Est. 2026 · Bellevue, WA

CRAIG ROAD

Intelligence you can defend.

“You bring the AI model. We bring the audit trail.”

Craig Road builds the harness that converts frontier AI model output into intelligence that holds up to LPs, trustees, counsel, and regulators. Customers bring whichever frontier AI model they prefer; Craig Road brings the audit trail, the confidence calibration, the multi-AI-model verification, and the atomic retraction. The same harness underwrites two product surfaces — AI-led diligence engagements for venture funds and the institutions that back them, and licensed AI infrastructure for enterprises whose AI decisions have to be defensible by construction. Epistemic sovereignty for the AI age — the firm owns the AI model layer, the audit chain, and the judgment.

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I Diligence Practice · Engagement-priced

Diligence for venture funds and the institutions that back them.

Engagements for venture funds running diligence on a target company, and for pension funds and other limited partner allocators running diligence on the managers they back. The principals bring multi-decade experience on both sides of that conversation — having allocated capital to venture from pension fund of funds, and having operated across deep technology, commercial fundamentals, governance, ESG, DEI, life-cycle assessment, and cross-border operating risk. Every engagement runs on the same infrastructure described below: factual claims are verified against source by multi-AI-model agreement before they enter the deliverable, retracted sources propagate through every downstream reference, and transcripts and source chains are deliverable in a form fiduciaries, trustees, counsel, and regulators can audit.

Confidence is scored, not assumed. Every finding carries a six-signal score; the system knows when it doesn’t know.

No. Signal Weight Method
I Source verification 30% Traceability to primary source documents
II Independent corroboration 20% Multiple analytical pathways converge
III Cross-reference validation 10% Consistency across documents in the data room
IV Logical consistency 15% Conclusion follows from established facts
V Relationship integrity 10% Consistent with known structural relationships
VI Uncertainty detection 15%* Disagreement between pathways lowers confidence and flags for human review
Total 100%

*Inverse-weighted · Weights configurable per firm and per sector

II CCR Infrastructure · Usage-priced · v1.0.0-alpha.1

Production-deployed AI infrastructure.

The infrastructure that makes Craig Road’s diligence defensible is the same system deployed today inside customer environments as a standalone product. Every AI model call from the firm passes through one connection point the firm owns. Calls are observed under firm policy and routed to whichever frontier AI model the firm chooses — commercial frontier AI models or open-source AI models running in-house. Every claim is verified by multiple AI models in agreement before it lands in the customer’s knowledge base; wrong-but-confident answers are blocked at the gate. Provider credentials never leave the infrastructure layer. Every action lands in a tamper-evident audit log scoped to the customer organization, queryable in one line.

Token spend on enterprise workloads drops by a measurable margin once traffic switches over. The capability gain is larger than the cost gain: workloads that exceed the upstream API ceiling — long codebases, document corpora at scale, sustained sessions — become tractable when they previously broke. The demonstration is five minutes on the customer’s own corpus.

Deployed today across three topologies, sized to the operator:

No. Topology Footprint Audience
i Native · Apple Silicon Local Individual operators · runs on the laptop
ii Hosted · Cloud Run Per-use Small teams · thin-client deployment
iii Single-VM Compact Single-tenant · cost-predictable

Released as v1.0.0-alpha.1 · Two production customers

III Engagement Four shapes · Across both surfaces

How we engage.

Four shapes across the two surfaces. Services price per engagement; infrastructure prices on usage.