The trust and provenance layer for AI agent infrastructure.

Mission

Every decision an AI agent makes on behalf of a company should be as auditable as a board resolution. Axiom makes that possible — so the future of enterprise AI is trustworthy, not just capable.

Why this matters — and who's behind it

Before Axiom, there was AI.FO — a production AI system for finance that Joe McCann built from scratch as a solo, non-technical founder using Claude, Claude Code, and Cursor. The core insight wasn't about AI models. It was about the infrastructure that makes AI trustworthy in regulated environments.

AI.FO's architecture was deterministic-first: a computation layer with 2,000+ automated assertions, an audit-independent test harness, and sealed-snapshot releases. Every output was provably derived. Every number was traceable to its source. Not because the AI was smart — but because the infrastructure demanded it.

Joe spent 20 years as CFO and COO across nonprofits, education, and operating companies. He ran Federal Single Audits, managed GAAP compliance, designed ITGC controls. He spun out a $12M nonprofit from the Tides Foundation, building the entire financial, HR, and governance infrastructure from scratch — independently, on time, without fail.

That background made one thing obvious: AI agents in production enterprise environments are a compliance nightmare waiting to happen. No receipts. No provenance. No way to answer the question a regulator will ask: "What did the AI decide, and how?"

Axiom is the answer. We're applying the same trust architecture — deterministic computation, automated assertions, cryptographic attestation — to agent execution provenance. Every skill invocation gets signed before it runs. Not logged after the fact. Attested in advance.

What we're building

Axiom is the execution receipt layer for AI agent infrastructure. We sign every skill invocation before it runs — not logging afterward, but cryptographic attestation — so that when a regulator, auditor, or compliance officer asks what an AI decided and why, there's a receipt, not a guess.

The product: an infrastructure layer that MCP servers, company brain systems, and AI OS platforms plug into. The output: verifiable, auditable, legally-defensible execution records for every agent action.

Built for the compliance officer who has to answer to a regulator — not the engineer who wants better debugging.

Where we're headed

One thousand days from now, every AI agent in production enterprise environments runs on Axiom.