Reality Kernel
Reality Kernel provides causal verification for AI agents by simulating actions across shadow worlds, preventing attacks undetectable by LLM judges.
Reality Kernel
What is Reality Kernel?
How to use Reality Kernel?
- 1Integrate Reality Kernel into your agent framework.
- 2Define agent actions and desired policies.
- 3Run simulations across parallel shadow worlds.
- 4Analyze causal impact and ensure safety.
- 5Deploy with confidence.
Reality Kernel Key Features
- Deterministic basin mapping for causal analysis
- Cryptographic audit logs with SHA-256 sealing
- Sub-millisecond latency fast path
- Parallel shadow world simulation
- Prevention of attacks undetectable by LLM judges
Reality Kernel Use Cases
- Securing AI agent actions in production
- Auditing agent decisions for compliance
- Testing agent behavior in simulated environments
- Detecting hidden vulnerabilities in autonomous systems
Reality Kernel Pricing & Free Credits
Reality Kernel currently operates on a Custom Pricing model.
Reality Kernel Pros & Cons
Pros
- High performance with sub-millisecond latency
- Cryptographic audit logs ensure integrity
- Catches attacks missed by traditional LLM judges
- Scalable across multiple shadow worlds
Cons
- May require integration effort
- Pricing not publicly available
- Limited to agent-based systems
What is Reality Kernel best for?
- Security teams for AI agents
- Developers building autonomous systems
- Organizations requiring robust agent verification
Reality Kernel FAQ
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