Krnel offers runtime security for autonomous AI agents by monitoring their intended actions in real time and intervening before execution. Its platform reads an agent’s “mind” to enforce guardrails and ensure transparent, measured behavior, enabling continuous improvement of trusted autonomous systems.
Funding
Funding not disclosed
Founders
Product
Problem
Autonomous AI agents often operate as black boxes, making it difficult for organizations to understand their internal decision processes and to prevent unsafe or undesirable actions before they occur.
Solution
Krnel provides a runtime security platform that instruments the internal state of autonomous agents and intercepts their intended actions prior to execution. By continuously measuring intent and behavior, the system enforces transparent guardrails that block unsafe decisions in real time. Detailed telemetry is collected to enable ongoing monitoring, debugging, and improvement of agent performance. The platform acts as a control plane for enterprise AI, delivering measurable, trusted autonomy for complex machine systems.
Target Audience
Primary customers are enterprises deploying autonomous AI agents in critical applications, such as industrial automation, robotics, and large-scale decision systems, as well as AI product teams that require safety and observability for their models.
Features
- Real-time instrumentation of agent state to expose intent and decision pathways
- Pre-execution interception layer that can block or modify actions based on policy rules
- Continuous telemetry stream for monitoring, debugging, and performance analytics
- Transparent guardrail framework that enforces safety and compliance constraints
- Integration hooks for enterprise AI pipelines, allowing seamless adoption in existing workflows