Crexi, a leading commercial real estate data platform and marketplace, has integrated Dwellsy IQ’s unit-level rental data into Crexi Intelligence—further strengthening its multifamily analysis capabilities, as announced in the latest release.
Through this strategic partnership, Dwellsy IQ’s source-verified rental intelligence is now embedded directly within Crexi’s Comps & Records experience. As a result, multifamily professionals can analyze rental comps, sales comps, and ownership data in one unified platform—within the workflow they already rely on daily.
For underwriting, pricing, and valuation, context is essential. This partnership now delivers that context more completely than ever.
Why Multifamily Underwriting Needs Better Rental Comps
Historically, multifamily underwriting has relied on fragmented rental intelligence. Analysts frequently move between platforms to gather rental comps, validate pro forma assumptions, review ownership history, and benchmark market trends. Consequently, this fragmentation slows decision-making and increases the risk of incomplete or inconsistent assumptions.
By embedding Dwellsy IQ rental data directly into Crexi’s Comps & Records experience, multifamily professionals can now evaluate rental and sales data side by side. The workflow becomes unified, not stitched together.
What Makes Dwellsy IQ Multifamily Rental Data Different
Unlike aggregated or scraped datasets, Dwellsy IQ is built on first-party rental data collected directly from property management systems. Therefore, rent information originates from the operational layer where pricing is created and updated—not from delayed estimates.
Currently, the dataset includes more than 17 million units listed nationwide, over 25,000 property managers, and 30+ PMS integrations. As a result, users gain granular, unit-level visibility into rent amounts, bed/bath mix, square footage, deposits, and amenities—inputs that directly influence underwriting accuracy.
How Crexi Is Structuring Multifamily Analysis Differently
Crexi integrates rental, sales, and ownership data within a single platform interface. With the addition of Dwellsy IQ’s unit-level rental dataset, multifamily professionals can evaluate rental comps alongside transaction history and property records without exporting data across systems.
Unlike workflows that require assembling rental data separately, Crexi structures rental intelligence inside the same Comps & Records environment used for sales analysis. Rental comps can be filtered by unit type, size, and rent range while reviewing comparable transactions. Property-level rental data is embedded directly within asset records.
Mapping tools and submarket filters allow users to benchmark rents geographically within the same analytical view.
By structuring rental validation within the transaction analysis workflow, Crexi reduces the separation between rent assumptions and sales comparables during multifamily underwriting.
How This Impacts Multifamily BOVs, Appraisals, and Lending
For brokers preparing Broker’s Opinions of Value (BOVs), integrated rental intelligence strengthens pricing narratives and improves defensibility. Similarly, appraisers gain clearer rent benchmarking at the unit level, while lenders can stress-test underwriting assumptions using more granular data.
Meanwhile, developers modeling lease-up scenarios benefit from competitive positioning insights at the bedroom-count level. Across the deal lifecycle, stronger rental inputs ultimately produce more defensible multifamily underwriting outputs.
What This Means for the Future of Multifamily Market Analysis
Multifamily professionals are increasingly asking, “Where can I find accurate multifamily rental comps?”, “How do I validate rent assumptions in underwriting?”, and “What data source provides unit-level multifamily rent trends?”
This partnership addresses those questions directly by embedding verified rental intelligence inside the same platform used for sales and ownership analysis.
Ultimately, the shift is toward integrated multifamily intelligence—where rental data supports pricing and underwriting decisions in real time.
Frequently Asked Questions (FAQ)
What is Dwellsy IQ?
Dwellsy IQ is an enterprise-grade residential rental data platform built on first-party rental listings collected directly from property management systems. It provides unit-level rental visibility across U.S. multifamily and single-family rental properties.
What is Crexi?
Crexi is an AI-powered commercial real estate platform built to support every stage of the deal lifecycle — from real-time market data and intelligence with Crexi Intelligence, to property marketing with Crexi PRO, to transparent bidding with Crexi Auction. To date, Crexi has subsidized over $2.74 trillion in property value, 26 billion square feet listed, and supports a growing community of more than 23 million yearly users.
What is the Crexi and Dwellsy IQ partnership?
The Crexi and Dwellsy IQ partnership integrates Dwellsy IQ’s unit-level rental data directly into Crexi Intelligence. This allows multifamily professionals to analyze rental comps, sales comps, and ownership records within a single Comps & Records workflow, reducing fragmentation during underwriting.
How does Dwellsy IQ and Crexi partnership improve multifamily underwriting?
By placing rental comps and transaction data inside the same workflow, analysts can validate rent assumptions more efficiently, reduce fragmentation, and improve the defensibility of underwriting decisions.
What rental data does the Crexi and Dwellsy IQ partnership include?
The integration includes detailed unit-level rental data for over 620,000 properties. Users can access rent amounts, bedroom and bathroom counts, square footage, deposits, and amenities. Rental comps can be filtered by unit type, size, and rent range, with geographic benchmarking through maps, submarkets, and ZIP-level views.
Who benefits most from the Dwellsy IQ and Crexi partnership?
Brokers preparing BOVs, lenders stress-testing assumptions, appraisers validating rent benchmarks, and developers modeling lease-ups all benefit from more granular rental intelligence within their underwriting workflow.
