Title

Presentation

Blend Labs, Inc. misses on earnings expectations. Reported EPS is $-0.04 EPS, expectations were $0.02.

Operator: Hello, everyone. Thank you for joining us, and welcome to Blend Labs, Inc.’s first quarter 2026 earnings call. After today’s prepared remarks, we will hold a question and answer session. To withdraw your question, press 1 again. I would now like to hand the conference over to management for prepared remarks. Please go ahead.

Meg Nunnally: Good afternoon, and welcome to Blend Labs, Inc.’s financial results conference call for 2026 Q1. I am Meg Nunnally, Blend Labs, Inc.’s head of investor relations. Joining me today is Nima Ghamsari, our cofounder and head of Blend Labs, Inc., and Jason Ream, our head of finance and administration. Before we start today’s call, I would like to note that we refer to certain non-GAAP measures which are reconciled to GAAP measures in today’s earnings release and in the appendix of our supplemental slides. Non-GAAP measures are not intended to be a substitute for GAAP results. Unless otherwise stated, all financial measures we will discuss today, including our profitability, refer to non-GAAP. Also, certain statements made during today’s conference call regarding Blend Labs, Inc.

and its operations, in particular, our guidance for 2026, other commentary regarding 2026, and our expectations about markets, our strategic investments, product development plans, and operational targets may be considered forward-looking statements under federal securities laws. We caution you that forward-looking statements involve substantial risks and uncertainties, and a number of factors, many of which are beyond the company’s control, could cause actual results, events, or circumstances to differ materially from those described in these statements. Please see the risk factors we have identified in our most recent 10-K for fiscal year 2025 and our other SEC filings. We are not undertaking any commitment to update these statements if conditions change except as required by law.

The financial information presented on this call is based on continuing operations, and prior periods have been recast to operations that are now discontinued. Lastly, we will be providing a copy of our prepared remarks on our website by the conclusion of today’s call, and an audio replay will also be available soon after the call. I will now turn the call over to Nima.

Nima Ghamsari: Thanks, Meg, and welcome, everyone. It has been a whirlwind two months since our last call. We reported our Q1 numbers today, which Jason will spend time on, but they came in higher on revenue and non-GAAP operating income than expected. We also signed 15 new deals and expansions in the quarter, including an eClose deal with a top 20 bank along with a new mortgage deal with another top 100 bank. Our pipeline as of March 31, 2026 is up more than 40% year over year, and that does not include Autopilot pipeline, which I will cover in a minute. But the world has shifted underneath us in those two months. Increased global conflict, inflation, and rising mortgage rates, and that leads me to be a little conservative in the short-term numbers.

But I am incredibly optimistic about the future. My optimism comes from two things, and they are both tied to artificial intelligence. The first is Autopilot, which is our AI agent and orchestration layer that we put right alongside our customers’ work as they work with consumers. The second is the agents we are building inside Blend Labs, Inc., which are starting to do our own work. Together, I believe these two pillars give us a path to see 10% to 15% incremental growth already for us in 2027, on the top line, and more efficiency and speed as a company internally. Let us start with Autopilot. For those new to the story, Autopilot is our flagship AI agent. We unveiled it and rolled it out in beta almost exactly two months ago, telling our customers they could use it for free and try it out for all of Q2 to see it in action and help their business.

As of Monday, May 4, 2026, 65 lenders have activated Autopilot, 22 are running it live in production, and over 7 thousand applications have already been touched by Autopilot since we moved it to live production. And we are seeing that early results are improving, both in cycle time and in conversion rate. Two of our largest lenders are actively implementing Autopilot right now with go-lives planned for Q2, and we have three more top 20 logos in our net new pipeline that we expect Autopilot to be a meaningful catalyst for closing. In total, Autopilot is already sitting on $10 million in pipeline because it solves a real problem for our customers and the consumers they serve. But the more important story for me and for our company, for our customers and our shareholders, is how quickly that product is evolving.

We have been publishing details on our blog every week, and there are two that I want to call out. The first is Autopilot Chat that was rolled out about a month ago, a conversational interface where the borrower can ask Autopilot questions about their loan in plain language as they are going through the process. What documents are still needed? Why did you ask me for this specific thing? Why does it matter to my situation? What happens next? Instead of a static task list or making a phone call, the borrower can have a real contextual understanding of what is going on to help them through the process. This is the kind of interaction that consumers are starting to expect, and we are right on top of it. The second is something I am even more excited about, which is Autopilot MCP.

That opens up the Blend Labs, Inc. platform so that our customers can build their own agents on top of Blend Labs, Inc. or use Blend Labs, Inc. in a headless way in their existing workflows and still get the benefit of all the compliance, all the data model, the workflows, all the native integrations we built, and the intelligence layer of Autopilot. One of our large mortgage company customers has already built a voice agent using it, and I am seeing this as really important and really promising for our customers who want to own more and more things they can do but move really fast. And that pattern, customers innovating with us and around us rather than instead of us, is exactly what we want and exactly what we expect to see more of going forward.

What this all adds up to is something I think is really powerful. Our customers can now see a path from initial borrower touch all the way to clear to close without a team member ever having to touch a file. Now they still can work on the file, but they will not have to. That is fundamentally different value than we could ever offer before or the industry could ever offer, and something that I dreamed of being able to offer when I started the company in 2012, and now agentic AI has made that dream possible. And on top of that, eight weeks in, we are shipping at a cadence that Blend Labs, Inc. of years ago and most enterprise software companies would measure in quarters. And every one of those updates is grounded on what our customers need, what they are telling us they want, and how we can help impact and improve their business.

With adoption well underway, let me give you an update on how we are going to monetize this. Autopilot has been in preview to date, and our priority has been getting real customers live and proving the value. Starting in June, we are going to move to paid tiers. Now just like any modern software company, there is going to be some base capabilities built into our workflow that are going to provide intelligence, like, did you upload the right document? And that is useful. That is going to lower some friction for consumers to get started and understand AI. But the paid tiers are where the full product lives, what we call underwriting intelligence, where Autopilot is reading the documents, taking real actions on the loan file, running calculations, reconciling against guidelines, and driving the work forward.

Over time, our intent is to move the paid tiers of Autopilot to a per funded loan model, just like the rest of our mortgage suite. It is the right long-term structure, and our customers like that because it allows them to see and track the value on a per-loan basis, and we get paid when they make a successful loan. That is a great product for us, it is great alignment with our customers, and it incentivizes us to make sure this is providing real loan-level funded value improvements. When Autopilot helps a lender fund more loans with the same number of people, our revenue scales with their success, not with their headcount. And that is how we have always built Blend Labs, Inc., and that is even more important today in an agent-first world. We are going to continue to provide updates on Autopilot as more customers sign on, but I want investors to understand this is not a small incremental line item for us.

Autopilot is a whole new leg of growth for the company on top of the great mortgage and consumer banking suites that are already growing, and we plan to keep growing it. Before we move off Autopilot, I want to spend a minute on something that I think is really important and I keep getting asked about from investors. The billion-dollar question is, where does the durable value in enterprise AI actually accrue? This is an ongoing debate, and it is important to understand where Blend Labs, Inc. fits and how I see this. For the last couple of years, the focus of the industry and the world broadly has been on the foundation models: which model is the fastest, the smartest, the best in benchmarks, the cheapest, and that focus is understandable. But as models converge in capability and keep innovating, the durable value is shifting up the stack to the orchestration layer between the model and the workflow, to the area that people call the harness, and the thing that is driving actual end-business outcomes.

The harness, to put it clearly, is a system that channels the engine and all the tools around it into a reliable, controlled outcome, which is so important for an industry like ours, like financial services. And the data and the documents and the specific context of any moment is the fuel that makes any of that work actually useful. And Autopilot is exactly that. It is not a model. In Autopilot, we use the best available models underneath; instead, it is the orchestration layer that decides what to do given that exact moment in a loan. It retrieves the specific guidelines, gets the full context of the loan, runs the right calculations, validates the outputs against investor and regulatory requirements, updates the loan file, and triggers the native Blend Labs, Inc.

workflows that move the file forward. That logic is specific to that exact loan, the exact consumer in front of it, and it is the kind of work that generic AI is not built to do. It needs a system around it. And that is where Autopilot fits in. And Autopilot MCP just takes that to the next level. It allows the Blend Labs, Inc. platform users to build their own agents or even work with Blend Labs, Inc. in a completely headless way, which means the harness becomes a platform for them to move really fast because they get all the regulation, the compliance, the integrations, and the Autopilot intelligence out of the box, and they can build their own experiences and their own agents around that. That is a meaningfully different level of importance because now you become more of the engine, the “powered by,” instead of the interface.

And that is where agents can be really powerful. And that compounds more as we open up more capabilities for our customers to build faster and on top of us. And that is why I get more confident every quarter about where Blend Labs, Inc. sits in the AI landscape. We are the vertical industry harness for origination. We have the proprietary data to make that harness work. We have the business model already to help capture the benefit of automation and still give most of the benefit to the customer and, hopefully, the consumer. That is the durable place to be. That is why I am excited; that is where Autopilot is. We are bullish on our first pillar, which is agents for our customers. But I am even more bullish on how we are using agents internally.

Over the last few months, we have been building something we are boringly calling Blend Labs, Inc. background agents. It is not a new idea, but it is a simple idea. Anytime we get an input from the outside world — it could be a ticket, a customer issue, a feature request — before that reaches a team member, we want an agent to take the first pass of that work and take action on it, and then the team member reviews and approves it. In practice, that could be something like: a ticket comes in outlining a bug in our system. An agent immediately picks it up from our support queue, looks at it, identifies the bug, writes the code to fix the bug, tests the code to make sure the bug is now fixed, and then sends it to a human and says, “I have to change these 10 lines or 50 lines of code.

Can you approve this?” That moves our team from manually driving the car and making the turns and figuring out how to get from A to B to playing air traffic control with, hopefully, dozens of cars. To support that, we have given our agents access to our internal tools, our entire code base, the ability to stand up environments, and they will now take a first pass before our engineers or our support team ever see that issue. When I look at the numbers, the new process of how we are adopting AI at Blend Labs, Inc. has already resulted in more than 1.5x productivity in 2026 versus 2025, based on the number of pull requests our engineering team is doing, and we are just getting started. Prospects and customers are already taking notice of how fast we are moving.

I get notes from customers all the time. I have been on-site with our biggest customers in the last month, and I can tell you that momentum is palpable. Our customers have noticed a change in our quality and speed. I want to be clear. This is not a one-team experiment. This exact same pattern of agents doing the first pass of work should apply to every role in every company, and specifically in Blend Labs, Inc., it will apply to roles here. That could be something like onboarding a new customer, preparing a cut for a customer business review when we are going on-site with them, or even something as esoteric as getting a manual Excel worksheet that outlines what loans have been funded and doing that work before our accounting team even has to pick it up.

I said on the last call that we aim to be in the top 1% of all companies in terms of agentic AI adoption, and I really meant it. We are going to do it. It is something I am very passionate about, and we are going to keep driving for that. When done, I believe this effort, combined with Autopilot, has created the path to 10% to 15% more top-line growth and a lot more efficiency and speed for us. And that speed is probably the most important thing for any business, and especially for a company like Blend Labs, Inc. It means more customer issues fixed, more great features developed, more things like we have done with Autopilot, continuing to grow Autopilot, faster time closing a quarter, better preparedness for customer business reviews; these will be the new Blend Labs, Inc.

To wrap up, transforming a company of our size into an agent-first company is definitely more work and more complicated than the world understands. But it is worth it. We have a really important mission. Our customers serve millions of consumers across the country every single year, so this change cannot come fast enough. We are taking it as fast as we can, and we feel like, to be quite candid from my perspective, we are the best-positioned company in the space. It is something that I spend a lot of my time on, and the team is even more passionate about. So, while the war and tariffs and oil and all those things might create some conservatism around short-term mortgage market numbers, because the macro and the rollout time for what we are building also take some time, I have never been more energized about the medium term and, hopefully, even the long term for our customers, our team, and our investors.

And with that, I will turn it over to Jason to walk through the financials.

Jason Ream: Thanks, Nima, and thank you to everyone else joining us on the call. We delivered a strong start to 2026, with both revenue and non-GAAP operating income above the high end of our guidance ranges. Revenue grew 15% year over year, and our non-GAAP operating margin expanded to 13%, reflecting growth across the business and reflecting the operating leverage we have continued to build into the model. Total revenue in 2026 Q1 was $30.8 million, above the high end of our guidance range, driven by growth in mortgage and consumer banking alike. Mortgage Suite revenue was $17.2 million, up 18% year over year. Funded loans on our platform were approximately 187 thousand in Q1, up 29% year over year and slightly better than we had assumed coming into the quarter.

That strong volume growth was partially offset by a lower year-over-year economic value per funded loan, which came in at $84 in Q1, within the $84 to $85 range we discussed on our last call. We were at the lower end of our range primarily because of higher mortgage volumes, which lowers the per-loan economics calculation given some of the fixed-fee arrangements that we have within our customer base. Consumer Banking Suite revenue for the first quarter was $10.8 million, up 12% year over year and consistent with the color we shared on our last call. Professional services revenue for the first quarter was $2.9 million, up sequentially from $2.1 million in Q4. Of the $2.9 million in professional services revenue, approximately $600 thousand related to work completed in prior periods that was recognized this quarter under our revenue recognition policies.

We would not expect a similar catch-up amount in future quarters. Turning to profitability. Non-GAAP gross profit was $24.8 million, and our non-GAAP gross margin was 80.3%, up from 72.9% in 2025. I would note that gross profit in the quarter benefited from the PS catch-up that I just mentioned, as well as some one-time cost of revenue benefit that together brought gross margin for the quarter up by about two to three points. Please keep that in mind as you think about modeling gross margin going forward. Non-GAAP operating expenses were $20.7 million in Q1, up 10% year over year. As a reminder, the year-over-year comparison reflects the change in our internally developed software capitalization methodology that we discussed last quarter, where we are capitalizing less of our R&D personnel cost than we did in 2025.

This is an accounting treatment change rather than a change in the nature of our R&D investment. As a result, reported R&D looks elevated on a year-over-year basis, an effect that will persist to some extent in 2026 until we lap prior-year periods. Non-GAAP operating income was $4.1 million, above the high end of our $2 million to $3 million guidance range, and representing a non-GAAP operating margin of nearly 13%, an improvement of approximately 10 points compared with 2025. Free cash flow for the quarter was $7 million compared to $15.5 million in the prior year. We are pleased with the strong cash flow generation and want to remind you of our seasonal patterns, where Q1 is typically a strong collections quarter in our business. And our balance sheet remains strong.

We ended the quarter with $59 million in cash, cash equivalents, and marketable securities and zero debt. Putting our cash to work, we repurchased 11.2 million shares during the quarter at an average price of $1.66 per share under our share repurchase program, deploying $18.6 million of the $50 million authorization we announced on our last call. As we said last quarter, this program reflects our conviction in the long-term value of the business and our commitment to disciplined capital allocation. With zero debt and a solid liquidity position, we have the balance sheet to invest in both the business and in our shareholders simultaneously. Before I turn to outlook, I want to spend a moment on market share and on the macro environment. On market share, the initial release of 2025 HMDA data in early April showed approximately 4.4 million originations for the year, which puts our 2025 mortgage market share at approximately 17%, squarely in the middle of the 16% to 18% range we guided to back in November.

The HMDA data will continue to settle as late filings come in, but we do not expect that figure to move meaningfully. As we look into 2026, we expect a market share headwind of 100 basis points, primarily reflecting the volume roll-off of one large customer that we have discussed previously. At this time, we do not see any other significant headwinds to our market share. On the macro side, the spring housing market started on stronger footing than many had expected, supported by improving affordability and slowly rebuilding inventory. That said, the recent rise in mortgage interest rates adds uncertainty to the outlook. Fannie Mae’s most recent forecast calls for total mortgage market growth of approximately 19% year over year in 2026. But Fannie reduced both its second quarter and full-year 2026 outlooks earlier this month as rates have moved higher.

Our own 2026 view is anchored to that updated Fannie outlook. We will remain cautious in our outlook until rates come down meaningfully and refi activity picks up. We have the platform and the customer base in place to capture the upside when conditions improve. Now let us turn to guidance. For 2026 Q2, we expect total revenue to be between $32 million and $34 million, representing approximately 1% to 7% year-over-year growth. Underneath those headline numbers, we expect Mortgage Suite revenue to grow 4% to 10% year over year, driven by mortgage market volume growth and partially offset by a year-over-year decline in value per funded loan, which we expect to be in the $79 to $80 range in Q2. The decline in EVPFL from Q1 to Q2 is primarily driven by increased volume, which, as I mentioned earlier, mechanically lowers EVPFL.

We expect year-over-year Consumer Banking Suite revenue growth to be between negative 2% to positive 4% in Q2. We expect Q2 non-GAAP operating income to be between $5 million and $6.5 million, implying a non-GAAP operating margin at the midpoint of approximately 18%. A few additional notes on what is embedded in our expectations. Our Mortgage Suite business continues to be subject to macro volume fluctuations, and depending on the trajectory of mortgage rates and the broader housing market from here, Mortgage Suite revenue could moderate or even flatten out in 2026, particularly if refi activity remains soft. On per-loan economics, Q1 is typically the high-water mark due to seasonality, which is why we are guiding to a Q1 to Q2 step down from $84 in Q1 to $79 to $80 in Q2.

In the absence of an uplift from Autopilot, which is too early to quantify and is not baked into any of our expectations, we would expect EVPFL in the second half of 2026 to fluctuate with seasonality but still stay below Q1 levels. On consumer banking, growth is moderating based on the headwinds we discussed on our last earnings call. In addition, we have also seen softer macro-driven volumes on home equity as rates have moved higher. Combining these two factors, we expect single-digit year-over-year growth in consumer banking in the back half of 2026, with Q3 growth likely lower than Q4 given the year-over-year compares. And there is macro sensitivity in the home equity portion of our consumer banking business. If rates rise from here, our expectation would be to see additional pressure on those growth rates.

Finally, I would like to touch specifically on Autopilot. While we are incredibly excited about the potential for Autopilot to generate revenue upside, we would encourage investors to be cautious about incorporating this into models at this juncture. We hope and plan to provide additional information on potential impact to the outlook as we get past the free trial period and have a little bit more time under our belt. In summary, we feel very good about the shape of the business heading into the rest of 2026. Q1 marked our second consecutive quarter of year-over-year growth in mortgage. With churn now stabilized and the partnership model transition behind us, we expect most of the variability in mortgage revenue from here to be macro driven.

Cost discipline remains intact. We expect to continue to drive additional productivity and efficiency over the year as AI-enabled workflows compound across our internal processes, an effort that, as Nima discussed, is now well underway across the company. This is indeed an exciting time for Blend Labs, Inc. We hope that you are excited to be part of it too. And with that, let us open up the call to your questions.

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Operator: Thank you. We will now begin the question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. We ask that you pick up your handset when asking a question to allow for optimum sound quality. If you are muted locally, please remember to unmute your device. Please stand by now while we compile the Q&A roster. Your first question comes from the line of Ryan Tomasello with KBW. Your line is open. Please go ahead.

Ryan Tomasello: Thanks, everyone. Nima, in your prepared remarks, you mentioned that Autopilot and your AI initiatives present a path, I think, to what you said was 10% to 15% more top-line growth. Can you just put a finer point on what you mean by that, and what underpins your confidence in quantifying the benefits at this stage? And then maybe just turning to consumer banking: given the noise in that segment from the large customer churn, can you help us understand where the underlying revenue growth is running in that business for Q1? And then at a higher level, based on the data points you have given previously about, I think, a $2.5 million impact from that large client in consumer banking, it just seems like the growth profile there is coming in a bit weaker than what was initially hoped for. So, Nima, your broader commentary around how you feel about the strength of that business going forward. Thanks.

Nima Ghamsari: Yeah, great to hear from you, Ryan. I would start with our current pipeline. Our current Autopilot pipeline is about $10 million. We have only been in the market for just over a month now with pricing, and we have a lot of customers who have turned it on with really positive feedback. I mentioned two very large go-lives with customers. If we can keep up that momentum, think of it as 10% to 15% incremental on top of whatever other growth you may be forecasting, coming from Autopilot, which is what we see a path to right now. We obviously have to keep executing and have a lot of work in front of us, but the product is awesome and our customers love it. On consumer banking, the biggest headwind is from that large customer you called out, and they had a pretty big consumer banking line item.

On the positive side, we have some good-sized financial institutions going live with our wall-to-wall suite this year. Those rollouts are in progress, and we are excited about that. Once that hits, I think that will be a positive benefit. We also have great customers rolling out our Rapid home equity product as we speak, which will be another positive catalyst. The home equity market has macro factors as well, but there are enough new things happening on the consumer banking side broadly that make me feel really good about the consumer banking business.

Operator: Your next question comes from the line of Dylan Becker with William Blair. Your line is open. Please go ahead.

Dylan Becker: Hey, appreciate it. Nima, I appreciate all the color on Autopilot and Autopilot MCP. It sounds like a lot of customers are interested in piloting. I think you called out some of the early proof points around improved cycle times and conversion rates. Could you provide a little bit more color on what that looks like relative to a non-automated process to try to tangibly put some value on what customers are seeing and learning? And then how you are thinking about the deployment or utilization of the first-party agents versus some of the MCP-enabled agents, and maybe the economic variability between those? And then, as a follow-up for Jason, you called out the per-funded-loan dynamics and market share dynamics. It sounds like you are increasing market share with the customers that are coming online or being onboarded, but that is kind of working inversely upfront against per-funded-loan economics.

Can you remind us of the mechanics there, as well as when we would expect that to flip so those tailwinds work in tandem — market share growth inflecting alongside per-funded-loan expansion over time?

Nima Ghamsari: Yeah. On the impact, there are two anecdotes I will share for two of the customers who have been some of the biggest users. We help them track the cycle time and the conversion. The conversion drivers are less obvious, so I actually talked to one of our customers about this; I will get to that in a second. On cycle time, for one customer, for example, from application complete in Blend Labs, Inc. to closing disclosures being sent to the customer, it went from 29 to 21 days. That is a pretty meaningful improvement. It makes sense because customers have a lot of back and forth with consumers, and what Autopilot does in real time as the consumer is in the flow is find those things that will be the gotchas down the line.

It shows the consumer, “We noticed that this account is in the name of a trust. We need to get your trust documentation right now,” versus asking for it a few days later once an underwriter reviews it and sends it to a processor, which sends it back to the loan officer. It short-circuits the process in a positive way. Our hope with Autopilot plus some of the Rapid products — put those two things together, call it Rapid Pilot — is you can get an application started and approved, because Rapid gives you an approval and an offer up front, and then once that customer is ready to go, get them clear to close in a matter of minutes, or conditionally clear to close on an appraisal if one is necessary. Where I have been more surprised is why the conversion is so much better, but it makes sense: when you give people more certainty faster, we are seeing good conversion uplift too.

It is early, but that is even more valuable to our customers, because those are consumers who would be walking out the door that they had spent time and money on as a lender — not just credit pulls and other data pulls, but also their teams’ time and energy. As we can shorten these cycles and make the process of lending more real time, it fundamentally transforms the industry. On consumer banking, we are building out the integrations to all the consumer banking products for Autopilot. There is opportunity there now. There are fewer manual tasks in consumer banking, but there is a lot more volume of those tasks. While it may not be worth thousands of dollars per loan in consumer banking, the scale matters, and they have very big operations teams managing these processes.

Autopilot enables those teams to do a lot more volume. One other thing: rates really drive refi activity. If you are a mortgage servicer with a lot of refi volume, your only way to handle large volumes historically has been to scale up and scale down teams, and you cannot really predict when rates go down. The ability to create elasticity of workforce — with agents that a lender can spin up and spin down alongside their team, with agents taking a first pass — changes the economic profile of servicing and recapture. For our large servicing customers, I think it will change the way they do business because it will allow them to handle market fluctuations even better than on the purchase side.

Jason Ream: Yeah, good question, Dylan. We are seeing volume growth. As I mentioned, we had better volume in Q1 than we had expected coming into the quarter. Part of that is our customers doing better; part of that was the market being a little better than we expected in the quarter. Of course, we are always trying to add share and bring new customers onto the platform. As far as per-funded-loan economics — putting aside the seasonal variability that comes from the mechanics I talked about — we are doing a much more concerted effort now to drive growth year over year with existing customers. Things like Autopilot give us better pricing leverage coming into new customer situations. Obviously, Autopilot drives its own revenue stream, but it also gives us leverage in the core platform as well.

Rapid remains a driver as well on the refi side in particular. As Nima mentioned, refi is even more sensitive to rates than purchase, and we do not have a Rapid purchase product; we have a Rapid refi product. As rates come down, we should see a benefit in volume and revenue in that sense, but also, as we get more customers up on Rapid refi, we should see a benefit in PFL as well.

Operator: Your next question comes from the line of Joseph Vafi with Canaccord Genuity. Your line is open. Please go ahead.

Joseph Vafi: Hey, guys. Good afternoon. Thanks for taking my questions. Nima, just the most recent update on the Rapid product uptake — how you are seeing market reaction to them? Obviously, the market backdrop is not as strong as we would like, but any feedback you are getting?

Nima Ghamsari: I would reiterate what I said about this Rapid Pilot. Rapid plus Autopilot together is getting momentum and focus from our customers. It is a lot of what I spend my time on. I have had two on-sites with two very large banks and lenders in the last two weeks about this specific thing that they want to get live in Q2. In practice, our customers — especially for refis and home equity — want to be able to make an offer in real time and then fulfill the work they need to get done on that offer in real time. The combination of those two things has been incredibly powerful. On top of that, we have some very, very large customers going live with Rapid home equity — some of the top home equity originators in the country.

It is definitely a good time in the industry. If I had one criticism of myself here, it would be: how do I make this so easy to adopt that they flip a switch and turn it on, and now they have Rapid refi enabled in their environment? That is a challenge for us that we are thinking about going into the next couple of months, and we intend to make that happen. As we make that happen, our customers will be able to adopt it much more easily. That is a key learning for us from the Autopilot rollout: we made it truly self-serve for a customer to turn on, and we are seeing the adoption. The numbers we shared in terms of the number of lenders that have turned this on — think about large financial institutions turning on a new AI agent for their organization with the flip of a switch, even without calling us.

The most surprising part was we had fairly large banks turning this on in beta and production without us even knowing about it. Then we saw it start to stream through our logs and reached out to them. We are a product-led growth company. We like to talk to our customers to help them get the most out of our product, but making things easy to adopt is going to be very good for Blend Labs, Inc. Everything comes back to speed — speed of adoption, speed of iteration for our team. We showed that with Autopilot, and I am very confident we can take that micro-culture and those concepts to the rest of what we do at Blend Labs, Inc. I will end with one last anecdote. Autopilot MCP has unlocked a lot of doors for us. I was on-site with one fairly large customer last week, and their head of engineering was in the room.

The first thing he asked was, “We want to build this into our mobile app.” I said, great — you now have a way to do that. It is called Autopilot MCP. You can get all the capabilities of Blend Labs, Inc., and the intelligence layer of Autopilot, entirely in your own environment. He said, wow, okay. His first question to me after that was compelling: “Can I use this in other parts of my business? We do not use Blend Labs, Inc. for these other kinds of loans,” and he named a couple. I said, yes. Autopilot works. You can put custom guidelines in there yourself; you do not even need to talk to us. His eyes lit up, and he asked for a copy of the Autopilot MCP documentation, which we sent to him. Historically, those stakeholders struggled with how to fit their tech stack into the Blend Labs, Inc.

world, and now we have opened that up. We had another really interesting sales call with a fairly large bank. The digital leader came on the call — historically someone who felt a little bit displaced by us sometimes — and his first question was, “Can I use this with my current digital stack?” As soon as the answer was yes, with Autopilot MCP, he went from potentially being a detractor to saying, “Oh, wow. This is actually really interesting. Now I can give new digital capabilities, improve my customer experience, in a powered-by way that would take months, if not years, to do internally,” especially building agents that are this powerful and complex.

Operator: A reminder, if you would like to ask a question, please press star 1 now to raise your hand. Your next question comes from the line of Aaron Kimson with Citizens. Your line is open. Please go ahead.

Aaron Kimson: Great, thanks for the questions. Nima, in your conversations, how do customers perceive the value that Autopilot is providing today? Do you feel like it is still primarily being thought of as a component of tech budgets, or are financial institutions increasingly open to viewing agentic products like Autopilot as a component of their labor budgets? And then one more: You have been working with financial institutions for a long time now. Can you talk about the appetite for adopting new products faster today than in the past, and how they are thinking about build versus buy — the balance between adopting AI products from AI-native startups versus established software vendors like Blend Labs, Inc. — and then where the frontier labs fit in? I think we are all trying to figure this out for application software in general. Thank you.

Nima Ghamsari: It is interesting. Right now, companies are figuring this out as we speak, so they do not know the answer to that exact question yet. That goes to how we price this in the short term — to allow our customers to use it free for a few months, and even after that we will have flat pricing that is good for us economically and good for our customers, to give them time in the short term to make the right changes in their processes and organizations. Long term, they are aligned to the fact that labor does not need to be scaled up and down with volume anymore. I was having a conversation with the CEO of one of our large customers, and the idea of being able to scale their organization without having to add thousands or more heads is so compelling.

It naturally ends up being a labor question. But the more important value proposition, as numbers around conversion rates get set in stone and we have a better understanding, will be even more valuable to our customers. There are so many consumers in this country who can benefit from lower interest rates, or equity from their homes, or consolidating debt — things that have been historically hard for our customers to capture, and hard for consumers because they have to go through a lengthy process. If we can make it really transparent with something like Rapid and then really automated with something like Autopilot, it is going to reduce friction, and therefore consumers will do it, and they will do it with our customers. On adoption appetite and build versus buy, we are in an interesting place where a switch flipped sometime in the first quarter of this year — I think February 2026 — where our customers started to realize how important a transformation this is going to be.

Maybe it was because of the Anthropic Claude code explosion in the market. They started to realize the magnitude, and they have put budgets behind AI and AI initiatives. It is important for their customers, for their users, and for their long-term economics as a business. It can do really powerful things, and people are starting to believe that. It is no longer something they felt was a 2027 or 2028 thing; it is, “I can do this now.” The sheer number of our large financial institution customers that have turned these capabilities on on their own, and are in active discussions or in process with us of rolling them out broadly, speaks for itself. They do think through how this fits into their stack. Is it a company like Blend Labs, Inc. that is already driving a lot of their work, internally and for their customers?

Are they working with Anthropic or OpenAI or some other company in a big project in a consulting-like fashion? Or are they working with a small startup? In the Autopilot versus small startup frame, because we already have so much of the workflow happening in our system — natural entry points to invoke and spin up AI agents, and then spin them back down — we have a good advantage to help move very quickly for our customers. Our job is to make sure Autopilot is the best product on the market for the exact types of work our customers need to do; in this case, underwriting intelligence like I referenced in the prepared remarks. As long as we do those things, I do not think they will go to a small startup. We have to move fast, and we are moving fast; we have to build a great product, and Autopilot is a great product, doing things that a year ago would have seemed like science fiction to our customers.

On the labs versus a company like Blend Labs, Inc., some of that remains to be seen. I have heard of really great things the labs are doing with many of our customers. The size of the pie is probably a lot bigger than anybody understands. The labs are not going to go in and try to build into our workflow to drive value for our customers — I do not think they would — but even if they would, we are already there. We already have it. Speed is very important in adoption. If you have to do a nine- or twelve-month project to get something, versus being able to flip a switch, our job is to make that possible.

Operator: We have now reached the end of the Q&A session. This concludes today’s call. Thank you all for attending. You may now disconnect.

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