THE OPERATING GRAPH FOR THE AI TRANSITION
A live AI interviewer starts with the CEO, maps work and decision authority, then cascades through verified reporting lines—turning human context and approved evidence into an implementation-ready operating graph.
THE CATEGORY WEDGE
Screen and system traces are valuable evidence. They do not, by themselves, prove who has authority, which policy governs a decision, whether a workaround is legitimate, or what should happen in a rare exception. Company Brain triangulates employee explanation, approved documents, and selected system evidence.
Start with leadership, follow verified reporting lines, then resolve the cross-functional relationships that make real work happen.
Attach owners, approval thresholds, policies, permissions, exceptions, escalation routes, outputs, and definitions of done.
Detect conflicting accounts, missing ownership, and unexplained handoffs—then ask the person best positioned to resolve them.
Package the current process, decision rules, integrations, access needs, evaluation cases, success metrics, and unresolved risks.
Verify explanations against approved documents, system events, and privacy-preserving desktop observations—with redaction and employee controls.
Maintain agent owners, permissions, approval gates, evaluations, incidents, reversibility, and measured outcomes in the same graph.
WHERE WE START
Observation-first products scale fastest when work is frequent, digital, repeatable, and performed inside approved applications. Our entry wedge is the inverse—not because those tools are weak, but because the missing context is most economically important here.
THE COMPOUNDING ASSET
Employee corrections, implementation decisions, agent failures, exceptions, and measured outcomes return to the graph. The first ranked roadmap is designed to arrive in five days; each delivery then becomes evidence for the next.