Figure S-1 Breakdown — The HELOC Machine on Crypto Rails

Aug 27, 2025

This is a special edition of the newsletter — we’re breaking down Figure’s S-1. It showcases a tech-enabled real-estate lender at real scale and profitability—with a clear, practical crypto layer. Let’s dig in!

Figure filed its S-1 last week. Figure is a blockchain-powered capital marketplace that connects origination, funding, and secondary market activity. This was one of the first investments I worked on at Thomvest way back in 2018. Our first meeting with co-founders Mike Cagney and June Ou took place in their living room, which doubled as Figure’s HQ in the early days. The company has come a long way since then, but it’s remarkable how much of Mike and June’s original vision remains intact 7+ years later.

Figure’s core business today centers around its mortgage technology efforts: the company originates and sells standardized HELOCs (home equity line of credit), increasingly for third-party brands, then take fees across origination, sale, and servicing. Crypto appears in its plumbing (blockchain records, lien/eNote registry) and in its longer-term vision (a digital asset exchange and a tokenized stablecoin/security), but near-term economics are tied to housing credit, not tokens. For public investors, that makes the model more legible—and testable—as a tech-enabled originator, with added upside from its blockchain platform.

The company has reached impressive scale — over the last year, Figure has facilitated more than $6 billion of home equity lending. From the start, Mike and June built the business around two key tailwinds:

There is massive, largely untapped demand for HELOCs — U.S. homeowners sit on roughly $11T of “tappable” equity (about $203k per borrower) yet more than half of mortgages carry rates at 4% or lower, making cash-out refinancing unattractive. A second-lien HELOC unlocks cash without disturbing the cheap first lien. HELOCs fund two important use cases—debt consolidation (there is more than $5T in outstanding consumer debt) and home improvement (the average home is more than 41 years old)—at lower cost than unsecured personal loans and credit cards.
The $3T global securitization industry is full of high-rent third parties, which extract 75–100 bps of fees in a typical securitization ($30B+ in total fees annual). Blockchains have emerged as a viable way to transform the loan lifecycle into a shared, low-cost system of record that cuts friction and errors—while promising tighter spreads and better secondary liquidity. The result is not “crypto for crypto’s sake,” but a fee-compression and liquidity story that aligns with how capital markets actually clear.

But why build both under one roof? The combination of the two businesses is powerful — Figure’s lending business acts as a powerful first customer and proof-of-concept for the blockchain-based securitization platform. It’s meaningful in banking, where regulation and general risk-aversion makes “first-mover” behavior uncommon. From the S-1:

“We made this pitch to the banks, and they universally said, “This is great! We love it! We’d like to be the 10th bank to do this…” It was clear this wasn’t an ‘if you build it, they will come’ situation – if we just built it, no one was going to show up.”

I’d also argue that the combination of origination and capital markets automation is key to actually delivering on speed and cost improvements in the mortgage value chain. The Figure team recently published a good piece on the topic, underscoring the cost savings enabled by their approach:

“Recording loan attributes immutably at origination reduces audit costs by 80% compared to legacy systems that require a full asset review with every ownership transfer.”

Let’s dig into these two segments, how they are connected, and what the the company is building to expand its product portfolio.

Figure’s Origination Business

Figure has built a modern HELOC stack, including proprietary loan origination system (LOS), automated verification of income and title, and efficient secondary market execution (more on that in the next section). The operating payoff shows up in two places that matter: speed and cost. Median time from application to funding is 10 days versus a 42-day industry median, and average production cost per loan is ~$730 versus an MBA-reported mortgage average of ~$11,230 in Q4 2024 (note that this is for all loan types, not solely HELOC).

In 2024, total net revenue rose 62.7% to $340.9M, and the company swung to $17.2M of net income from a $47.9M loss in 2023—driven by higher gain-on-sale, origination, and servicing economics. Momentum has carried into 1H25: net revenue reached $190.6M, up ~22% year-over-year, with net income of $29.1M and adjusted EBITDA of $47.9M.

Scale increasingly comes via partners: 168 as of June 2025; the top 10 partners drove 57% of origination volume in 1H25. Partner-branded originations grew from $149M (June 2022) to ~$4.3B over the last twelve months (as of June 2025), and were 77% of total originations in 1H25. Figure-branded volume (originated via DTC channels) reached ~$2.0B LTM (as of June).

A typical Figure HELOC partner is a medium-to-large U.S. non-bank mortgage finance company (though banks, credit unions, servicers, and wholesale brokers also participate) that wants a turnkey HELOC without building the stack. They run a white-labeled, partner-branded portal on Figure’s LOS—automated underwriting, decisioning, and closing under the partner’s name. Partners contract on a non-exclusive, auto-renewing basis to use the LOS and the Figure Connect marketplace, which is monetized via percentage and volume-based tech and execution fees.

Figure’s top line comes from (i) ecosystem & technology fees (LOS and Connect; plus program fees for securitizations), (ii) origination fees, (iii) gain on sale, (iv) servicing fees, (v) interest income, and (vi) changes in servicing asset fair value. Partner contracts pay volume-based technology/processing fees tied to principal balances, while program fees are earned on securitization close. In practice, this means the platform monetizes both the creation of loans and the liquidity events that follow.

In 2024, gain-on-sale rose 179% to $140.4M as pricing improved ~110 bps and unpaid principal sold increased from $3.3B to $4.8B; retained servicing asset gains also expanded with larger sale volume and slower prepay assumptions. Servicing fees climbed with the servicing book (UPB $8.1B vs. $5.2B). Technology offering fees scaled as partners used the LOS (weighted-average ~0.8% of principal in 2024). Nearly all originations are HELOCs (99% in 1H25), so category growth maps to that product’s throughput.

Figure’s revenue mix is moving toward platform fees. Ecosystem & technology fees were $28.3M in 2024 (~8% of net revenue), then $43.8M in 1H25 (~23% of net revenue). That’s a meaningful step-up in recurring, non-spread income while core credit throughput stays high.

Figure’s Blockchain Platform

While the near-term revenue engine is HELOC origination and sale, Figure’s blockchain efforts are an important efficiency driver for the business. When combined, they allow Figure (and its originator partners) to prove ownership and servicing rights on-chain, match loans to buyers, and eventually finance and trade them against a native, interest-bearing stablecoin. From the S-1:

“Financial services historically have been and still are trust-based markets. Trust-based markets require significant intermediation. Up to seven parties sit in between a buyer and seller of public equity. Five parties intermediate a debit card transaction. Massive companies with enormous market capitalizations have been built around this rent-seeking. Blockchain has the power to distill these multi-party marketplaces down to just two: buyer and seller. All the rent-seeking goes away.”

The S-1 shows early adoption where it matters (registries and loan distribution), modest traction in trading, and seed-stage scale in yield products. Let’s walk through their product portfolio:

Provenance (public blockchain). Provenance is a public, proof of stake decentralized blockchain (Figure owns 20% of the network’s utility token, $HASH). Provenance is the “system of record” for assets on the Figure platform, i.e. a public Layer-1 used to hash each origination and update ownership as loans trade. Figure pays gas fees in HASH and currently subsidizes participant fees; average gas consumption is <1 HASH per transaction (~$0.026). The chain’s performance (≈4.4s blocks) and low fees make it viable for back-office scale. Figure cites >$50B in cumulative on-chain transaction records (as of June 2025), ~$10B of “real world assets” (RWA) value on-chain (TVL), and ~75% share of tokenized private credit by outstanding loans (RWA.xyz).

Provenance launched in 2018 as Figure’s big move into the blockchain ecosystem. Today, every asset passing through Figure’s origination system is recorded on Provenance, and many other buyers / seller pairs utilize the blockchain’s smart contract framework (here is a good case study on how JP Morgan utilizes Provenance).

DART (on-chain lien & eNote registry). Digital Asset Registry Technologies (DART) is an electronic registry that records lien/eNote control and updates ownership automatically as loans are pledged or sold. It runs on Provenance and sits alongside county records. Adoption moved fast—about 80% of loans originated on Figure’s LOS were boarded to DART in 1H25 (up from ~2% in FY24), with ~30k loans relying on DART and ~75 entities signed to participation agreements by June 30, 2025. The pay-off is fewer manual assignments, cleaner pledging/sale, and lower post-closing friction.

Figure positions DART as a real-time, programmable successor to MERS, which is the primary recording system for tracking mortgage ownership and servicing rights in the U.S. Instead of updating ownership/control through manual assignments and disparate systems (as is the state of the art for MERS), DART “listens” to on-chain events and synchronizes control automatically, while preserving county recording and traditional documentation.

Figure Connect (loan marketplace). A standardized, electronic market for HELOCs where assets originated on the LOS can be sold to whole-loan buyers or prepped for securitization; Provenance is the system of record for asset transfers. In its first 12 months (to June 2025), Connect handled ~$1.3B of HELOC flow with ~27 participants and generated ~$45M of net revenue in 1H25 (from de minimis in 2024). The model is volume-based tech/execution fees; disclosures indicate originators have historically netted >1% more UPB by selling on Connect than via Figure as an intermediary. A Sixth Street–backed guarantor vehicle exists to deepen the bid, though as of June 2025 its purchases via Connect had not yet begun—another execution milestone to watch.

Figure Exchange + ATS (tokenized RWA trading). A regulated exchange stack (broker-dealer/ATS + money transmitter/VASP registrations) for digitally native securities and tokenized real-world assets. Activity has crossed $1B cumulatively since launch, but 1H25 revenue was effectively $0—useful plumbing, not yet a P&L driver.

YLDS (yielding stablecoin). YLDS is an SEC-registered, interest-bearing stablecoin backed by cash and cash equivalents, paying a constant rate of SOFR minus 50 bps. It launched in Feb-25 and stood at ~$4M outstanding by Jun-30, 2025, contributing <$1k of revenue in 1H25. The S-1 positions YLDS as settlement collateral for Exchange and as a funding rail for Connect. The aim is to migrate more marketplace settlement into YLDS over time.

Democratized Prime (on-chain funding market). This is a Dutch-auction lending market where institutions and retail provide cash to specific collateral pools (e.g., tokenized HELOCs, margin funding). Auctions reset hourly; Q2-25 clearing rates ranged from 1% to 30% (weighted avg. ~10%). As of Jun-30, 2025, assets on the platform were ~$1.5M and fee economics are 50 bps (borrower-paid), with revenue to be recognized under ecosystem/tech fees once third-party funding scales. A planned cross-collateralization feature is slated for late-2025.

Closing Thoughts

The near-term economic engine is HELOC origination and sale, Figure’s crypto products act as core infrastructure. This underscores the strategy: build durable, fee-generating infrastructure around HELOC flow first; let adjacent blockchain products add optionality without driving the P&L near term (perhaps Amazon’s strategy building and ultimately monetizing AWS is an appropriate analogy). The timing is good given regulatory tailwinds around crypto and token securitization.

The company is already expanding its securitization efforts beyond HELOC. Figure CEO Michael Tannenbaum recently shared that the company had completed a securitization comprising of all first-lien mortgages:

“What made this securitization even more notable was that these loans could have gone to Fannie Mae or Freddie Mac, but instead went to Figure's marketplace. Our partners either explicitly (as is the case with most financial institution partners) or implicitly (because our marketplace was the best for pricing and liquidity) chose our market.”
Our use of blockchain and the related liquidity and transactional benefits we have brought to our marketplace has enabled us to catch up and beat what has been well known to be the most liquid and robust debt market.

Blockchain matters where it reduces funding frictions: (1) DART de-risks collateral and simplifies due diligence; (2) Connect increases take-out velocity and price transparency; (3) Exchange/ATS and YLDS create always-on settlement and, over time, balance-sheet-light financing; and (4) Democratized Prime adds market-clearing funding that can compress spreads. That stack is already showing up in mix: in 1H25, 22% of revenue came from transactions via Figure Connect, with the remainder split across origination, servicing, and interest income.

Congratulations to the Figure team! As always, please feel free to share feedback or thoughts on this newsletter — you can find me on LinkedIn and Substack.

Note: Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others.

The Appraisal, August 2025 — Opendoor's Open Questions

Nima Wedlake

Aug 12, 2025

Welcome to the August edition of The Appraisal, a newsletter on real estate tech. My writing focuses on the 30+ public companies operating at the intersection of real estate and technology. In this issue, we review Opendoor’s journey as a public company amid its recent share price run-up and strategic changes to its core iBuying model.

Opendoor has been the subject of intense social media discussion over the last quarter, including a popular post on the r/WallStreetBets subreddit, and viral tweets from hedge fund manger Eric Jackson (who correctly called Carvana’s big rally, suggesting that Opendoor had similar 100x potential). This led to a flurry of trading activity that drove the company’s share price up 5x in a matter of days (from $0.51 to as high as $4.97). Shares have since settled back to the $2 range.

I last wrote about Opendoor in October 2020, ahead of its SPAC led by investor Chamath Palihapitiya. The recent run-up, along with last week’s Q2 earnings announcement, inspired me to revisit that post and update the bull and bear cases for Opendoor. Let’s dig in.

Opendoor announced its SPAC during a period of intense investor demand for technology IPOs, particularly those within the real estate segment that were benefiting from fiscal stimulus and low interest rates. The transaction valued Opendoor at an enterprise value of $4.8 billion, representing a nearly 18x EV-to-Forward Adjusted Gross Profit multiple (adjusted gross profit strips out inventory valuation adjustments from GAAP GP).

Since then, the company and it’s stock have been on a rollercoaster. Opendoor grew aggressively in 2021 during a period of record-high home price appreciation. The company went on a home buying spree that year, purchasing more than 37,000 homes across 30+ markets. And rising home prices meant profitable home sales for the company — Opendoor generated more than $500 million in contribution profit in 2021 (profit on homes sold net of direct selling costs). Opendoor’s share price peaked at $35.88 in February 2021, representing a market cap of more than $16 billion.

Unfortunately, the good times were short-lived: beginning in early 2022, the Federal Reserve initiated aggressive rate hikes to combat rising inflation (ending the year at a Fed funds rate of 4.50%). In response to the rate hikes, Opendoor meaningfully slowed down its pace of home buying (from 14k in Q2 ‘22 to less than 4k in Q4 ‘22).

Rising rates also cooled buyer demand for homes, which impacted the company’s ability to sell its inventory of homes at a profit. Contribution margin went negative in Q3 ‘22, and by Q1 ‘23, the company lost nearly $30k per home sold (selling homes for on average 7.7% less than what they purchased them for, net of selling and holding costs). Opendoor’s share price fell below its SPAC price of $10 per share, and has not recovered since.

The Wheeler Era

By Q4 ‘22, Opendoor’s price per share fell below $2. And by December, the company’s founder and CEO Eric Wu announced he was stepping down. CFO Carrie Wheeler moved into the CEO role with a mandate to cut costs while navigating a challenging housing market.

Wheeler has led a period of aggressive cost-cutting. The company laid off more than 500 employees in 2023. Last year, Opendoor announced another workforce reduction of 300 employees (17% of its workforce). The company also spun off its transaction platform for institutional investors, Mainstay, in order to further reduce operating expenses (the company reported $35 million in annual savings resulting from the divestiture).

Adjusted operating expenses (which strip out stock-based compensation and variable costs related to selling properties) were $46 million in Q2 ‘25, down by over 50% from the same quarter last year.

Opendoor has also improved the gross margins generated from its home buying efforts in recent quarters. The team at SFR Analytics put together a great chart in their recent piece on Opendoor, highlighting per-home gross margins generated by cohort. Recent cohorts are producing strong average gross profits. From their post:

Opendoor isn’t nearly as bad at acquiring properties as some people make the company out to be. In 2022, Opendoor was — but since then the company has been consistently gross margin profitable. In Phoenix, which accounted for >50% of total losses in 2022, the last 12 months have routinely been between $20k-$30k gross margin profitable. As the company has laid off the risk in 2025 acquisitions, margins have also gotten stronger.

However, those efforts have yet to generate durable earnings results, nor appease public market investors. The stock has consistently traded below its SPAC price for the last thee years. Just two months ago, Opendoor received a warning from Nasdaq that it could be delisted after the stock price failed to break above $1 for 30 consecutive days. In June, the company announced a special meeting to discuss a reverse stock split “ranging from any whole number between 1‑for‑10 and 1‑for‑50.”

While the recent retail frenzy over the stock served as a lifeboat for the company, that ship may now be sailing away. The company’s stock price slipped below $2 again following last week’s earnings announcement, in which management guided to weak Q3 earnings (only 1,200 homes acquired, projected revenue down 44% quarter-over-quarter to $875 million). Prominent investors have lobbied for broad leadership changes at the company.

Looking Forward

The iBuying model has several structural challenges — forcing operators to constantly tradeoff growth for margin. Macroeconomic volatility makes the job even harder. For example:

Opendoor must buy homes at a meaningful discount to cover marketing, holding, selling, renovation, and overhead costs. As discounts deepen, seller conversion rates fall, pushing CAC higher and reducing purchase volume. According to a recent Opendoor investor presentation, “sellers are about twice as likely to sell their home at a 6% fee vs. a 12% fee.”
Opendoor must turn inventory quickly to recycle capital and keep carrying costs low—especially in a flat or declining market—but that speed often means accepting lower gross margins. This may prove challenging in today’s market — home prices in cities like Dallas and Phoenix are down slightly year-over-year, while total inventory of homes for sale is up more than 15% (indicating a buyer’s market).
Opendoor must be very responsive to changing market conditions that can impact buyer demand. But when it scales back home buying its fixed costs are spread over fewer homes, impacting the company’s ability to reach EBITDA profitability. This is playing out now — Opendoor is guiding to just 1,200 purchases for Q3 ’25 (versus 3,504 a year earlier) in response to headwinds in the housing market.

Let’s use some simple math to better illustrate the hurdle the Opendoor team must overcome in order to profitably manage this business:

The company has averaged about $16.5k of contribution profit per home sold over the last 8 quarters
Advertising costs per home sold average about $5.5k over the last 8 quarters (based estimates from UBS)
So net contribution profit (stripping out advertising expense) is about $11k.
Adjusted R&D and G&A expense in Q2 ‘25 was $38 million according to UBS (this is down by over half from 2 years ago) and is expected to stay within this range through 2026.
In order to “pay for” these fixed operating costs, Opendoor must sell about 3,500 homes per quarter. Anything less implies that the company won’t produce contribution profits in excess of its costs. The company acquired only 1,757 homes in Q2, suggesting a reversion to negative EBTIDA margins in future quarters.

So what should Opendoor’s leadership do? Wheeler has described the company as a “leaner, more efficient operation” in 2025. I already highlighted the actions the company has undertaken to drive down operating costs. Now let’s discuss the company’s efficiency initiatives, namely Cash Plus and Key Agent.

Cash Plus provides sellers with upfront cash for their home, then professionally renovates and resells it on MLS. If the renovated home sells for more than Opendoor’s costs, the owner receives the additional proceeds (net of all fees and expenses incurred). This model combines the speed and certainty of an instant offer with the price-maximization potential of a traditional listing. Cash Plus is live in Dallas, Nashville and Raleigh and slated for wider rollout this year.

Key Agent flips Opendoor’s old direct-to-consumer model: the company now funnels high-intent seller leads and instant-offer tools to a hand-picked network of top agents, who present every option (cash offer, Cash Plus, or a standard listing) and earn a referral fee no matter which path the client chooses.

Both programs chip away at the two structural weaknesses that have plagued the iBuyer model — balance-sheet exposure and high customer acquisition costs. They achieve this by partnering with agents, as described by Wheeler in the company’s most recent shareholder letter:

“We believe a great agent can be an invaluable guide through one of life’s biggest decisions, and our path forward lies in deepening these partnerships.”

This is an important shift from prior messaging that tended to eschew the agent’s role in a real estate transaction. Opendoor is no longer trying to replace real-estate agents with its own end-to-end service; instead, it’s providing agents with ready-made tools— cash offers, renovation teams, pricing and market data—that they can plug into their own listing workflow.

Together, these initiatives reposition Opendoor as a capital-light marketplace that (hopefully) improve unit economics. Wheeler hinted at this in the shareholder letter, sharing some early data on seller conversion rates when agents are leading the conversation:

We began piloting this new approach in select markets in the second quarter, and the early signals have been encouraging:
Twice as many customers are reaching a final underwritten cash offer as compared to our traditional direct-to-consumer flow.
Listing agreement conversion rates (i.e., consumers who end up listing with a partner agent) are 5x greater than what we have realized in our direct-to-consumer flow.

These are good (early) signs of more sustainable unit economics. We’ll certainly learn more over future quarters.

Closing Thoughts

As I highlighted above, the central questions for Opendoor’s core iBuying business are two-fold: first, what is the contribution margin-optimal volume of home purchases per quarter (i.e. factoring the relationship between marketing spend and discount rate on homes purchased)? And second, can management drive down operating expenses to a level such that the company can comfortably generate contribution profits in excess of those expenses? This is a challenging task, as I highlighted in my original post:

While the core vision of the company is quite elegant (“building the digital one-stop shop to move” according to Opendoor founder Eric Wu), the path to realizing that vision is incredibly complex. It requires thousands of employees across dozens of markets, holding billions in home value at any given time.

That’s why the company’s efforts around Cash Plus and Key Connections are so critical — they offer the promise of a more sustainable business that can better navigate changing housing market conditions.

If you have any colleagues that may find The Appraisal valuable, please share this newsletter. Thank you!

Five Trending Topics

The Housing Market Is Frozen. Zillow’s C.E.O. Knows You’re Still Scrolling [New York Times] Zillow is growing even as the housing market stays frozen—prices remain high, many owners are rate-locked, and home sales have hovered near 30-year lows. The piece attributes Zillow’s resilience to its platform scale and expansion into rentals, mortgage, and services.
Monopoly Round-Up: The $100 Billion Race to Become the Home Buying Super App [BIG Newsletter] Matt Stoller argues Rocket, Zillow, and Compass are racing to build a “home-buying super app” to capture the ~$100B in commissions now paid to agents, setting up a fight for market power in residential real estate. He outlines how private lawsuits and a pullback in federal antitrust enforcement could dismantle the old agent-centric model—or just swap it for new platform monopolies.
How Many Jobs Do Robots Really Replace? [MIT News] From 1990–2007, adding one robot per 1,000 workers cut the U.S. employment-to-population ratio by ~0.2 points—about 3.3 jobs per robot—and reduced wages ~0.4%. The effects are concentrated in robot-heavy regions and industries (e.g., autos) but create interesting questions as robots gain more widespread adoption, including across real estate and construction.
Measuring AI Ability to Complete Long Tasks [METR] METR proposes a simple metric—how long a task (in human-hours) an AI can complete—and finds this “time-horizon” has doubled roughly every seven months over the past six years. Today’s best models reliably handle tasks lasting minutes and falter on multi-hour work; if the trend holds, week- to month-long autonomous projects could arrive within a few years.
1,000 Homes of Power in a Filing Cabinet — Rising Power Density Disrupts AI Infrastructure [Goldman Sachs] Goldman argues AI’s performance gains from tightly clustered GPUs are driving rack power from ~20–40 kW to ~600 kW by 2027 (with 1 MW on the roadmap), forcing a shift to liquid-cooled, industrial-grade data centers. It frames 2025 as a decisive buildout moment where obsolescence risk and export-control limits on interconnects will shape winners in the AI infrastructure race.

The Appraisal, June 2025 — Index Performance Updates & Ten Trending Topics

Nima Wedlake

Jun 17, 2025

Welcome to the June edition of The Appraisal, a newsletter on real estate tech. My writing focuses on the 30+ public companies operating at the intersection of real estate and technology. In this edition, we’ll review the Real Estate Tech Index’s recent performance and highlight several recent stories across the real estate ecosystem.

The Real Estate Tech Index has been quite volatile through the first half of the year — up nearly 15% in February, followed by a sharp pullback in April, and a recovery in May and June (now down 2% year-to-date). The Trump administration’s tariff actions drove much of the April sell-off, which spiked 10-year treasury yields (currently at 4.4%) and threatened to further increase construction material costs (which are now 40% higher compared to February 2020).

Of course, the Index represents aggregate returns, and we’ve seen a wide dispersion of outcomes at the individual company level. Some have remained resilient within a tough macro (Compass and Lemonade are up 75% and 149%, respectively, over the last year), while others have struggled to sustain durable growth and profitability (Opendoor is down 68% over the last year and is planning a reverse stock split to avoid a Nasdaq delisting).

In my inaugural newsletter, I highlighted three primary headwinds facing companies in the Index: a challenging macro environment, a SPAC wave that brought dozens of companies public prematurely, and shifting investor appetite from “growth at all costs” towards profitable growth.

Several companies have struggled to navigate these headwinds — since launching the Index about three years ago, six companies have been taken private or delisted (Doma, Latch, Matterport, Redfin, Vacasa and WeWork). I’ve written previously about consolidation in proptech, including Rocket’s recent acquisition of Redfin (since that post, Rocket also announced its acquisition of Mr. Cooper, the country’s largest mortgage servicer). Should we expect further M&A activity heading into the second half of 2025? I’ve compiled several data points below that give us a sense of where we are in the real estate cycle and how investor sentiment may evolve in the coming quarters.

Housing Supply

The COVID-era housing market was dominated by low cost capital and very tight housing supply — leading to a supply-demand imbalance that drove home prices up by 40%+ in most markets. Now, housing supply has increased significantly, with for-sale inventories growing on a year-over-year basis for 17 straight months.
According to Redfin, home sellers in the U.S. are sitting on $700 billion of unsold housing stock, the highest dollar amount ever. For-sale inventory is at a five-year high and 44% of listings have been on the market for over 60 days, the highest share since 2020.
Home price growth is now decelerating in 100% of the top 100 MSAs in the country. 25% of these MSAs are now seeing home prices decline on a YoY basis, up from just 5% one year ago.

Mortgage Rates and Housing Demand

The housing market remains paralyzed by high mortgage rates, which rose back to 7% in the aftermath of President Trump’s announcement of a new global tariff regime.
The disparity between pre-COVID and post-COVID homebuyers is striking — a typical homebuyer in 2018 now spends about 9% of their household income on housing, whereas a median buyer in 2024 pays more than 25% of their income on housing payments. Persistently high rates, without a reset of homes prices, is leaving many buyers on the sidelines.
The Federal Reserve is widely expected to keep its benchmark interest rate flat when the central bank's policy committee meets this week. The Fed appears to be in a wait-and-see mode as it watches for clearer signals about the path of the economy. Inflation is especially difficult to predict because tariffs may change the picture, but it’s not yet clear by how much. JP Morgan’s forecast puts the Fed Funds Rate at ~3% by Jan 2026, and believes mortgage rates could drop to ~5.75% by year-end.

Inflation & Sentiment

There have been several encouraging inflation reports this year, suggesting we are closing in on the Fed’s 2% annual inflation target. In April, the Consumer Price Index rose 2.3% on an annual basis, reflecting the lowest level since February 2021. On a month-over-month basis, the CPI rose 0.2%, lighter than the 0.3% pace forecast by economists. The Truflation index has been below 2% for most of 2025.
U.S. consumer sentiment improved in June, easing fears that Trump’s trade policies triggered major economic disruption, though views on the economy remain uneasy. The University of Michigan’s preliminary index rose to 60.5 from May’s 52.2, marking its first increase in six months. Still, sentiment is down about 18% from December 2024, when post-election optimism peaked.
The NFIB released their Small Business Economic Trends Report for May, and their headline figure, the Small Business Optimism Index, climbed 3 points to 98.8, edging back above its long-run average.
The U.S. continued to add jobs at a steady pace in May, and the unemployment rate remained at 4.2% for the third straight month.

Commercial Real Estate Activity

Through Q1 2025, national transaction activity declined 11.6% quarter-over-quarter and 8.0% year-over-year (by property count). Total transaction volume reached $69.3 billion, down 22.3% from Q4 2024 and 19% from Q1 2024.
The CMBS delinquency rate has climbed to 11% in June, its highest since 2013. Office and retail assets make up the bulk of distressed loans, with office accounting for over 50% of total delinquencies.

Since my last update, there have been a number of transactions impacting companies in the Index; as such, I’ve made the following changes:

The “Real Estate Services” category has been removed — Matterport was acquired by CoStar and Latch has been delisted from Nasdaq.
Porch has been moved to the “Digital Insurance” category; property insurance-related revenue makes up more than 50% of the company’s total revenue.
SmartRent has been moved to the “Vertical SaaS” category. SaaS revenue makes up about one-third of the company’s total revenue and is actively shifting to a “hardware-enabled SaaS model.”
Vacasa was removed from the “Short Term Rentals” section; the company was acquired by Casago in April 2025 for $5.30 per share.
Redfin was removed from the “Brokerage & iBuying” category; the company was acquired by Rocket Companies in March 2025 for $12.50 per share.
ServiceTitan was added to the “Vertical SaaS” category; the company went public in December 2024. ICE was removed from the “Veritcal SaaS” category; while the company owns Ellie Mae and other mortgage software assets, its mortgage-related revenue makes up less than 20% of the company’s total revenue.

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Ten Trending Topics

In lieu of a deep dive this month I am sharing several great articles and podcasts I’ve consumed recently that cover proptech, housing and the broader real estate market. Going forward, I’ll try to share at least a handful of links in each newsletter.

AI to Drive 165% Increase in Data Center Power Demand by 2030 [Goldman Sachs] Good research piece on the unprecedented scale of demand for electricy, driven by data center development globally. In 2023, U.S. data centers used 176 TWh of electricity, which was 4.4% of total U.S. electricity consumption. This is expected to meaningfully increase by 2028, with projections suggesting a consumption of up to 580 TWh, or 12% of total U.S. electricity.
Wall St. Is All In on A.I. Data Centers. But Are They the Next Bubble? [NYT] Private equity giants like Blackstone have poured hundreds of billions into data centers to capitalize on the AI boom, with Blackstone alone investing over $100 billion in buying, lending to, and building data centers through its acquisition of Quality Technology Services (QTS). The piece highlights Blackstone’s vertical integration in the data center category — from ownership stakes in construction and equipment companies to deep relationships with tenants (the hyper-scalers and AI labs).
Trends Report — Artificial Intelligence [Bond Capital] Comprehensive (340-slide!) overview capturing the AI moment we are in from Mary Meeker at Bond Capital. What’s most striking is the scale of adoption and infrastructure buildout in AI — the big six are spending $212B annually on CapEx (63% year-over-year growth). This isn’t just “cloud 2.0” – it’s the biggest infrastructure buildout in tech history.
Invasion of the Home Humanoid Robots [NYT] Humanoid robotics firm 1X is teaching robots to mimic human motion with surprising dexterity. The humanoid robot industry has attracted $7.2 billion in investments since 2015. My last post on AI in Real Estate touched briefly on “physical AI” as an emerging category — this piece offers a glimpse into near-future use cases in logistics, property services, and assisted living.
Watch These Construction Robots 3D Print a Walmart Extension in Just Seven Days [Archinet] Alquist 3D successfully completed a 5,000-square-foot Walmart extension using robotic 3D printing technology in just seven days, which is six weeks faster than their previous warehouse project and required only five workers instead of the 25-30 typically needed for traditional construction. The project, completed two weeks ahead of schedule, utilized a pair of RIC-M1 Pro construction robots with a new Mobile-Rail design and custom tool heads that enabled continuous printing, demonstrating the commercial viability of large-scale robotic 3D construction for commercial structures.
Rent-Setting Algorithms Find Legal Lifeline [WSJ] A provision in the House Republicans' recently passed tax bill would prevent state and local governments from regulating AI and automated decision systems for 10 years, potentially nullifying dozens of local and statewide efforts to ban algorithmic rent-pricing systems like RealPage.
The U.S. Housing Market Has Nearly 500,000 More Sellers Than Buyers—the Most on Record [Redfin] According to Redfin data, the U.S. housing market currently has nearly 500,000 more sellers than buyers (34% more sellers than buyers), the largest imbalance on record dating back to 2013, which is expected to cause home prices to drop 1% by the end of 2025. This buyer's market is particularly pronounced in Miami, where sellers outnumber buyers by nearly 3 to 1, and in the condo market, where there are 83% more sellers than buyers.
Real Estate Giants Wage War Over Coveted Private Listings [SF Standard] Two companies on our index — Zillow and Compass — are engaged in a battle over "private exclusive" real estate listings, with Zillow announcing that by the end of the month, any home listed as a private exclusive will no longer appear on its platform. Compass currently advertises more than 100 private listings in San Francisco alone, which are only available to their clients and not publicly distributed through multiple listing service (MLS) databases, creating tension in the industry as critics argue this practice restricts the market and allows Compass to double its commissions by representing both sides of transactions.
Voice AI is Working. Here’s Where It Wins First [NFX Blog] Venture firm NFX has a great piece about emerging voice AI use cases across a number of sectors, including home services, construction and real estate. I’ve seen a number of early stage companies building vertical voice AI solutions (several were featured on my top 50 list last month). These platforms can respond to customer calls and messages 24/7, with high accuracy at a fraction of the cost of human receptionists.
The Billionaire Behind Japan’s Art Islands Has One Final Jewel in His Crown [NYT] Naoshima, a tiny Japanese island, has become a global cultural destination thanks to many museums designs by architect Tadao Ando—highlighting the powerful interplay between art, space, and place-making. A tenth museum was recently opened on the island — worth visiting if you are traveling to Japan this year!

Thanks for reading! As always, please feel free to share feedback or thoughts on this newsletter — you can respond to this email directly or shoot me a note at nima@thomvest.com.

The Appraisal, April 2025 — The Top 50 AI Startups in Real Estate 🏆

Nima Wedlake

Apr 29, 2025

I’m excited to release the inaugural Real Estate x AI List, highlighting the top startups building AI applications within the real estate sector. Congratulations to the companies selected this year! A high-resolution version of the graphic is available here. The complete list and methodology is included below.

In 1968, an unassuming device quietly reshaped our relationship with computers: the mouse. Introduced by Doug Engelbart during SRI’s landmark “Mother of All Demos,” the mouse was unveiled alongside a suite of innovations that would shape modern computing — including word processing, hypertext, shared screen collaboration, and teleconferencing. This small, handheld device served as a vital bridge between human intention and digital execution, making computers more intuitive and accessible. In the decades that followed, the personal computer — propelled in part by this humble tool — reshaped virtually every industry and profession.

Today, large language models (LLMs) are delivering the next transformative leap. Where the mouse lets us point and click, LLMs now enable us to converse, create, and collaborate with machines. It broadens the scale of problems software can address and the industries it can touch—from healthcare and law, to accounting and education. We believe real estate is poised for a similar transformation.

Why Real Estate?

Despite a decade-plus of venture capital flowing into real estate technology startups, significant inefficiencies persist across the asset class. Thomvest’s early investment thesis in real estate touched on this:

Much of the inefficiency associated with a real estate transaction can be traced back to coordination hurdles. Multiple stakeholders are required to get a transaction across the finish line, including agents, lawyers, title companies, inspectors, appraisers, and notaries (the list goes on). In total, intermediaries capture more than $80B of transaction value annually.

Of course, some of this is inherent to the sector, driven by structural barriers to software adoption, including:

Real estate is a multi-player game — every real estate transaction or development involves dozens of stakeholders. This creates coordination friction and slows down tech adoption.
Real estate is highly localized and heterogeneous — real estate is not one uniform industry but thousands of hyper-local ones, each with unique regulations, processes, and data formats. This lack of standardization creates challenges in scaling across markets.
Real estate is cyclical — capital markets dictate the pace of activity in the sector. Today, high interest rates and rising labor costs have significantly cooled transaction volume; during these times, companies often postpone or reduce spending on technology.

The recent wave of AI advancements may finally create openings to tackle some of the sector’s most persistent inefficiencies. Unlike earlier software tools — which digitized only isolated tasks — modern AI systems can learn from messy, siloed data and even coordinate multi-party, multi-modal processes. This creates an opening for new use cases, new business models and new control points, sidestepping some of the adoption hurdles that stymied earlier startups.

The 2025 List — Early Winners & Themes

By our count, there are more than 750 startups building AI tools for real estate practitioners. This includes dozens of AI startups in every sub-category of real estate. Our goal in compiling the “Top 50” list is to present a snapshot of promising companies based on feedback from end-users and investors. Given the flurry of activity in this space, I expect the list to change meaningfully year to year, reflecting the period of innovation and iteration we’re in.

The pace of innovation both at the infrastructure layer and app layer of AI is astounding — it’s difficult to overstate the flood of smart technical talent and entrepreneurial energy into the category. ChatGPT launched publicly just over two years ago, acting as the starting gun for startups building AI apps. Today, foundational models are simultaneously more powerful and more affordable to deploy. As cost per unit of knowledge declines, new use cases and industries at the app layer are unlocked. My graphic above gets at this dynamic — AI systems are evolving to handle increasingly complex and creative use cases for end-users.

While we’re seeing entrepreneurs build AI startups across every corner of real estate, several key themes are emerging that help describe the nature of products being built:

Tackling Recurring, Lower Skill Work (The “Junior Analyst”)

AI streamlines labor-intensive administrative tasks—like scheduling, document drafting, and repetitive follow-up—allowing real estate teams to focus on higher-value work. I’d classify these companies as “sell the work” models that have become popular over the last year. This concept is particularly salient in real estate, where cyclicality leads to constant periods of understaffing and overstaffing. Interesting companies in the category include:

EliseAI provides a virtual leasing assistant that automatically responds to renter inquiries, schedules property tours, and follows up with prospects — automating roughly 90% of a leasing team’s routine workflows.
GreenLite is an AI-driven permitting platform that standardizes and automates the once-manual construction permit process across jurisdictions. It can reduce the time and labor needed for plan review by up to 75% per project, allowing developers to obtain permits faster while easing the burden on municipal building departments.
Rexera develops specialized AI agents to handle real estate closing workflows, from gathering HOA documents and lien searches to sending routine updates.
In the mortgage space, Maxwell (a Thomvest portfolio company) has built an AI-enabled “mortgage fulfillment-as-a-service” offering. This means lenders can outsource and automate underwriting, processing, and post-closing tasks.

Design & Pre-Construction Automation (“Generative First Drafts”)

Generative AI tools let architects, developers, and even non-experts rapidly produce and refine floor plans, building models, and interior layouts. By eliminating guesswork and manual drafting, they not only speed up design cycles but also expand the range of viable options for each project (here’s a fun recent example shared on X). Interesting companies in the category include:

Bobyard interprets landscaping and site plans, producing instant material takeoffs and cost estimates that replace hours of manual counting. This automation saves contractors time, improves bidding accuracy and speeds up client proposals.
TestFit applies generative design to produce optimized building layouts in seconds, accounting for zoning, density, and financial constraints. This turns multi-week feasibility studies into a more instant and iterative review process for real estate developers.
Cedar unifies public datasets with AI-powered modeling to generate multiple early-stage building configurations for any parcel, giving developers quick, data-driven insights into project feasibility and potential returns.

Data Capture & Analysis (“Instant Understanding”)

We are seeing broad adoption of tools designed to better capture and process both visual data (e.g., property photos, construction drawings) and textual data (e.g., sales contracts, loan agreements). Although it's still early days, the major AI labs have recently released impressive new models for OCR (Mistral) and image recognition (Gemini 2.5) that significantly advance the state of the art. I view this category as an important enabler to digitizing manual workflows in real estate. Interesting companies in the category include:

NavigateAI’s platform uses AI to automatically aggregate and analyze disparate real estate data, eliminating error-prone manual data gathering. By delivering instant, unified analytics, it enables professionals to make faster, insight-driven decisions in everything from market research to portfolio strategy.
Hover employs AI-powered computer vision to turn ordinary smartphone photos of a property into a precise 3D model, collapsing a multi-hour site inspection into a 15-minute digital workflow. This ensures contractors and insurers get consistent, accurate measurements and documentation with a fraction of the usual effort.
ZestyAI applies machine learning to high-resolution aerial imagery, automatically identifying property features and risk factors for over 150 million buildings. By replacing manual inspections with instant AI-driven analytics, it helps insurers and investors make quicker, data-backed decisions on property valuations and risk management.
DocumentCrunch uses AI to automatically analyze construction contracts and identify critical risk clauses and obligations. This streamlines contract review workflows, reducing manual review time and helping project teams ensure compliance.

Unblocking Bottlenecks (“Messy Inbox Problem”)

Real estate transactions often encounter slowdowns at specific choke points — whether it’s waiting on a mortgage underwriter, a legal review, or an appraisal. Much of the industry still runs on spreadsheets, emails, and repetitive workflows. AI is now being deployed to attack these bottlenecks and speed up the slowest parts of the process. These are often “agentic AI” models that are multi-modal and work across multiple systems. Interesting companies in the category include:

Keyway (another Thomvest portfolio company) streamlines complex commercial real estate transactions with an AI-driven platform that automates labor-intensive tasks — from extracting critical deal terms out of dense documents to instantly generating rental comps and pricing recommendations.
Valuebase can instantly appraise properties; they’ve built workflows for tax assessors offices to streamline the valuation process for local jurisdictions — a process that has historically been manual, highly subjective, and error-prone.
TurboHome is a fixed-fee real estate brokerage. Their platform automates transaction workflows to help agents close faster, reducing friction and overhead to support a low-cost, high-volume brokerage model.

Looking Ahead — Obstacles & Opportunities

We’re so early into the AI era — the contours of how machine intelligence will weave into every physical and financial workflow of real estate are only just beginning to come into focus. Yet turning that vision into tangible value across real estate will mean grappling with a host of challenges:

The tools and use cases in real estate are nascent, leading to an “enthusiasm vs. implementation” gap across most firms. This is to be expected — every major technical shift experiences a productivity paradox where where measurable productivity gains lag early adoption and excitement (for example, it took nearly fifteen years from the mouse’s unveiling in 1968 before it evolved into the everyday staple of personal computing). To help overcome this implementation gap, AI startups must prioritize tangible, immediate value creation for their customers — showcasing quick wins that demystify AI.
Another important question for startups in the category is how to out-compete incumbents with a distribution advantage and a mandate to integrate AI into their existing products. Procore, Rocket, Appfolio have leaned in to the AI narrative over the last year, as have many other public companies in our real estate index.
And finally, it’s important to consider the long-term value of verticalization in AI — by that, I mean the role sector-specific AI tools will play vs. general purpose AI (e.g. ChatGPT). There have been an influx of “horizontal” AI startups over the last year, for example Writer and Hebbia are making inroads selling into enterprises across multiple sectors. And last month, Chinese AI startup Monica launched Manus, “the first general AI agent,” capable of doing a wide range of tasks using a computer like a human would. In my view, vertical AI startups will build the models, integrations and workflows to win-out over general-purpose competitors, particularly in sectors with deep mid-market and SMB segments (like real estate).

In addition to the themes highlighted above, I’m tracking a few areas this year where I expect an influx of startup activity:

Physical AI: A common refrain when discussing the proliferation of AI within the sector is the physical nature of real estate that limits startups’ potential impact. That’s certainly a valid point, which speaks to why we’ve seen more immediate impacts of AI on purely white-collar industries like law, accounting and software development. We are in the early days of startups innovating at the intersection of artificial intelligence and the physical world, enabling robots and machines to perceive, understand, and interact with their surroundings autonomously. This is critical to breaking the five-plus decade streak of declining productivity in the construction industry. There are a handful of robotics startups targeting specific trades, like painting, landscaping and drywall. Expect robots to be deployed more broadly over the next decade, particularly in factory settings (e.g. modular construction) where physical conditions can be better controlled.
Better Generative Design Tools: The state of the art in generative design is rapidly improving — I expect an evolution from “first draft” tools to higher-fidelity outputs that can be relied on for more accurate renderings, schematic designs, interior staging, and even construction drawings. This has the potential to meaningfully decrease soft costs in a construction project.
Better Agentic AI Tools: I highlighted agentic AI earlier, but it’s worth emphasizing the opportunity here, particularly as these tools embed more deeply into existing systems (e.g., property management systems, loan origination systems). Much of the industry continues to run on spreadsheets, email, and repetitive workflows. I’m especially intrigued by agentic AI’s potential to address challenges point solutions could not—automating processes end-to-end, replacing human “middleware,” and seamlessly navigating across fragmented data systems and platforms (here is a helpful demo from Kairos to see this action). Recent releases of Model Context Protocol, Computer Use and Operator are just now getting implemented by startups. I expect additional improvements to agentic AI systems in the near future, including longer context windows, model interoperability, and better data security.

Thanks for reading! As always, please feel free to share feedback or thoughts on this newsletter — you can respond to this email directly or shoot me a note at nima@thomvest.com.

Complete 2025 List

Methodology: Thomvest selected companies for inclusion on this list based on proprietary criteria, taking into consideration nominations from dozens of venture capital firms investing in the real estate technology vertical, real estate operators and industry experts. Certain companies selected (as indicated above) are Thomvest portfolio companies.

The Appraisal, March 2025 — Unpacking the Rocket & Redfin Combination

Nima Wedlake

Mar 14, 2025

Welcome to the March edition of The Appraisal, a newsletter on real estate tech. My writing focuses on the 30+ public companies operating at the intersection of real estate and technology. This edition will focus Rocket’s recent acquisition of Redfin.

On Monday, Rocket Companies announced the acquisition of digital real estate brokerage Redfin for $1.75 billion in stock, implying an enterprise value of $2.36 billion and an EV / 2025 revenue multiple of ~2x. This price represents a 63% premium over Redfin’s 30-day average stock price before the announcement.

This acquisition will unite America’s largest mortgage lender with one of the most visited real estate search platforms. It’s a good outcome for Redfin and its shareholders — its core brokerage business has contracted over the last several years (Redfin’s stock price is down ~90% from its 2021 peak). The deal also offers a glimpse into how residential brokerage may evolve over the next several years — we should expect more “end-to-end home-buying platforms” that bundle multiple services including home search, agent services and mortgage, into a unified consumer experience.

However, Rocket shares were down as much as 15% on the news, signaling some investor skepticism about whether the anticipated synergies will materialize as planned. Let’s dive into the strategic rationale for the combination to better understand the risk and reward here.

1. Expands Massive Customer Pipeline

Redfin brings instant top-of-funnel scale to Rocket’s business. Redfin.com is a top-3 real estate search site nationally, with about 43 million monthly visitors (as of Q4 ‘24). This gives Rocket an enormous pool of potential homebuyer leads. Those visitors drive ~1M buyer/seller inquiries per year — a huge stream of home buyers who may need mortgages. This is especially significant for Rocket, given its stronger position in refinance compared to home purchase loans (12.3% refinance market share vs. 4.0% purchase share in Q4 ‘24).
In turn, Rocket can also funnel its own clients who lack an agent toward Redfin’s agents. The result is a bidirectional flow of leads: Redfin’s house-hunters can be converted into Rocket borrowers, and Rocket’s pre-approved borrowers can be handed off to Redfin agents, boosting conversions in both the brokerage and loan segments.
Redfin has already demonstrated an ability to attach mortgage and transaction-related services to the home buying experience — its mortgage unit had a 27% attachment rate on buy-side customers in 2024, a 5% attach rate on title, and a 61% attach rate on escrow.
By 2027, Rocket projects about $60M in revenue synergies from cross-selling (i.e. attaching Rocket mortgages and titles to Redfin brokerage deals, and vice versa).

2. Strengthens the Rocket “Superstack”

Rocket is repositioning itself as a broader consumer finance platform, inclusive of mortgage, personal finance, home search and brokerage offerings. Redfin’s strengths in home search and brokerage nicely complement Rocket’s mortgage-centric business. For example, a customer browsing Redfin can get paired with a Redfin agent and pre-qualified for a Rocket mortgage within minutes, integrating what used to be disparate steps.
This isn’t the first time Rocket has made a $1B+ acquisition to further its “Superstack” vision — in 2021, Rocket acquired Truebill for $1.3B (which was later rebranded to Rocket Money) and has successfully scaled the business to more than 4 million paid members and $100M+ ARR. They have a track record of integrating and growing consumer finance products that complement the core mortgage business.

3. Competitive Response to Zillow

Rocket is not the only company with “Superstack” ambitions — in a similar vein, Zillow refers to itself as the “Housing Super App.”
Zillow has aggressively expanded into mortgage origination in recent years, aiming to integrate financing with its home search platform. In 2018, Zillow acquired Mortgage Lenders of America and relaunched it in 2019 as Zillow Home Loans.
Zillow’s mortgage business is growing quickly — in 2024, Zillow Home Loans more than doubled its loan originations, funding about $3.1 billion in purchase mortgages, up 102% year-over-year. That is tiny compared to Rocket, which generated $101.2 billion in closed loan origination volume in 2024, but the growth rate is impressive and Zillow’s management team is focused on growing share here.
Both Zillow and Rocket are now converging on a similar end-to-end model: Rocket seeks to bring more buyers into its ecosystem “at the top of the funnel” via Redfin, while Zillow is moving down the funnel by attaching loans to its home shopper base.
Additionally, CoStar is a more recent, but formidable entrant into the portal wars via its acquisitions of Homes.com and Matterport. And Compass is aggressively building share in the brokerage space (the company is reportedly in advanced talks to acquire HomeServices of America from Berkshire Hathaway).

4. New Model for a Post-NAR Settlement World

The acquisition is happening against a backdrop of major changes in real estate brokerage commissions. As a result of last year’s NAR settlement, sellers are no longer required to pay a buyer’s agent commission by default, and agent fees have become much more transparent and negotiable.
Thus far, the overall commission structure hasn’t drastically upended – in Q4 2024, the typical buyer’s agent commission was ~2.37%, only a minor decline from ~2.45% a year prior. However, both buyers and sellers are increasingly aware that commissions are negotiable now, which should put downward pressure on commissions over the long-term.
The Rocket-Redfin combination can potentially offset lower commission revenue with other revenue streams (like mortgage origination and refinancing down the line). In a post-NAR settlement market, this could be a competitive advantage: Rocket-Redfin can pitch a better deal to consumers (e.g. lower fees or commission rebates), while still monetizing the customer through the mortgage and ancillary services. Traditional brokerages that rely solely on high commission splits may find it harder to compete if the norm shifts toward leaner fees.

5. Relative Value of the Redfin Asset

Redfin went public in 2017 at a $1.73 billion valuation. Eight years later they are getting acquired for $1.75 billion, despite tripling revenue and gross profit over that period. The deal value implies a ~6x EV / 2025 Gross Profit multiple.
Redfin’s core business is its discount brokerage — they charge a 1% fee when representing home sellers (as opposed to a 3% fee common at other brokerages). There are ~2,000 Redfin agents across 42 states — importantly, these are W-2 employees as opposed independent contractors (as is the norm at other brokerages). Redfin’s rationale here is that the combination of technology and in-house teams leads to higher productivity — Redfin’s agents complete 2.8x more transactions per year vs. the industry average.
However, the heavy fixed cost load has put pressure on profitability during a period of high interest rates and lower transaction volume. Brokerage revenue was $643 million in 2024, down from a peak of $903 million in 2021.
The company has had trouble achieving consistent profitability — Redfin posted an adjusted EBITDA loss of -$76 million and -$27 million in 2023 and 2024, respectively. And Redfin’s market share has flatlined over the last three years, hovering at sub-1% share:

I’d argue that Rocket is uniquely positioned to drive incremental value in this business. Redfin user base is under-monetized, and Rocket has built the best organization for converting digital leads into mortgage clients. There is a compelling opportunity to convert these high-intent organic visitors into mortgage and financing clients.

I’ve written previously about the potential wave of consolidation in proptech, driven by a tough macro and the value in bundling disparate workflows in real estate. It’s good to see two pioneers of the digital real estate come together, and I expect more large-scale M&A activity throughout 2025.

Thanks for reading! As always, please feel free to share feedback or thoughts on this newsletter — you can respond to this email directly or shoot me a note at nima@thomvest.com.

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