser extensions, through productivity tools quietly shipping agentic updates in the background. By the time we tried to get a handle on what agentic software was actually running across our environment, we realised we had no clean inventory, no consistent view of what those tools could access, and no policy layer that had been built with autonomous software behaviour in mind. Neo's platform gives security operations teams an inventory of AI agents, applications, browser extensions, plugins, Model Context Protocol servers, and traditional software that has quietly acquired agentic functions. That inventory capability alone addressed the most immediate gap, finally having a complete, continuously updated picture of what agentic software exists across the environment rather than a partial list assembled from approved procurement records that hadn't kept pace with how fast the landscape was changing. Neo's AI agents automatically discover software, analyse skills, summarise intended functionality and compare those findings with actual behaviour to identify malicious or deceptive software. That behavioural comparison intended function versus actual runtime behaviour is the detail that matters most from a risk intelligence standpoint. A browser extension that declares itself a productivity tool but is observed accessing credential stores behaves differently than its stated purpose implies, and Neo surfaces that discrepancy rather than taking the software's self-description at face value. The platform also reviews terms of service, requested permissions and data usage policies to determine whether applications train on enterprise information or request excessive privileges. That automated policy review layer is something our security team had been trying to do manually for approved AI tools and failing to keep up with, Neo operationalises it at the speed and scale that manual review can't match. Neo links actions to the responsible user, agent, application or identity and blocks activity deemed risky, which closes the attribution gap that makes agentic software so difficult to govern with traditional security tooling. When an autonomous agent takes an action using inherited user permissions, understanding whose permissions were used, which agent invoked them, and what the action chain looked like end to end is exactly what incident response needs and exactly what most security stacks currently can't provide. For a platform performing continuous real-time discovery and behavioural analysis across an enterprise software environment, performance is a legitimate concern, and Neo handles it better than expected given its stage. The on-device analysis architecture, which processes AI sessions locally rather than routing data through external cloud services, contributes to low-latency detection without the network overhead that cloud-relay approaches introduce. Inventory updates and risk posture changes reflect reasonably quickly when new software is detected or existing software behaviour shifts, which matters for a control layer meant to catch risky actions before they complete rather than flag them after the fact. At larger environment scales the platform's performance characteristics are less proven simply because the track record across truly large, complex enterprise deployments is still being established. Early indications are positive but any security team running at significant scale should validate performance behaviour in their specific environment during evaluation. Neo analyses AI sessions directly on the endpoint rather than forwarding prompts, conversations or user activity to external cloud services, which reduces privacy concerns because sensitive information remains on the device. For enterprise environments with data residency requirements or handling sensitive personal data, that on-device analysis architecture removes a category of concern that would otherwise complicate or block deployment entirely. The founding team's depth is also worth noting because in security it genuinely signals product quality. Neo was founded by former executives and engineers from SentinelOne, Wiz, and Palo Alto Networks, organisations that collectively defined how modern endpoint and cloud security works. That institutional knowledge shows in how the platform thinks about detection, attribution, and policy enforcement rather than just inventory and reporting.