AI & Automation

It’s your data, use it.

Plug your portfolio into an AI application, layer in comps and market composites for full context.

Your data, your AI

Connect to any MCP-compatible assistant. No vendor lock-in.

Layered context

Your portfolio + your comps + the full market, in three layers.

Common data model

Every PMS normalized to one schema, so the AI reads it right.

Refreshed daily

Live data underneath every answer.

Full market Your comps Your portfolio You

How it works

Context, in three layers — you control each one.

Context builds outward from you. Step through the layers to see how RevRE turns your raw portfolio into 360° market intelligence.

Full market Your comps Your portfolio You

Step 01 · Your data

Start with your own data.

Connect your property and portfolio data to the MCP client you already work in. (MCP — Model Context Protocol — is the open standard that lets AI assistants pull from live data sources.) Point Claude, or any MCP-compatible assistant, at your portfolio and ask it anything.

Behind the scenes, RevRE normalizes your data from every major property management system into one consistent schema, so the AI reads it correctly — same occupancy formula, same NOI calculation, same expense mapping, refreshed daily.

  • Your data, your AI — no vendor lock-in
  • Every property management system normalized to one schema
  • Ask in plain English, get answers grounded in your real numbers
YouWhat’s the expense ratio across my Austin assets this month?
ClaudeBased on your 7 Austin assets, you’re running an average expense ratio of 41% this month — up 3 points from last month, driven mostly by Riverfront and Domain North.

Step 02 · Your comps

Add the comps you choose.

Your portfolio in isolation only tells half the story. Is 89% occupancy strong or soft? It depends entirely on what you’re up against. So pick the properties and markets you want to measure against, and RevRE feeds that comp set through the same connection.

Now your AI doesn’t just report your numbers. It tells you how you stack up — against the peers you actually care about, not a generic index someone else built.

  • Build a comp set on your terms
  • Context that reflects your strategy, not a one-size-fits-all average
YouHow does Riverfront’s effective rent compare to my comp set?
ClaudeRiverfront’s effective rent is $1,840 — about 4% below the median of your 6-property comp set, and the second-lowest in the group.

Step 03 · The full market

Add market composites for full 360° context.

Layer in market data composites: aggregated, normalized performance across hundreds of thousands of units in 20+ markets. This is the view no single operator can build alone.

Now your AI sees all three rings at once — your portfolio, your chosen comps, and the broader market. Every answer gets measured against what’s actually happening out there, and it stays current because the data refreshes daily.

  • Aggregated market composites across 20+ markets
  • Your portfolio measured against the full market
  • Deep revenue and expense review, not just rents
YouWhich of my Austin properties are below market occupancy, and by how much?
ClaudeThree of your seven Austin assets are below their market occupancy benchmark: Parmer Lane (−2.0%), Domain North (−1.4%), and Riverfront (−0.8%).

That’s 360° context — your data, made smart by everything around it.

What your team can build

Describe it. Let AI build it.

With all three layers connected, you describe what you want and let AI build it — no data engineering team, no months of pipeline work.

Custom portfolio dashboards

Describe your ideal view — NOI by market, occupancy trend by asset class, expense variance vs. peers — and build it on RevRE data as the live source.

Build me a dashboard showing rent-to-market ratio for all Austin assets, updated daily.

Automated investor reports

Set a cadence. Define the format. Let your AI agent pull fresh RevRE data, populate the report, and distribute it — without a manual step from your team.

Generate my Q2 LP report using current portfolio KPIs vs. market benchmarks.

Anomaly detection & alerts

Build agents that watch your portfolio every morning and flag the moment something looks off — expense spikes, occupancy drops, renewal anomalies — before they compound.

Alert me if any property’s expense ratio exceeds market avg by more than 15%.

Underwriting co-pilots

Connect RevRE market data to your underwriting models and stress-test assumptions faster — live market benchmarks, instant comp sets, no manual pull.

What’s the average effective rent for Class B properties in the Domain market?

Natural language data queries

Ask your portfolio questions in plain English and get answers grounded in real, current operational data. No SQL, no exports, no waiting.

Which of my properties are below market occupancy and by how much?

AI data pipelines

Use RevRE as the structured data layer underneath your own AI products. Feed clean, continuously refreshed property data to your models — no pipeline team required.

Fetch all Phoenix market data for my rent prediction model training set.

Who it’s for

Built for the people putting AI to work.

Operators automating with AI

You’re curious about AI but your data is a mess, so the tools give you nothing useful. RevRE cleans the foundation — so when you point Claude at your portfolio, you get real answers.

  • Ask about your portfolio in plain English — get real answers
  • Automate reporting workflows without a data engineering team
  • Build custom dashboards backed by live data

Analysts building AI-powered models

You want to build predictive models — rent forecasting, occupancy projection, expense anomaly detection — but you spend most of your time cleaning data instead of modeling.

  • Analysis-ready data via API — feed models without pre-processing
  • Live market benchmarks to validate and calibrate outputs
  • Daily refresh — your models always train on current data

PropTech companies shipping AI products

You’re building AI-powered products for multifamily — pricing engines, underwriting tools, portfolio intelligence. You need a structured, continuously refreshed data layer underneath. That’s what RevRE is.

  • API and MCP Server — integrate RevRE data into your stack
  • Continuously refreshed — no stale data in your AI outputs
  • Layer in market composites
Get started with AI & Automation

Stop guessing. Start with context.

Your data, the comps you choose, and the full market — connected to the AI you already use.

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