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Pave: Real-Time Compensation Intelligence for Growing Companies

The Challenge

For HR leaders at companies with 100 to 500 employees, compensation management often exists in an uncomfortable middle ground. You've outgrown the ad-hoc approach that worked when you had 30 people, but you're not large enough to justify the enterprise tools and dedicated comp teams that big corporations deploy. The result? Spreadsheets. Lots of them.

The typical scenario involves a compensation manager maintaining unwieldy files for salary benchmarking, manually cross-referencing outdated survey data, and spending weeks each year just getting through merit cycles. Meanwhile, candidates are comparing your offers against real-time market rates, and your best performers are fielding recruiter messages with fresh compensation data you can't easily match. The gap between how quickly the market moves and how slowly traditional comp processes operate creates real business risk—lost hires, preventable turnover, and pay decisions made on gut feel rather than current intelligence.

How Pave Approaches It

Pave's core premise is that compensation data shouldn't be a static report you purchase once a year. Founded in 2019 by Matt Schulman, a former Facebook engineer who watched colleagues struggle to understand their own pay, the platform aggregates real-time salary and equity data from over 8,000 companies through direct integrations with HR systems. When you connect your HRIS to Pave, you contribute anonymized data to the pool and gain access to continuously refreshed benchmarks—a "give-to-get" model that keeps the dataset current in ways annual surveys cannot.

The benchmarking data covers base salary, bonuses, and equity across more than 200 job families, with geographic adjustments for U.S. metros and 50-plus countries. Rather than telling you what senior engineers earned 18 months ago when a survey was conducted, Pave shows you what companies are actually paying right now. The platform uses machine learning to map your internal job titles to standardized roles, reducing the manual matching work that traditionally consumes days of HR time.

Beyond data, Pave provides the operational tools to act on that intelligence. The platform handles pay range management, merit cycle planning, and approval workflows in one system. Managers can see their team's compensation relative to market and internal bands without digging through the HRIS. The total rewards portal gives employees a clear view of their full package—salary, equity, and benefits—addressing the common problem of people undervaluing what they actually receive. For recruiting, visual offer letters present compensation in a format that helps candidates understand the complete picture, including potential equity growth.

The integration ecosystem is notably broad, connecting with systems like Workday, BambooHR, Rippling, Greenhouse, Lever, Carta, and dozens of others. A 2024 partnership with UKG expanded this further for companies on that platform. The practical effect is that Pave can serve as a compensation layer that sits across your existing HR stack rather than requiring you to rip and replace anything.

Who It's Built For

Pave's sweet spot is mid-market companies in growth mode—typically Series B through pre-IPO, though the customer base includes public companies like Affirm and HubSpot. The common thread is organizations that have enough headcount to need formal compensation structure but haven't yet built (or don't want to build) the infrastructure that enterprises maintain internally. If you're hiring a Head of People, implementing your first real HRIS, and realizing that your salary data from last year's Radford survey is already stale, you're in the target profile.

The platform is strongest for North American companies, particularly those competing for tech talent. While Pave has expanded its international data, companies with primarily European or APAC workforces may find regional competitors like Figures or Ravio offer deeper local coverage. The ideal Pave customer is a U.S.-based company, likely in tech, fintech, healthcare, or another sector where talent competition is intense and pay transparency expectations are rising.

What Customers Are Saying

User feedback on Pave skews remarkably positive—the platform holds a 4.7 out of 5 rating on G2 with no reviews below three stars. The consistent themes are ease of use and responsive support. One compensation director noted she uses Pave "multiple times a week—anytime I want to look up a range or an employee's package" because "Pave's UI is so much more user friendly" than navigating her HRIS. Another reviewer described the customer success team as "phenomenal—they feel like an extension of our own team."

The operational results customers cite are specific. Workato reported cutting their benchmarking and pay range process from 10 weeks to 3 weeks after implementing Pave, and closed their subsequent merit cycles on time for the first time. At The Krazy Coupon Lady, a media company that rolled out Pave's total rewards portal, 93 percent of employees said they had a better understanding of their total compensation afterward. Affirm credits Pave with making their industry-leading pay transparency program possible. The pattern across testimonials is that Pave helps companies move compensation from an administrative burden to something they can actually execute well.

Getting Started

Pave offers a free tier called Market Data Launch that provides baseline U.S. salary and new-hire equity benchmarks in exchange for connecting your HRIS and contributing to the data pool. This lets smaller companies access real-time market data without cost, though the full platform—including planning tools, global data, and total rewards features—requires a paid subscription. Pricing scales by employee count and modules selected, with annual contracts standard. Pave does not charge per seat, so you can roll it out to all managers and employees without per-user fees.

Implementation typically takes 8 to 12 weeks, with Pave's team handling integration setup, job mapping, and configuration. Customers consistently describe the process as organized and well-supported, a contrast to the lengthy implementations associated with enterprise HR systems.

Key Takeaway

For mid-market HR teams tired of making compensation decisions with stale data and spreadsheet processes, Pave offers a modern alternative that combines live market intelligence with practical workflow tools. The platform won't solve every compensation challenge—global data depth varies, and advanced analytics like pay equity modeling require other tools—but for companies ready to professionalize their comp function without enterprise-level complexity, Pave has built a focused solution that customers genuinely seem to like using.

Learn more at pave.com