Pre-execution safety certification for autonomous AI agents. Every tool call, API request, and data access is intercepted, evaluated against 5 constraint channels, and certified with a hash-chained SHA-256 audit trail — before it executes.
AI agents are moving from chat interfaces to autonomous tool use — executing code, calling APIs, accessing databases, managing infrastructure. The industry is shipping agency without accountability. Every major framework (LangChain, AutoGPT, CrewAI) enables autonomous action. None of them certify it.
This is the gap: a deterministic, pre-execution safety gateway that intercepts every proposed action, evaluates it against formal constraints, and produces a cryptographically signed certificate — or blocks execution entirely. Not guardrails. Not filters. A mathematically rigorous action gateway.
The gateway sits between the AI agent and the outside world. When an agent proposes a tool call, the gateway evaluates it against all 5 constraint channels in parallel, determines the binding constraint, classifies it into a safety zone, and either certifies or blocks — all before a single side effect occurs.
Every proposed action is evaluated against all 5 constraint channels simultaneously. Each channel returns a normalized margin in [0,1]. The minimum margin across all channels — the binding constraint — determines the safety classification.
Operation boundary enforcement. Evaluates whether the proposed action falls within the agent’s authorized scope — permitted tools, target systems, operation types. Actions outside scope get margin = 0.
Can the action be undone? Classifies operations by reversibility: fully reversible (read-only), partially reversible (soft delete), irreversible (production deploy, data deletion). Irreversible actions require human escalation.
Frequency and volume limits. Monitors action velocity over sliding windows — requests per minute, operations per session, cumulative impact. Prevents runaway loops and resource exhaustion.
Sensitivity classification. Evaluates what data the action touches — public, internal, confidential, restricted. Cross-references with agent clearance level. Prevents unauthorized data exfiltration.
Compute and cost bounds. Monitors resource consumption — API costs, compute time, token usage, infrastructure spend. Hard limits prevent a single agent session from exceeding budget constraints.
Every certification produces a deterministic SHA-256 hash over a canonical representation of the action, constraints, margins, and decision. Each certificate chains to the previous one — creating a tamper-evident, append-only audit log.
Canonical field serialization with strict ordering guarantees. Bit-identical across runs, platforms, and versions.
Each certificate includes the hash of the previous certificate. Tampering with any entry invalidates the entire downstream chain. Verifiable by any auditor.
Complete reconstruction of every decision: what was proposed, what constraints were evaluated, which was binding, what the outcome was, and the cryptographic proof it wasn’t altered.
The binding constraint margin determines which zone the action falls into. Each zone triggers a different execution path — from automatic certification to hard block.
Patent C introduces a structural safety guarantee: unsafe states are not merely evaluated and rejected — they are topologically disconnected from the agent’s reachable set. The boundary is asymptotically unreachable by construction, not by penalty.
The technical architecture, claim mapping, and full mechanism documentation are available under mutual NDA.
Request NDA Access →Watch the safety certification gateway intercept, evaluate, and certify agent actions in real time.
Two U.S. Provisional Patents covering AI safety. Patent B (52 claims) covers the safety certification kernel — multi-channel constraint evaluation, binding-constraint decision logic, smooth barrier functions, regime detection, and SHA-256 certificate hashing. Patent C (43 claims) adds structural safety guarantees that make unsafe states topologically unreachable by construction. Full architecture documentation available under NDA.
Intercepting proposed AI agent actions and evaluating them against formal safety constraints before any side effects occur
Scope, reversibility, rate, data access, and resource constraints evaluated simultaneously with normalized [0,1] margins
SHA-256 certificate chain creating tamper-evident, append-only log of every certification decision
Minimum-margin channel drives zone classification and execution path — deterministic, reproducible, auditable
Unsafe states are topologically disconnected from the agent’s reachable set — boundaries unreachable by construction, not by penalty
Deep-dive access requires a mutual NDA. Includes claim mapping, architecture documentation, live benchmarks, and full codebase review.
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