REITs and property owners

Protect profits. Catch cost creep. Spot the revenue leaks.

SquareShift helps REITs and property owners use their own data to improve operations, profit, and returns. We build working AI systems for asset management, market review, forecasting, contracts, and investment decisions.

Map a proof of concept

Invitation only · Phoenix 2026

An exclusive CXO briefing and roundtable at The Lodging Conference.

One hour, a closed table, and a small group of owner-side leaders. Bring the portfolio question you cannot answer fast enough today — we will show how the same question gets answered on a client's own data, and you will leave with a first read on what a proof of concept would take.

  • For asset management, investment, revenue, legal, and technology leaders at REITs and property owners.
  • Working software on screen, not a product demo.
  • Seats are limited and confirmed by invitation.
Request an invitation

The problem

REIT owners and operators have valuable data, but it is hard to use.

The data is spread out. People spend too much time pulling it together. Senior people spend time on analysis prep instead of decisions.

Six problems we hear from owner-side teams

  1. 01

    Data is fragmented.

    Property financials, lease records, operator reports, market data, contracts, forecasts, research, and notes sit in different places.

  2. 02

    Manual work is still too high.

    Even when the data exists, teams spend too much time joining it, checking it, and turning it into something useful.

  3. 03

    Important people lose time.

    Asset managers, investment leaders, legal teams, and operators should spend more time on action and less time building the same review pack again.

  4. 04

    Good partners are hard to find.

    REITs and owners need teams that understand real estate, data, AI, delivery, and long-term support.

  5. 05

    Useful data stays unused.

    There is data that can improve operations, profit, and return on investment. It often stays out of reach.

  6. 06

    Owners need control.

    The system has to work inside the client environment, use the client data, follow the client rules, and keep improving after launch.

The answer

We help your team get faster answers from the data it already uses.

Start with one decision that matters. Connect the data needed for that decision. Build the first working version on your data. Improve it with your team until it works in the real review cycle.

Problem

Data is fragmented.

Records, reports, and documents sit in different places.

Connect your data without a costly integration.

Linked where it already sits. No warehouse rebuild first.

Problem

Manual work slows the team.

Analysts rebuild review packs and senior people wait.

Build AI workflows for repeatable analysis.

The work runs as software. Your team keeps the judgment.

Problem

AI projects stall.

The demo works, but the outcome does not arrive.

Understand the business, then deploy AI end to end.

One defined problem, carried from data to decision owner.

Problem

Useful data stays unused.

Data that could improve profit and returns sits idle.

Get real value out of the data you already pay to keep.

It becomes a working review your team runs every cycle.

Problem

Owners need control.

The data and the process must stay under your rules.

Partner, build, operate, transfer.

We build with your people, run it, then hand it over.

Four entry points

Four solutions that turn real estate data into better owner decisions.

  1. Solution 01 Asset Management Intelligence Run monthly reviews across every property and bring back only what needs attention. See the workflow →
  2. Solution 02 Market Intelligence Know which markets changed, which assets are exposed, and which assumptions need review. See the workflow →
  3. Solution 03 Forecasting Intelligence Compare the outlook, the downside case, and the investment thesis before the next review. See the workflow →
  4. Solution 04 Contract Intelligence Turn agreements, amendments, exhibits, and side letters into clear answers. See the workflow →

Solution 01 · Asset Management Intelligence

Run the monthly asset management review across every property.

Asset managers need to know which assets need attention after the latest close. The workflow reviews profit flow-through, cost creep, revenue and market share, pace against forecast, and operator follow-through.

  • Read the data

    Financials, operator commentary, and market data your team already uses.

  • Run the reviews

    The five monthly reviews, every property, on your review rules.

  • Return exceptions

    Only what needs a decision, with the calculation and where the number came from.

  • Act

    The asset to look at next, and the operator conversation to have.

Asset management review
Hotel porte-cochere and forecourt at golden hour
Built for a large U.S.-listed lodging REIT · 100+ properties in scope

Solution 02 · Market Intelligence

Market review
Resort property and grounds at sunset
Markets, comp sets, and holdings ranked by what changed

Know which markets changed and which holdings are exposed.

Market Intelligence watches market signals and brings back the markets, assets, comp sets, supply changes, demand patterns, and assumptions that changed enough to review.

  • Collect signals

    Performance, demand, supply, local indicators, and internal material your team accepts.

  • Rank changes

    Markets, assets, and segments ordered by what moved and why it matters.

  • Review exposure

    Which holdings are affected and which growth, rate, share, or hold-sell assumption to revisit.

  • Decide

    Only material changes go into the executive review, with what supports the read and what challenges it.

Solution 03 · Forecasting Intelligence

Compare the revenue outlook, downside exposure, and investment thesis.

Forecasts lose value when inputs, assumptions, and market comparisons move faster than the review cycle. This workflow keeps the forecast current, comparable, and tied to the data behind it.

  • Connect signals

    History, licensed benchmarks, external signals, and portfolio assumptions.

  • Run models

    Base, upside, and downside cases against matched horizons.

  • Compare

    Budget, underwriting, and hold-sell thesis, with validation against the current approach.

  • Rank attention

    Markets and assets ordered by forecast movement and thesis exposure.

Forecast review
Mountain resort property at sunrise
RevPAR is the lodging example of this workflow

Solution 04 · Contract Intelligence

Contract questions
Managed lodging property exterior at dusk
Contract question answering and review routing, not legal advice

Turn contract documents into clear answers and gap reports.

Contract risk builds when agreements, amendments, exhibits, notices, and side letters sit in fragments. Contract Intelligence answers questions from the documents your team accepts, and shows what is missing before anyone relies on the answer.

  • Register

    Property, entity, agreement family, document status, reviewer, and access.

  • Ask

    One question with the right scope, against only the documents your team allows.

  • Answer

    An answer, a portfolio comparison, a clear no-answer, a gap report, or a legal review route.

  • Keep the record

    The question, search path, answer, and review history stay available to check later.

Case study

Asset Management Intelligence for an owner operator with 100+ properties.

A large lodging REIT wanted asset managers to get their analysis without assembling it by hand. SquareShift built the workflow on the client's data and review rules.

The workflow runs the five monthly reviews across the portfolio and returns the exceptions worth the team's time. Each finding shows the calculation and where the number came from.

How we start

Start with one workflow, one owner question, and your data.

The first step is not a platform rebuild. It is a focused proof of concept around one workflow where the manual review is slow, expensive, or incomplete.

01

Pick the question

One decision owner and one question worth improving. Narrow beats broad.

Week one →
02

Connect the data

Only the data needed to answer that question, with your access rules in place.

Your environment →
03

Build the workflow

Review rules, assumptions, gaps, and output format, built as working software on your data.

Working software →
04

Expand to new workflows

Once the first workflow earns it, the same pattern moves to the next question, the next property set, and the next team.

Then grow it →

Bring one owner-side workflow. We will map the proof of concept.

Map a proof of concept

Why SquareShift

We build the workflow, not only the slide.

SquareShift builds data and AI systems for enterprises. For REITs and property owners, we apply that work to cost reviews, comp-set reads, market screens, hold-sell questions, contract questions, and forecast reviews.

Google Cloud Premier Partner

Real delivery experience

Built AI analysis for a large U.S.-listed lodging REIT, on the client data and the client review rules.

Data and AI build team

Experience across structured data, unstructured documents, and systems that keep running after launch.

Google Cloud partner

Work across enterprise data and AI programs, built inside the client cloud environment.

Next step

Bring us one owner-side real estate workflow that still takes too long by hand.

In twenty minutes, we can map the data, rules, review owner, output, and proof-of-concept path.

Map a proof of concept Request a TLC invitation

Good first workflows

  1. 01

    Monthly asset management review

    Which assets need attention after the close.

  2. 02

    Market movement review

    Which markets moved and which holdings are exposed.

  3. 03

    Forecast downside case

    What the outlook looks like if the market turns.

  4. 04

    Contract question answering

    One agreement family, answered with the gaps named.

  5. 05

    Investment committee prep

    The pack assembled before the meeting, not during it.