A deterministic verification layer for AI systems. QWED verifies AI outputs using mathematics, symbolic reasoning, and formal methods (Z3, SMT, SymPy), creating an auditable trust boundary for agentic AI. Not generation. Verification.

Deterministic validation firewall that verifies AI-generated proposals against ground-truth state using immutable rules. Zero dependencies. Patent pending.

Deterministic MCP Security Architecture. FrozenNamespace as Root of Trust for Model Context Protocol tool verification

🏛️ Deterministic rejection layer for computational legal claims. Verifies dates, amounts, and structured constraints; blocks unproven legal outputs.

Proof records linking detection, validation, and evidence-backed claims.

Natural-language circuit generation with deterministic electrical verification.

Platform architecture and operational components supporting the security stack.

Validation harnesses, test cases, and reports for detection quality gates.

Deterministic local proof harness for verifying AI agent recommendation claims against source-of-truth fixtures, with append-only outcome logs.

Deterministic verification via MCP - Sandboxed Python execution for math, logic, code, and SQL verification

Structured prompts and verifiable execution for Claude Code agents. The Danilov method: INDEX/DEFINITIONS/RELATIONS prompts, one-hot DanilovGoal tracking with an HMAC-signed trace and a deterministic verdict, plus token-efficient .vascend memory. Zero dependencies.

Verification for Universal Commerce Protocol (UCP) transactions - Catch AI math errors before payment

Verify any agent output before it is trusted, paid for, or acted on. A universal SAR verification pattern for AI agent workflows.

Posts a PR change receipt showing what was checked, what was found, and what was not checked. Covers Kubernetes, Dockerfile, and GitHub Actions.