Pave

Benchmark pay, price jobs, build pay ranges, run merit cycles, and communicate total rewards in one end-to-end platform.

[Pave @pavecomp]

Compensation intelligence is more useful where you already work. Pave Agent now connects to Claude in two steps.

You can now find Pave Agent in Claude’s connector directory. Once it’s connected, you can ask Claude to:

→ Pull the latest Market Data benchmarks to reprice your pay bands

→ Compare last year’s merit cycle performance score distribution to market insights

→ Answer anything else you’d ask Pave Agent directly in Pave

Here’s how to set it up: https://t.co/iBR0QBakaG

[Pave @pavecomp]

Most companies are planning 2027 pay the way they planned 2026: 𝘀𝘁𝗲𝗮𝗱𝘆 𝗮𝗻𝗱 𝗰𝗮𝘂𝘁𝗶𝗼𝘂𝘀.

We partnered with Alpine Rewards to survey compensation leaders on how they’re budgeting for 2027. Three things stood out:

→ Merit budgets are holding at a 3.5% median in the US.

→ Hiring is cautious. Three in five companies expect headcount to grow, but a quarter are only hiring to backfill departures.

→ About 80% of companies post ranges on all US job postings, but employees mostly have to ask for theirs.

For more insights to help you plan, download the 2027 Compensation Budgets & Planning Report: https://t.co/Ntc58APmWq

[Pave @pavecomp]

The AI frontier is showing us where the labor market goes next. 👀

In this upcoming webinar, Pave breaks down what sets these companies apart, which roles have staying power, and who is winning and losing as AI changes how work happens.

November 10, 10am PT / 1pm ET. Save your spot 👉 https://t.co/MYIfp0dTPV

[Pave @pavecomp]

Either view gives your team a fuller picture for benchmarking, workforce planning, and hiring.

Read how it works: https://t.co/nh8cwwnQqD

[Pave @pavecomp]

Total Direct Compensation (TDC) is now live in Market Data Pro. 🎉

It's one of the most requested data points in Market Data, and the larger the company, the more it tends to matter.

[Pave @pavecomp]

TDC combines base pay, variable pay, and annualized equity, and you choose how equity is counted:

• Granted in the last 12 months, the view traditional benchmarks use
• Vested in the last 12 months, the view closest to what employees actually received

[Pave @pavecomp]

@Levelsfyi Compensation teams shouldn’t have to choose between the sources they trust. We’re building Pave to be the one place where all of them come together, and we’ll keep adding more.

Read the full announcement. https://t.co/QAkTvhHZ0t

[Pave @pavecomp]

Compensation decisions draw on more data than ever, and that data is scattered across surveys, spreadsheets, and tools.

Today, we’re announcing a strategic alliance with @Levelsfyi to bring their data into Pave Agent and Market Pricing. https://t.co/FW7CT3KpFG data is contributed directly by the people earning it and backed by proof documents like offer letters, W-2s, and pay stubs, so it shows what talent is actually earning.

[Pave @pavecomp]

Ever wonder what makes an AI recommendation actually trustworthy? 🤔

When SymphonyAI’s Total Rewards team started layering their data into Pave, they weren’t just looking for answers. They were building something smarter.

💡 Thank you, Leanne and the SymphonyAI team, for building with us.

[Pave @pavecomp]

Three years ago, Pave set out to build a community for Total Rewards leaders. Now look at this room!

From swapping AI experiments to leaning on each other through trial and error, TRL 2026 reminded us why the comp world is better together. 🤝

Thank you to everyone who joined us. We cannot wait for what’s next! ✨

[Pave @pavecomp]

Read the full Hot Jobs Index: https://t.co/gpARGjn5rP

[Pave @pavecomp]

🔥 Some of the fastest-growing roles in the market barely existed on org charts two years ago.

Pave’s Hot Jobs Index tracks the jobs on the rise across our real-time compensation data, and this quarter the shift is hard to miss.

[Pave @pavecomp]

📈 GTM Engineers went from showing up at 0.3% of companies in early 2025 to 3.2% today.

Swipe through to see which roles are taking off: AI Transformation Lead, GTM Engineer, AEO/GEO Specialist, and AI Product Manager. 👉

[Matt Schulman @Matthewschulman]

Getting comp right at @SymphonyAI means bringing data together from a lot of different places.

The more data you can layer into @PaveComp, the more the Pave Agent has to work with. Thank you to Leanne for sharing how SymphonyAI does it, both here and on stage at TRL.

[Pave @pavecomp]

Dig into the Q3 rankings 💰 https://t.co/mN4MDAcOei

[Pave @pavecomp]

Which jobs are the hottest in the market right now? 🔥🔥🔥

Our Q3 Hot Job Index is LIVE, ranking the roles in highest demand based on Pave data. Whether you’re planning headcount, setting pay, or building your hiring strategy, this is the pulse check you need.

[Pave @pavecomp]

Don’t miss your chance → https://t.co/dBOXXGzzzj

[Pave @pavecomp]

One day left to weigh in on the question every team is asking: what should our token budget be? 🤖

Our AI Token Use & Spend Policy Pulse Survey closes tomorrow, Oct 23. Complete it to get the full report and see how your approach to budgeting, governance, and measurement stacks up against the market.

[Zuhayeer Musa @zuhayeer]

Update. Got an anonymous tip that the first product designer at Ramp (within first 5 hires), received 0.25% over 4 years for their initial grant.

That’s ~24% under the low end I modeled for hire #5, so my estimates ran high. That 0.25% would be worth ~$28.5M at Ramp today.

I reached out to @Matthewschulman and @rithikaneti at @pavecomp, and they pulled their data on equity grants across US VC-backed tech companies (chart below).

Among the first 5 employees, 0.25% sits above the median (0.16%) but below the 75th percentile (0.42%). For a product designer in the first 5, it lines up almost exactly with the 75th percentile.

And more importantly, benchmarks for “founding” roles are a bit more of an art rather than a science this early in hiring, since grants can be ultra-specific to individuals and their worth to the organization.

It can change with role, seniority, stage, growth etc, so I wouldn’t treat it as prescriptive.

It’s also just a bet on the company from the candidate’s perspective, and sometimes employers will need to flex to close a stellar candidate.

Hope my post helped shed some light on what outcomes can look like at a high growth startup, post-dilution.

Some more exciting updates coming soon between @pavecomp + @Levelsfyi. This post sparked some awesome discussion, and there’s a lot of neat data between the two of our platforms 📊

[Zuhayeer Musa @zuhayeer]

Update on the Ramp equity grants for early hires. Got an anonymous tip that the first product designer at Ramp (within first 5 hires), received 0.25% over 4 years for their initial grant.

That’s ~24% under the low end I originally modeled for hire #5, so my estimates ran high. That 0.25% would be worth ~$28.5M at Ramp today.

I reached out to @Matthewschulman and @rithikaneti at @pavecomp, and they pulled their data on equity grants across US VC-backed tech companies (chart below).

Among the first 5 employees, 0.25% sits above the median (0.16%) but below the 75th percentile (0.42%). For a product designer in the first 5, it lines up almost exactly with the 75th percentile.

And more importantly, benchmarks for “founding” roles are a bit more of an art rather than a science this early in hiring, since grants can be ultra-specific to individuals and their worth to the organization.

It can change with role, seniority, stage, growth etc, so I wouldn’t treat it as prescriptive.

It’s also just a bet on the company from the candidate’s perspective, and sometimes employers will need to flex to close a stellar candidate.

Hope my post helped shed some light on what outcomes can look like at a high growth startup, post-dilution.

Some more exciting updates coming soon between @pavecomp + @Levelsfyi. This post sparked some awesome discussion, and there’s a lot of neat data between the two of our platforms 📊