Boundary Enforcement
Hard and Fast
Multi-layered approaches to ensuring AI systems operate within defined boundaries, combining neuro-symbolic engines, cryptographic gating, and behavioral proof techniques.
Overview
Boundary Enforcement is our flagship research into constraining AI behavior. We combine multiple complementary techniques to create robust guardrails that prevent AI systems from exceeding their intended operational boundaries.
Key technical approaches include:
- Neuro-symbolic engines that combine neural flexibility with symbolic precision
- Cryptographic gating mechanisms that mathematically enforce access controls
- Behavioral proof techniques that provide formal guarantees about system behavior
Research Preview
The Rule Problem: Key Hazards in AI Boundary Enforcement — Our latest research preview identifies four classes of hazards across the rule lifecycle (lossy policy translation, rule generation pathologies, runtime enforcement gaps, and complexity-driven deadlock) and maps them to complementary mitigation strategies.