Middleware and infrastructure that make AI behavior structurally verifiable — not promised, proven. Built on MaL, a formal framework where mathematics is the system, not a layer applied on top of it.
Four products. Each drops into deployments you already run — no retraining, no rip-and-replace.
A mathematical decomposition pipeline makes injections structurally inadmissible — not pattern-matched, not classified after the fact. No secondary classifiers, no retraining.
Every record receives a STARK proof and a cryptographic derivation chain. Immutable, auditable, quantum-resistant — proving what happened, not asserting it.
13 lifecycle gates check scope, evidence, risk, integrity, review, merge, closure, and release before agent-generated work is allowed to count. Reason-coded blockers and remediation — not conversational judgment.
Not a prompt wrapper, chatbot, IDE plugin, or hosted service. A repo-native lifecycle governance layer — alongside CI and repository permissions, not replacing them.
A green-looking result is not closure. MetaCortex Code stops when the repository is actually closed — queue empty, evidence complete, working tree clean — not when a model says it's done.
ORI, Metis, and Acropolis are peers — not layers, not parent and child. Each is autonomous, each serves a different domain, and all three compile down to MaL.
A research platform that reads, hypothesizes, and publishes — targeting ARC-AGI-3 and SciCode benchmarks.
A native deterministic cognitive architecture — not LLM-based. Built on the dual machine: dodecahedron and icosahedron.
A hash-only post-quantum L1 blockchain. STARK proofs, SLH-DSA/SPHINCS+ signatures, SHA-3/Poseidon dual-hash.
For digital consultancies and integrators: embed Hyphasis and Acropolis into your client deployments and ship provable AI governance as part of your delivery.
Become a partner →No academic lineage. The framework's authority comes from proven theorems, a self-hosting compiler, three autonomous systems, and empirical data — not from where the work was done, but from whether it holds.
An instrumentation background means treating cognition the way you treat a sensor system: define what must be true, build the apparatus that makes it true by construction, and measure. MaL is that apparatus.
Whether you're evaluating a product, integrating as a partner, or reviewing the research — tell us what you're trying to prove.
contact@metacortexdynamics.com