Everything an HR generalist needs to build compliance-ready salary ranges — without a comp analyst on staff.

What it does: Type any job title — "Marketing Manager," "Software Engineer," "Registered Nurse" — into the occupation search. Salary Range Builder queries BLS Occupational Employment and Wage Statistics (OEWS) data for US occupations or Statistics Canada NOC data for Canadian occupations and returns the median, 10th percentile, and 90th percentile wages for your selected state or province within 500 milliseconds.

Why it matters: The BLS OEWS national and state-level CSV files contain 800,000+ wage data points. Navigating them manually — downloading the spreadsheet, identifying the correct SOC code, cross-referencing the correct geographic table — takes 30–90 minutes per occupation. The typeahead search eliminates that entirely.

Compliance value: BLS OEWS data is public domain, zero cost, and cited in EEOC enforcement guidance. It is the same data that large employers use for internal benchmarking. Using it as the basis for your salary ranges is legally defensible in enforcement proceedings — and the data vintage watermark on every PDF export proves exactly which release you used.

What it does: A horizontal bar chart showing min/mid/max per role, color-coded by pay grade. Compare up to 5 roles side-by-side. The midpoint is anchored with a Burnished Brass marker so you can immediately see where each role falls relative to market median.

Why it matters: Visual comparison makes internal pay equity immediately obvious. If the Software Engineer L3 range overlaps significantly with Software Engineer L4, you have a compression problem. If two roles with identical market medians have materially different range spreads, you need a documented rationale. The pay band visualization surfaces these issues in seconds.

What it does: Every range view, export, and modification automatically generates an immutable timestamped audit log entry. The log records the organization ID, user ID, role, action type, range values at the time of the action, BLS or Statistics Canada data vintage date, and timestamp. Exportable as CSV with a date range filter. Retained 3 years by default.

Why it matters: In an enforcement action, the question isn't just "do you have a salary range?" It's "can you prove what range you posted, when you posted it, and what data you used to calculate it?" The compliance audit trail answers all three. It's the product's primary legal defense documentation artifact — and it's the feature that most enterprise tools treat as table stakes but that no sub-$500/month tool has provided to SMB HR teams.

What it does: Create separate Tier 1 metro, Tier 2 mid-market, and Remote range configurations. BLS geographic differentials are applied automatically from state-level OEWS data. Each range set generates its own compliant PDF export with the correct state disclosure statement.

Why it matters: A company with employees in Seattle, Chicago, and remote-only positions needs three different salary ranges for the same role. Setting this up manually — and keeping three spreadsheets synchronized — is exactly the kind of error-prone complexity that creates pay equity exposure. Location-based range sets solve it in a single workflow.