Cortexive

AI safety rules that exist only in system prompts can be silently overridden under context pressure. We build compiled enforcement layers that intercept every AI tool call and validate it against behavioral rules before execution, running outside the model's reasoning loop.

Fourteen lifecycle interception points. Twenty-plus validators in a prioritized chain. A dangerous git command is blocked by compiled regex, not by hoping the agent remembers the rule. The entire chain executes in under ten milliseconds.

Beyond blocking, the system manages cognitive load: 200+ behavioral rules are dynamically reduced to context-relevant subsets of five or fewer. Quality convergence systems make agents verify their own outputs through iterative defect discovery, catching premature completion before it reaches production.

Standard AI tools treat memory as flat file storage with no model of relevance, decay, or contextual recall. We apply computational models of human cognition to AI persistence: biologically-inspired memory with three distinct types, each with configurable stability and exponential decay curves.

At session start, five perception channels scan the environment before the agent is asked anything: code texture, context aroma, error resonance, conversation signature, and flow state. Spreading activation across the association graph produces ranked warmth scores. The AI wakes up already knowing what matters.

A reflexive intelligence layer promotes high-frequency patterns into sub-10ms cached responses, analogous to biological myelination. Emotional markers attach valence, arousal, and discrete emotions to memories. Deliberate knowledge crystallizes into reflexes over time, exactly as human expertise does.

Rule-based systems have blind spots that traditional testing cannot surface. We apply evolutionary algorithms to stress-test them: population-based evolution with fitness tracking and LLM-guided strategy synthesis in sandboxed runtime isolates.

Populations of attack strategies compete, combine, and mutate. Full genealogy tracking preserves evolutionary lineage: every successful evasion traces its ancestry through mutations and recombinations across generations.

The result integrates directly into CI/CD pipelines: merge only if the latest generation of adversarial strategies fails to breach the rules.