Who They Are
AI Cornerstone Associates LLC is founded and stewarded by Michael L. Shuler.
The organization is developing runtime governance infrastructure for enterprise AI systems operating in consequence-bearing environments, with particular attention to financial, regulatory, audit, authority, and system-of-record boundaries.
Michael registered AI Cornerstone Associates LLC with the TA-14 AI Governance Exchange as an attributable, version-bound governance entity and has authorized its registered architecture to proceed into a bounded TA-14 Founding Demonstration pathway.
What They Are Building
AI Cornerstone describes a Layer 3 Runtime Authority and Admissible Execution Architecture designed to separate probabilistic AI decision-making from consequential enterprise execution.
Its T = 0 model evaluates governing conditions before a proposed state mutation is permitted to bind.
The registered architecture describes pre-commit admissibility gates, deterministic BPMN/DMN evaluation, fail-closed behavior, human-in-the-loop escalation, and execution receipts intended to preserve evidence concerning the proposed action, governing authority, determination, and execution boundary.
The architecture is particularly focused on environments where autonomous or agentic systems may attempt to write to financial, operational, regulatory, or other systems of record.
What They Declared
AI Cornerstone declares that its architecture can evaluate policy boundaries, data state, identity, authority, and other defined execution conditions at T = 0 before consequential state mutation.
Its registered claims include pre-commit execution-boundary control, deterministic fail-closed logic, immutable T = 0 payload logging, threshold-based exception routing, and evidence mapping to multiple governance and regulatory frameworks.
The registration also preserves explicit non-claims. AI Cornerstone does not claim that the architecture proves underlying model correctness, independently certifies regulatory compliance, replaces human or fiduciary responsibility, originates underlying organizational authority, guarantees upstream data quality, or guarantees immunity from cybersecurity failure.
Those claims and non-claims remain governed by the permanent Registry baseline.
Explicit Boundaries & Non-Claims
This profile does not certify or endorse AI Cornerstone Associates LLC; validate technical performance; establish legal or regulatory compliance; adjudicate intellectual-property ownership or priority; establish fitness for deployment; or predetermine any finding in FD-2026-0004. Registration is not certification.
Known Limitations
No additional public commentary is published for this section yet.
TA-14 Institutional Commentary
AI governance becomes materially different when governance is expected to control whether consequence may occur rather than merely explain or review it afterward.
AI Cornerstone has placed a specific runtime-governance proposition into an attributable institutional record and agreed to subject that proposition to bounded demonstration.
That progression matters:
Declare the architecture.
Preserve its boundaries.
Freeze what will be tested.
Admit the evidence.
Run the governed scenarios.
Preserve what actually happened.
The value of the record is not that registration proves the architecture works. The value is that subsequent evidence and findings can now be compared against a preserved declaration without silently changing what was originally claimed.