For enterprise fitness and wellness real estate teams

Open clubs faster, and hold the line on occupancy cost.

REAL runs AI agents across site selection, buildouts, facilities, leases, and property tax, so expansion moves fast and occupancy cost stays under control.

14% average cost reduction across enterprise portfolios.

Portfolio agentsLive
  • Site selection
  • Construction and CapEx
  • Lease and CAM
  • Property tax

Trusted by industry leaders

The Aspen Group
DCA
Mall of America
CVS Health
Summit Properties USA
The Aspen Group
DCA
Mall of America
CVS Health
Summit Properties USA
The Aspen Group
DCA
Mall of America
CVS Health
Summit Properties USA
The Aspen Group
DCA
Mall of America
CVS Health
Summit Properties USA
Premium fitness gym interior with well-spaced equipment

In your portfolio

14% average cost reduction across enterprise portfolios.

See it on your locations

Outcomes

Why fitness teams choose REAL

Ground every club site in data

Candidate markets scored on demographics, competition, traffic, and unit economics, so the next club rests on more than a hunch.

Keep buildouts on budget

Every line priced against your own delivery history, so the estimate holds from bid through opening.

Recover CAM in retail centers

Every charge matched to the lease, so overpayments surface.

Audit the tax on every club

Assessments and pass-throughs checked for overcharges.

The shift

What changes with REAL

Today

With REAL

  • Club sites chosen on instinct and a broker's read

    Candidate markets scored on demographics, competition, traffic, and cost

  • Buildout budgets set from the last club's number

    Every line priced against your own delivery history

  • CAM in retail centers paid without a close check

    Every charge matched to the lease, overcharges recovered

  • Tax pass-throughs accepted as billed

    Assessments and pass-throughs audited for overcharges

The agents

The agents on your fitness portfolio

Site selection

Scores candidate markets on demographics, competition, traffic, and unit economics, so an expansion decision has data behind it.

Construction and CapEx

Reads plans and change orders across every buildout and holds budget to your own delivery history.

Lease and CAM

Abstracts leases, tracks critical dates, and reconciles CAM across your retail-center locations to recover leakage.

Property tax

Audits assessments and pass-throughs to reduce what each club pays.

Facilities

Reads condition across clubs and prioritizes equipment and capital before a failure closes a floor.

1.2B sq ft

of enterprise real estate analyzed

14%

average cost reduction

8M+

tasks processed across portfolios

Matthew DeSilva
REAL has become a strategic agentic partner for CVS, helping our team recover value, move faster, and execute more intelligently.
Read the CVS Health story

Matthew DeSilva

Executive Director, Real Estate, CVS Health

CVS
Benjamin Bragdon
REAL does our CAM reconciliations in the background while our team focuses on larger priorities that push the company forward.
Read the Aspen Group story

Benjamin Bragdon

Director, Real Estate Systems and Lease Admin, The Aspen Group

The Aspen Group

Integrations

Works on top of your existing accounting and property systems, so your team keeps its tools and gains the execution.

Questions

Frequently asked questions

  • Yes. The site selection agent scores candidate markets on demographics, competition, traffic, and cost, so an expansion decision has data behind it.

  • Yes. The CAM agent matches each charge to the lease and recovers overcharges, and the tax agent audits assessments and pass-throughs for overcharges.

  • It reads your plans and prices every line against your own delivery history across clubs, so the estimate holds from bid through opening.

  • REAL is SOC 2 Type II and ISO 27001 certified, single-tenant, and never uses your data to train shared models.

Ready to open clubs faster with AI agents on your portfolio?

Enterprise security, built in

  • SOC 2 Type II
  • ISO 27001
  • Single-tenant architecture
  • Your data never trains shared models
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