The AI compensation platform

Build, customize, and scale AI agents that manage every compensation workflow

Built directly on the world’s largest real-time dataset of 9,000+ integrated Pave clients

Take control of your company’s largest expense

The average 10,000-person company in Pave’s dataset spends $2.68 billion a year on its people. Pave helps you deploy that budget with confidence and build credibility with every stakeholder.

Market Data

Access real-time compensation benchmarks and workforce insights from 9,000+ integrated Pave clients. No manual survey submissions required.

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Market Data Pave’s data compositionLearn more
Product Management All levels
Product Management
US — United States Tier 1 ▾Private & Public ▾Valuation: $1–5B ▾3 Comp Types ▾USD ($) ▾⚙ Equity Settings
LevelConsistency10th25th40th50th
P1Low$79,192$98,852$109,836$111,544
P2High$93,361$126,586$148,196$162,677
P3Very High$148,492$165,500$183,375$195,000
P4Very High$170,304$185,000$195,000$201,300

Agentic Workflows

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Move beyond spreadsheets by integrating all survey sources with Pave’s real-time data to create reliable pay ranges at every level. Agentically reprice your entire job architecture within days without starting from scratch.

Market PricingEngineering · P-trackLearn more
ProgressionsP1 → P2P2 → P3P3 → P4P4 → P5P5 → P6
Auto-smoothed23.1%24%24%25%30%
Original91.7%−13%0%----
Team ViewPlatform org · 34 peopleLearn more
PersonPosition in bandCompa
SC
Susie CollinsProduct · L5
1.04
MG
Milton GreenEngineering · L4
0.97
DR
Dina ReyesEngineering · L6
1.09
TK
Theo KimDesign · L4
0.88
PP
Priya PatelProduct · L3
1.01
JW
Jonah WeissEngineering · L5
1.06
AS
Ana SousaDesign · L5
0.99
ML
Marcus LeeEngineering · L3
0.91
Compensation PlannerFY26 merit cycleLearn more
AC
Aaron Collinsaaron_collins@gmail.com
DDYDZHAG
TitleAI Researcher P5
LocationSan Francisco, USA

Aaron has a tenure of 4 years, with 35% of equity unvested. This cycle they rated 4 — Exceeds expectations — and are being promoted to M3 in Engineering. New compa ratio: 1.52, plus 2,100 units of new equity.

Summarized by Pave AI Beta
Comp HistoryActivityPeersUSDLocal
Compensation GraphOpen Total Rewards ↗
20222023202420252026
hooli
Welcome, Susie Collins!

Now you can see your entire total rewards package in Pave!

Job RoleVice President, Level 12
LocationSan Francisco
Tenure3 Years, 4 Months
ManagerHarmony Cobel
OverviewTimelineSalaryOptionsBenefitsToolsComp SimulatorLearning Hub
Overview
Your Annual Comp ⓘ$452,460
Salary$248,000
Target Bonus$62,000
Annual Option Grant$75,500
Benefits$66,960
Model the next 4 years by Share PriceValuation
1x3x5x7x10x
$10.00 (1x)
Annual Compensation$452,460
Visual Offer LetterSent 2 hours agoLearn more
hooli
Congratulations, Monica!

We’re excited to present this offer to join Hooli as a Software Engineer — here’s your total rewards package.

Job RoleSoftware Engineer, P3
LocationSan Francisco
Start DateAug 1, 2025
ManagerGavin Belson
OverviewTimelineSalaryOptionsSigning BonusBenefits
Overview
Your Annual Compensation ⓘ$230,000
Salary$150,000
Options$50,000
Signing Bonus$20,000
Benefits$10,000
Your Annual Comp$230,000

Pave Agent

Transform weeks of manual compensation tasks into fully agentic workflows. All securely powered by your company’s structured comp data alongside Pave’s proprietary real-time dataset.

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Your AI is only as good as the data you feed it

Make Pave your compensation system of record to unleash the potential of agentic AI in a secure and protected platform. Eliminate the privacy and security risk of putting your company’s sensitive compensation data into Claude.

Chronosphere 4× Headcount growth,
zero benchmark lag
Reddit

"Benchmarking 3,000 roles used to take a full quarter. With Pave we did it in two weeks."
Workato
92% Comp cycles automated
Checkr
Bands that match today's market
Refreshed continuously with Pave

"Our comp bands finally reflect what the market looks like today, not six months ago."

 SeatGeek Comp ops at SeatGeekWatch · 2:31
13M+ Offer letters analyzed
Reddit
SharkNinja

"Pave gave us real-time data during a hiring surge. We stayed competitive without overpaying."
Chronosphere
Checkr
Workato Workato × Pave — the filmWatch · 3:04
SeatGeek
9,000+ Companies in dataset
The Pave Films

Hear it from the teams

80%

of the Forbes AI companies are in Pave’s dataset—the market’s fastest-moving talent, benchmarked live.

Forbes AI 50 · 2026

“What I appreciate most about the Pave AI tool is that it acts as a thought partner for our compensation team.”

Brian Weigandt, Global Head, Compensation at McDonald’s

“Before Pave, configuring a cycle took about two months, relying on cross-functional support. Now with Pave, I can do it in a week.”

Hong Le, Lead, Global Compensation Programs

Reddit
4,000+

hours saved annually on the compensation planning process, based on internal estimates.
56%

Decrease in the share of workers aged 21–25 at public companies since 2023

“More and more, the people who submit to [traditional survey providers] are just not the people that I care about. All the companies I care about submit to Pave.”

Liz Thomas, Head of Total Rewards

Handshake
13% more

Senior ICs at top native AI companies relative to traditional tech—and 19% fewer junior employees

“We chose Pave because of the interface and the flexibility it gives our team… it’s a phenomenal product.”

Adra Long, VP of Total Rewards

Fanatics
7.8

Average direct reports for a VP/SVP at top native AI companies vs 5.1 at traditional tech

“With Pave’s Peer Groups, I can say exactly which companies are in the data which drives significantly more confidence.”

Lauren Weber, Sr Director of People Operations & Development

Cockroach Labs

Discover what’s new in compensation

Articles, guides, and events from Pave’s in-house comp experts, data science team, and partner network.

See your comp data come alive

Thirty minutes with a comp specialist. Bring your hardest question.