Attestloop
An employment-AI evidence layer that inventories tools, correlates instrumented decision chains, records human review, and prepares jurisdiction-specific notices and assessments only from verified rules and observed events.
Employment decisions can pass through screening, scheduling, HRIS, messaging, performance, and compensation tools without one trace showing which AI feature influenced which outcome. Illinois now requires notice around AI use in employment decisions, but implementing rules are still developing, and the supplied input does not independently substantiate the exact California, Colorado, and Texas artifacts. Attestloop should capture only instrumented events, distinguish tool availability from actual use and influence, and produce reviewer-owned drafts rather than calling an integrity-protected log compliant or court-admissible.
The HR compliance, employment legal, people systems, or AI-governance lead at a 100-to-1,000-employee company using AI-enabled employment tools.
Illinois is active and other state signals create a current preparation window.
HR compliance, legal, and people systems own the evidence problem.
The input has extensive graph links but moderate grounded convergence.
A clear mid-market buyer, strong graph connectivity, a confirmed Illinois law, available observability primitives, and an unserved chained-attribution workflow support the direction.
Only one jurisdiction is independently grounded, rules are evolving, instrumentation is incomplete by nature, integrity is not legal sufficiency, and HR platforms can add native evidence.
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