Asset Management Intelligence for hotel owners and lodging REITs

AI for hotel asset management: review every property, every month. Catch cost creep and revenue leaks
with AI.

SquareShift builds AI for hotel asset management: five monthly reviews on your data and your rules. Your asset managers get the exceptions, not the spreadsheets.

Plan a proof of concept See the five reviews

The gap

Monthly reviews across every property

No team has time to run every review for every property after each close.

Five places the monthly review breaks at scale

  1. 01

    Revenue beats plan, but profit does not follow.

    Flow-through slips while the top line looks fine.

  2. 02

    Costs climb without a clear reason.

    Lines rise faster than the drivers explain.

  3. 03

    Share gains may not be profitable.

    Growth can hide unprofitable business.

  4. 04

    Pace drifts from forecast.

    Forecast checks reach some hotels, not all.

  5. 05

    Operator commitments fade between quarters.

    Last quarter's operator promises go untracked.

The five monthly reviews

AI for hotel asset management that runs your review rules on every property

Each review checks your data against your rules and returns one clear follow-up.

Asset management for hotels means reviewing each property after the monthly close. Hospitality asset management teams can use this workflow to see the exceptions across the portfolio.

How the review cycle works

We build AI agents that run your review rules on every property.

Your data and rules go in. Checked exceptions come out, inside your environment.

  • No upfront data overhaulStart on the data you already have. No warehouse rebuild, no big program.
  • Four-week planOne workflow, live on your data.
  • Yours through the build and beyondYou own it, run it, and extend it.
  • Your data, your environmentNothing leaves. Your access rules apply.

Source data

  • Data warehouse
  • Finance database
  • Budget and forecast workbooks
  • Operator P&L sheets
  • Operator review decks
  • Approved market data

Semantic layer

  • Cleansing and aggregation
  • Semantic model
  • Business layer with your definitions
  • Knowledge graph
  • SquareShiftBusiness context engineeringMakes your data make sense to AI

Review agents

  • Profit flow-through
  • Cost creep
  • Revenue and market share
  • Pace versus forecast
  • Operator follow-through
Runs on your rules

Review workspace

Exceptions only

Only what needs attention.

Asset manager action

Controls on every layer

  • Runs inside your environment
  • Approved data only
  • Your access rules
  • Every number traced to source
  • Your team keeps the decision

Start with one workflow. Extend the pattern from there.

See the four-week plan

I used to spend three hours across spreadsheets, decks, and queries to answer one question. Now I just ask it in chat.

It has even surfaced correlations we had never thought to look for.

Asset ManagerHotel owner, 100+ properties

Case study

Asset Management Intelligence for a hotel owner with 100+ properties.

A large U.S.-listed hotel owner wanted hotel asset management analysis without the manual assembly. SquareShift built the workflow on the client's data and review rules. It runs the five monthly reviews across the portfolio and returns only the exceptions, each with its calculation and source.

  • Five monthly reviews: profit flow-through, cost creep, revenue and share, pace against forecast, and operator follow-up.
  • Built on the client's financials, operator reporting, and approved market data.
  • AI agents apply the client's own review rules to every property in scope.
  • Returns exceptions, not every data point.
  • Runs inside the client's environment.
  • Executives reviewed it live and approved the direction.

Read other client work in our case studies.

Four-week plan

Five monthly reviews on your data and your rules.

Start with one workflow on your data.

We build the automation in your environment. Your team tests it in a live review.

Map your proof of concept

Four-week plan

What you bring

  • One workflow and its owner
  • Current data sources
  • Your review rules
  • Environment access
  • Review team time

What SquareShift delivers

  • Working automation
  • Review rules
  • Findings with source
  • Environment controls
  • Team read-out
Week 1Scope and connect data.
Week 2Build model and rules.
Week 3Run with your team.
Week 4Review and decide next.