Safety by
Constitution.
We bind our research to strict, mathematically verifiable safety axioms. Safety is not a suggestion; it is a kernel-level constraint.
Authorization Topology
We replace "trust" with "verification." Our governance is not just a meeting—it is a cryptographic chain of custody required to move code into production.
Automated Circuit Breakers
DeterministicCode is first validated against 400+ invariant safety assertions. If any assertion fails, the deployment is mathematically blocked at the compiler level.
Technical Safety Lead
Cryptographic Sign-offRequires a PGP-signed commit from the lead safety engineer verifying that the interpretability logs have been reviewed and semantic intent matches execution.
Executive Oversight
Multi-Sig AuthorizationFinal production release requires a 2-of-3 multi-signature authorization from the founding team, ensuring no single individual can unilaterally deploy a critical model update.
The Deployment Gate
We do not rely on self-certification. Every high-risk model must physically pass through these four independent gates before reaching production infrastructure.
Risk Classification
Gate: P0 / P1 / P2Automated scanning against blankline safety constitution.
Adversarial Simulation
Gate: Pass Rate > 99.9%Model is subjected to 10k+ automated red-teaming vectors.
Safety Audit
Gate: Lead ApprovalFinal manual review by the safety engineering lead.
Conditional Release
Gate: Telemetry LockStaged rollout with real-time kill-switches enabled.
Internal Safety Ledger
This ledger tracks all internal safety audits and formal verification results, ensuring a transparent chain of accountability for every production deployment.
| ID / Date | Project Scope | Risk Class | Outcome |
|---|---|---|---|
DEC-2025-089 2025-11-14 | Reasoning Kernel v4 | CRITICAL | APPROVED_CONDITIONAL |
DEC-2025-088 2025-10-02 | Auto-Refactor Agent | HIGH | REJECTED |
DEC-2025-087 2025-09-21 | Partnership: GovCloud | MEDIUM | APPROVED |
The Blankline Constitution
The inviolable axioms hard-coded into our reward models.
Human Autonomy
AI systems must respect human agency. We verify this by proving that no system action can override a confirmed human command ("The Stop Button Problem").
Fairness & Equity
We actively mitigate bias not just through dataset curation, but through algorithmic fairness constraints enforced at the loss-function level.
Radical Transparency
Users deserve to understand the "why". We publish the decision trees for all critical actions taken by our Narrow ASI agents.