Investor brief · October 2026
The AI-native agency for vacation rental revenue

We don't sell revenue software. We run the revenue function.

Pacer is the embedded, AI-enabled revenue management function for short-term rental operators. We price and yield every unit, every day, on the tools operators already run, and we own the RevPAR outcome. AI does the work. Our revenue managers handle judgment and relationships.

~$1.9M ARR
Nearly $2M in annual recurring revenue, about $161K MRR.
As of August 2026.
+18%
First-year RevPAR lift, pooled across first-year clients.
Same-store Adj. RevPAR, Key Data methodology. No mix shift.
600 → 44K+
Vacasa homes. Jon Latorre helped scale it before founding Pacer.
Founder and CEO.
What Y Combinator is calling for

YC's Summer 2026 Request for Startups asks for "AI-Native Service Companies."

"Instead of giving you a tool, they just do the work."

Y Combinator, Requests for Startups (Summer 2026)

"The total spend on services is many times larger than the spend on software. And a lot of these services are already outsourced, which makes them much easier to replace with an AI-native product."

Y Combinator, Requests for Startups (Summer 2026)

The thesis, as laid out in "Why Y Combinator Is Betting on AI-Native Agencies," is that AI handles the repeatable operating layer of the work while senior operators govern strategy, exceptions, and accountability. The company sells finished outcomes, not tools. The result is professional services at software-like margins, because AI breaks the linear relationship between headcount and revenue.

Pacer is that company for a specific, large, already-outsourced job: revenue management for vacation rentals and boutique hotels. The pages that follow map our model to the thesis point by point, show how margins expand as AI takes on more of the work, and explain why the agency model is our edge.

Pacer Systems, Inc. · pacerrev.comConfidential draft · 1
Why Pacer fits the thesis
The thesis, point by point

Every line of the AI-native agency thesis already describes how Pacer works.

The thesisPacer
Sell the serviceDon't give the customer a tool. Do the work. Pacer is an embedded revenue function, not another tool to log into. We hold PMS and pricing-tool access, so we execute, not just recommend: rates, minimum stays, fees, promotions, OTA programs, distribution mix.
Replace, don't improveTarget services that are already outsourced. Operators already pay for pricing tools and underuse them. Tools still need someone to run them. We replace that missing revenue team, on any pricing tool, with no migration.
AI does the repeatable layerHumans govern strategy, exceptions, accountability. AI handles routine diagnostics and reporting. The revenue manager owns the strategy, approves the price, and stands behind it. Someone has to own the outcome. That is us.
Break the headcount linkThe next client adds minimal marginal cost. One system pulls PMS, pricing, and market data together and flags what needs attention across the portfolio each morning. Revenue managers spend time on decisions, not rebuilding reports.
Data flywheelEvery engagement makes the system better. We see many portfolios across many platforms, plus years of what actually worked in each market. A general model can't be trained on data it never sees.
Ride the model curveBetter, cheaper AI widens the margin. Every better model makes our revenue managers faster and lowers our cost to serve. The labs are effectively funding our R&D. New pricing-tool agents plug into our workflow too.
Less key-person riskKnowledge lives in systems, not heads. Strategy, history, and benchmarks live in our platform and the Pacer Portal. Director-level oversight on every portfolio.
How the model works

AI does the work. People handle judgment and relationships.

What AI and the platform do

  • Pacing, pickup, and demand signals, updated daily
  • Morning flags on what needs attention, across every portfolio
  • Unit-level performance, same-store and prior-year, beside market benchmarks
  • Listing quality scored per unit; AI-written photo captions
  • Owner-ready performance decks and per-owner review views

What our revenue managers do

  • Approve and stand behind every pricing call
  • Set fee, cancellation, promotion, and OTA program strategy
  • Handle exceptions: demand shifts, events, soft markets
  • Run biweekly strategy calls and quarterly business reviews
  • Own the client relationship and the result
Pacer Systems, Inc. · pacerrev.comConfidential draft · 2
Margins and scale
The margin and scale story

Margins expand as AI takes on more of each revenue manager's work.

Our main cost is revenue-manager time. Our price is per unit under management, not per hour. So every task AI absorbs becomes more units per revenue manager at the same quality, and headcount grows only with the judgment the work needs.

01
AI absorbs routine work

Monitoring, diagnostics, and reporting move to the platform.

02
Each RM covers more

Freed hours go to more units and better decisions.

03
Revenue per RM rises

Per-unit pricing tracks units, not hours.

04
Margin widens

Shared platform cost. Better models cut cost to serve.

The path to software-like margins

Three stages. The human share of the work falls at each one.

Today
AI-enabled team

AI handles routine diagnostics and reporting. Revenue managers make and execute every call. The Portal adds visibility, not headcount.

46% gross margin (Aug 2026). Direct labor per billed unit $17.45, down from $30.57 in Dec 2025.
Next · FY2027
AI drafts, humans approve

The platform proposes rate, stay, and promotion changes. Pricing-tool agents plug in. White-label owner reporting ships. RMs approve.

Target: 55% gross margin in FY2027 at 800 units per RM, exiting the year at 57%.
Then · FY2028
AI runs, humans govern

Routine execution runs inside guardrails each RM sets. People own strategy, exceptions, accountability, and the relationship.

Target: 65% gross margin in FY2028 at 1,000 units per RM.
The numbers that show it
Gross margin by quarter
53 → 19 → 38 → 32 → 44%Q3 2025 to Q3 2026. The Q4 2025 dip was a hiring step, since recovered.
Units per RM
536 billed units per RMUp from 308 in Dec 2025 and 498 a year ago. 52 units per client vs 42.
Revenue per RM
$243K recurring per RMUp from $157K in Dec 2025. Flat vs a year ago on 45% more RM capacity.
Cost to serve
Down 43% since DecemberDirect labor per billed unit, $30.57 in December to $17.45 in August.
Retention
19 mo average tenure, rising83 clients billed vs 65 a year ago. Largest client is 6.4% of MRR.
Growth
+46% ARR YoY$1.33M to $1.94M (August basis). Billed units +56%. FY2025 revenue +59%.
The article behind YC's thesis puts achievable gross margins for AI-native agencies at 65 to 80%, against 20 to 35% net margins for traditional services. Our job is to move along that curve with every model release and every platform feature, and we built the business so that each one does.
Pacer Systems, Inc. · pacerrev.com · Financial metrics: Summary Financials & Metrics, August 2026 close basis.Confidential draft · 3
Why the agency model wins
The service is the moat

The managed service is a feature, not a bug.

Software vendors sell a tool and hope it gets used. We sell the result and do the work. That position gives us four advantages a pure software company can't easily copy.

Distribution
Partners send operators to us, not around us.

Exclusive RM Partner of Key Data. Integration Partner of Track, Guesty, and Streamline. We run on PriceLabs, Wheelhouse, Beyond, and RevMax, so pricing-tool vendors gain when we grow. A free portfolio audit opens every relationship.

Retention
We are embedded in daily operations.

We hold PMS and pricing-tool access, run the daily cadence, and power the Portal clients and their owners rely on. Contracts are month-to-month, so retention is earned every month. 83 clients billed, up from 65 a year ago, with a 19-month average tenure that keeps rising.

Data moat
We see what no single tool or model can.

Software sees one operator on one platform. We see many portfolios across many platforms in 50+ markets across 7 countries, and spot a demand shift across all of them at once. That data compounds with every engagement.

Outcome pricing
Sold on results. Priced on the portfolio.

We own the RevPAR outcome and prove it with same-store numbers. Simple per-unit monthly pricing means revenue grows as clients grow, while our cost to serve each unit falls.

Why we win
vs. AI labs

They sell the engine. We sell the finished result. A messy vertical with PMS integrations and owner reporting is not their business.

vs. pricing software

Tools need someone to run them. Owning outcomes would mean competing with the agencies that bring them customers.

vs. Airbnb pricing

It optimizes one channel. Operators price across Airbnb, Vrbo, Booking.com, and direct through their PMS.

vs. hiring in-house

Enterprise revenue discipline, a full platform, and director oversight, with no hire to recruit or replace.

Team
600 → 44K+ Vacasa homes, scaled
Jon Latorre, Founder and CEO

Early Vacasa revenue leader. Helped scale Vacasa from 600 to 44K+ homes across 16 countries, leading a 55-person team managing $2B+ in revenue across 100+ acquisitions.

Pacer's revenue team is led by operators from Vacasa, Vail Resorts, Inspirato, and VTrips.

Traction

  • ARR +46% YoY with the same eight RMs since April. Gross margin back to 46% from 19% in Q4 2025.
  • Nearly $2M ARR, about $161K MRR, as of August 2026
  • +18% first-year RevPAR lift, pooled, same-store, Key Data methodology
  • 50+ markets across 7 countries: beach, mountain, lake, urban, resort
  • Integrated with Guesty, Track, Streamline, Hostaway, Hospitable, Hostfully, OwnerRez, Escapia, and more
Services-sized market. Software-like margins. Pacer does the work, and AI makes each revenue manager go further every quarter.
Jon Latorre, Founder and CEO · [email protected] · pacerrev.com
Pacer Systems, Inc. · Figures as of August 2026. RevPAR lift is same-store: units under management in both the current and prior-year periods. Financial metrics: Summary Financials & Metrics, August 2026 close basis.4