Wage compliance
Federal, state, county, city, and rooftop-precision minimum-wage rules — operationalized inside your workforce systems. Bulk evaluation, streaming alerts, citation-backed audit trails, and pre-payroll review workflows. Built for distributed national employers, -driven recruiting teams, payroll providers, and PEOs.
The problem
Existing wage providers sell jurisdictional data. They do not operationalize that data inside your , ATS, or payroll workflows. The operational burden — bulk review, streaming alerts, jurisdictional override resolution, future-increase impact analysis — remains manual.
External
Federal floors, 50 state floors, ~150 local ordinances (Seattle, NYC, SF, Louisville, Flagstaff…), tipped-worker variants, healthcare-worker variants, scheduled future increases, ballot-initiative ramps. Most organizations track this by spreadsheet, by consulting newsletter, or by hoping their payroll vendor handles it. None of those scales past a few thousand workers across a few dozen locations.
Internal
Payroll cycles approach with nagging "did we miss anything?" energy. Recruiters worry whether the offer they just sent is legal at the candidate's location. Comp teams discover after the fact that a band's floor doesn't actually clear the local minimum. Audit-time means assembling evidence from sources nobody trusts.
Philosophical
Most "wage-compliance" vendors sell data. The lookup is a solved problem; the workflow around the lookup isn't. Organizations should not need entire manual processes — research, joining, alerting, reviewing — just to determine whether employees are being paid legally. The data should drive the workflow, not the other way around.
Scale
A vendor that asks you to query one location at a time is fine when you have 10 offices. It's untenable when you have 10,000 employees across 1,500 ZIP codes. Bulk evaluation, scheduled monitoring, streaming alerts, and explainable audit trails are not nice-to-haves at that size; they're the entire product.
The plan
Upload a CSV / Excel roster or connect your , , or payroll system. The platform resolves employee locations and identifies applicable jurisdictions through the federal / state / county / city hierarchy.
The system evaluates current wages against the applicable minimum, surfaces upcoming scheduled increases, applies jurisdictional overrides, and estimates workforce impact — all from one operational workspace, with every evaluation backed by citation-traceable rules.
Your payroll / HR / comp / recruiting teams receive compliance alerts, review queues, exportable remediation reports, future-increase warnings, and audit-ready evaluation traces. No more one-location-at-a-time lookups.
How we use AI
Tracking US local-ordinance wage rules used to mean a law firm or consultancy with a quarterly research cycle. Our AI ordinance extractor compresses that work to minutes — but every extraction lands in a human-review queue with citation + confidence before becoming canonical. AI moves the bottleneck from "research time" to "review time."
The critical posture: the AI extractor operates on public ordinances and government sites only. Your HRIS rosters, individual compensation records, and workforce evaluations never enter a model prompt. Compliance evaluation is a deterministic Postgres lookup against canonical jurisdictions the AI helped build — the model contributed to building the rule graph; it does not see your data when the graph is queried.
On precision and what's shipping when
Today the resolver applies federal/state/county/city tiers at postal/ZIP fidelity on the seeded rule corpus in this deployment (see DOL + state jurisdictional artefacts in-repo). Narrow sets of municipalities still require finer-than-ZIP granularity; those workloads surface explicit precision flags ahead of PAT-89 rooftop ingestion.
Rooftop precision for the carve-outs enumerated in roadmap + review-queue artefacts (examples called out publicly: NYC payroll districts, Louisville Metro variants, Cleveland / Cuyahoga overlays, Philly wage-tax bands, tracked Ohio CBSAs) lands with PAT-89 ingest — not an open-ended someday promise.
Capabilities
Bulk review, streaming alerts, integrated workflows, citation-backed audit trails. Designed for organizations operating across hundreds of jurisdictions.
Review your entire workforce against applicable wage rules from one operational table — sortable, filterable, exportable, drill-down to the jurisdiction chain + applied rule + source citation per worker.
Connect Workday, BambooHR, Greenhouse, or upload CSVs directly. Normalization happens through the toolbox's canonical-field engine — no per-vendor field-mapping consultancy required.
Resolve federal, state, county, city, and rooftop-precision rules with explainable jurisdiction traces. Every applied rule names its source, its effective date, and its confidence.
Alerts fire 90 / 30 / 7 days before announced wage changes activate — Seattle, NYC, California's annual indexing, NCSL-tracked pending legislation. Plan the payroll impact before it lands.
Built for payroll, comp, HR ops, and recruiting workflows. Assign, comment, approve, export. Pre-payroll-cycle review without bypassing the human-in-the-loop.
Every evaluation includes the applied rule, the jurisdiction chain, the effective date, the source confidence, and an audit-ready evaluation trace. The decisions are reviewable in the same shape an auditor would ask them in.
Built for
What's coming
The same rule engine extends without rework to overtime thresholds, paid-leave mandates, pay-transparency requirements, and local payroll-tax districts. The jurisdictional graph + the temporal-versioning + the AI extractor + the workforce-evaluation pipeline all generalize. You don't replatform when the regulatory landscape adds a new requirement.
International expansion (UK, Canada, Australia, EU member states) ships from the same engine on the same contracts. Same posture, same audit trail.
Most conversations we have with payroll and compliance leaders start with the same question: "What's the scope of my exposure right now?" Bring a roster, we'll tell you. The demo walks through your data + the rule graph; you decide whether the operational layer is something you want to bring in-house.