Pave AI features and pricing (November 2026)

Pave is a US compensation management platform for HR and total rewards teams, built around real-time market data from thousands of connected companies. It combines salary benchmarking, compensation planning, and an AI agent that automates parts of the merit cycle.

Pave is a compensation management platform headquartered in San Francisco, serving more than 9,000 connected companies according to the vendor, including large employers such as McDonald's, DoorDash and Zoom. The core product delivers real-time market benchmarks sourced directly from customers' HRIS, ATS and equity systems rather than annual surveys, alongside compensation planning for merit cycles, a manager-facing team view with compa-ratios, and a total rewards portal for employees.

The Pave Agent sits across these modules and automates workflows such as market pricing and merit cycle simulation. Pricing is USD-based, and a free Market Data Lite tier covers basic US benchmarks.

• Automates merit cycle simulationThe Pave Agent runs merit cycle scenarios grounded in a company's own compensation data and philosophy, combined with Pave's market benchmarks from connected companies. Compensation teams can test several scenarios before committing budget, rather than modeling each one manually in a spreadsheet, according to the vendor.
• Prices jobs from real-time market dataPredictive machine learning analyzes compensation data pulled continuously from participating companies' HRIS and ATS systems to suggest salary ranges and equity targets for a role. Compensation teams get market-priced ranges without submitting a manual survey or waiting for an annual refresh.
• Flags flight risk in team pay reviewsAs part of Pave's agentic workflows, Team View combines compa-ratio and market data to highlight employees whose pay may be falling behind the market during a compensation cycle, according to the vendor. Managers see which reports carry higher flight risk before finalizing merit decisions, instead of discovering pay gaps after someone resigns.
• Answers compensation questions via MCPPave connects to external AI tools through the Model Context Protocol and APIs, so a company's own assistants can query its compensation data and Pave's market benchmarks under permission-based access controls. HR teams get compensation answers inside other tools instead of switching into Pave for every question.

• Market data is sourced continuously from connected companies' HRIS and ATS systems rather than annual survey submissions.
• Free Market Data Lite tier covers US benchmarks; broader global and equity data sits behind paid tiers.
• Pave Agent integrates via the Model Context Protocol, letting other AI tools query compensation data under permission controls.
• Pricing and reference customers are US-focused, with benchmark coverage extending to 60-plus countries in paid tiers.

Headquartered in San Francisco per independent company data, with USD pricing and reference customers such as McDonald's, DoorDash and Zoom based in the US.

Confirm which modules and countries your quote covers, since the free Market Data Lite tier covers the US plus one additional market. Pave's flight-risk flagging in Team View evaluates individual employees' pay position and retention risk, so decide who sees those flags and how they feed pay decisions. Illinois bans AI that discriminates by protected class, including through proxies like zip codes, and California's CCPA covers employee data like consumer data.

• No federal employee privacy law, a state patchwork instead
• NYC requires bias audits for AI hiring tools
• Illinois bans discriminatory AI in employment decisions

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