CCC Intelligent Solutions Holdings Inc. (CCC) Q4 2025 Earnings Report, Transcript and Summary

Good day, and thank you for standing by. Welcome to the CCC Intelligent Solutions Fourth Quarter 2025 Earnings Call. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Bill Warmington, Vice President of Investor Relations. Please go ahead.

Thank you, operator. Good afternoon, and thank you all for joining us today to review CCC's fourth quarter and full year 2025 financial results, which we announced in the press release issued following the close of the market today. Joining me on the call are Githesh Ramamurthy, CCC's Chairman and CEO; and Brian Herb, CCC's CFO. The forward-looking statements we make today about the company's results and plans are subject to risks and uncertainties that may cause the actual results and the implementation of the company's plans to vary materially. These risks are discussed in the earnings releases available on our Investor Relations website and under the heading Risk Factors in our 2025 annual report on Form 10-K, which we will file with the SEC later today. Further, these comments and the Q&A that follows are copyrighted today by CCC Intelligent Solutions Holdings, Inc. Any recording, retransmission or reproduction or other use of the same for profit or otherwise without prior consent of CCC is prohibited and a violation of United States copyright and other laws. Additionally, while we will provide a transcript of portions of this call, and we've approved the publishing of a transcript of this call by a third party, we take no responsibility for inaccuracies that may appear in the transcripts. Please note that the discussion on today's call includes certain non-GAAP financial measures as defined by the SEC. The company believes these non-GAAP financial measures provide useful information to management and investors regarding certain financial and business trends relating to the company's financial condition and the results of operations. A reconciliation of GAAP to non-GAAP measures is available in our earnings release that is available on our Investor Relations website. Thank you. I'll now turn the call over to Githesh.

Thank you, Bill, and thanks to all of you for joining us today. I'm pleased to report that CCC delivered another quarter of strong top and bottom line performance to cap off a solid 2025. For the fourth quarter of 2025, CCC's total revenue was $278 million, up 13% year-over-year and above the high end of our guidance range. Adjusted EBITDA for the fourth quarter was $119 million, also above the high end of our guidance range, and adjusted EBITDA margin was 43%. Looking at the full year 2025, revenue was $1.057 billion, up 12% year-over-year. Adjusted EBITDA was $436 million with an adjusted EBITDA margin of 41%. 2025 was a year of many significant milestones for CCC. We crossed the $1 billion revenue threshold for the first time, up more than $350 million since we went public in late 2021. 85% of our revenue now comes from subscriptions with continued strong EBITDA margins and annual free cash flow crossing $250 million for the year, also a record high. We also continue to benefit from exceptionally strong customer relationships. During 2025, we renewed and expanded numerous clients across the business, including several Tier 1 insurers and the largest collision repair provider in the United States. We also continue to add significant new customers across our markets. For example, adding two new auto manufacturers so that we now serve 14 of the top 15 OEMs in the United States. Our gross dollar retention was once again 99%, a testament to the value we provide and the strength of our client relationships. In aggregate, we ended the year with approximately 900,000 registered users of our solutions, who collectively process over $200 billion of commerce per year. Finally, we were thrilled to complete our acquisition of EvolutionIQ, a pioneer in AI claims guidance and the leader in bodily injury claims resolution. Throughout 2025, EvolutionIQ continued to add new customers and modules across disability and workers' comp product lines. And we were excited to introduce EvolutionIQ's capabilities to CCC's casualty customers. We anticipate continued momentum there in the years ahead. Looking ahead to 2026, we see a generational opportunity in front of us and CCC is uniquely well positioned to capitalize on it. I will cover this in three themes. Our excitement around the opportunity AI represents for our industry and CCC, how this reinforces our durable economic model and long-term growth; and finally, how we are approaching go-forward capital allocation in light of that strength. Turning to my first theme. The reason we're so excited about AI is that it's a powerful force that makes CCC's platform even more important over time. CCC's advantage has never been just a single model or feature. It is the combination of proprietary and hyper-local data, a deeply connected network and embedded workflows that allow complex decisions to be made reliably, consistently and at scale in an industry with a very high bar for governance, compliance and accountability. A common question we hear is whether rapid advances in AI that can establish platforms. Our experience says the opposite. In regulated multiparty industries like insurance, AI increases the need for trusted data, governed workflows and platforms that can operate safely at scale. As many of you know, CCC has been an AI pioneer and leader for over a decade. We were an early innovator in deep learning computer vision AI, having been among the first companies in any sector to bring AI solutions to market and have stayed at the forefront of every major AI leap since. Our AI solutions have been used to process tens of millions of unique real-world claims representing many billions of dollars. AI is embedded in our products, our support and our internal operations. While other companies talk about AI in theory, we have been in production at scale for years. Nearly $100 million of our annual $1 billion of revenue comes from real-world AI products that our customers use in their businesses every day. Importantly, these solutions are not stand-alone tools. They are embedded directly into mission-critical workflows where decisions carry financial, regulatory and operational consequences. All of this gives us a unique perspective into the generational opportunity AI represents for our industry and for CCC. Our industry, the insurance economy, is attempting to navigate many challenges, some common to other industries and some on its own. Like many industries, the insurance economy is facing a massive structural labor shortfall in the coming years. Insurance appraisers, collision repair technicians and many other roles are facing a wave of retirements with insufficient talent pipelines to fill the gap. Macro pressures and uncertainties add to this dynamic. Add to that, the enormous and never-expanding complexity of the insurance economy itself. An ecosystem with tens of thousands of companies, rapidly advancing vehicle technology, persistent medical inflation, changing regulations and many other forces are why more than 1 billion days elapse every year from auto claims being open to auto claims being closed. We began investing in AI more than a decade ago because we knew automation would be essential to navigating these long-term structural challenges, not because it was a short-term technology cycle. There is the same that Fortune favors to prepare, and we have been preparing for the insurance economy's inflection on AI for some time. We believe the industry is now entering a phase where AI moves from experimentation to scale deployment and CCC is positioned to be the platform on which that deployment occurs. As we look to scale this opportunity, execution discipline matters more than ever. This is why we strengthened senior product leadership with the addition of Josh Valdez as Chief Product Officer. Josh brings deep experience leading large-scale platform-centric product organizations, most recently overseeing global product management at Dayforce and previously at Workday. His background is directly relevant as we embed AI more deeply into mission-critical workflows and expand across products, customers and markets. Since joining CCC, Josh has been focused on sharpening prioritization, strengthening road map discipline and accelerating the delivery of capabilities that customers can deploy at scale. CCC has been a system of action for decades. While our platform does many things, at its core, CCC is a collection of incredibly complex, deeply interconnected and massively real-time decision engines for a highly regulated industry where outcomes must be governed, explainable and defensible. Hundreds of billions of dollars in payouts across the insurance economy every year and the path for AI to supercharge them is via those decision engines. Let me make this real. We were able to build highly effective AI solutions because we have an enormous repository of proprietary data representing more than $2 trillion of actual real-world outcomes. That data is contextual, claim-specific and continuously validated through real transactions, which is what makes it usable in regulated environments. Scale alone is not the challenge. The challenge is complexity. Insurance decisions depend on hyper-local pricing, insurer-specific rules, regulatory requirements and the coordination across many parties. What matters most is not what something costs on average, but what it costs for a specific vehicle in a specific location under a specific set of rules at a specific point in time. We do this for more than 20 million unique vehicles per year. And to do that, our systems process more than 2 million business events every day across 2 million labor rate profiles, 7.4 million part SKUs, 62,000 insurer audit rules, 5.5 billion live part quotes and more than 200,000 insurer-to-shop relationships and 13,000 unique jurisdictions. This is not a static data repository. It is a living operational system that reflects how work actually gets done in the insurance economy. From there, the output of those decision engines needs to be put into action. And the path for that is through the CCC network. CCC connects more than 35,000 companies, including 27 of the top 30 auto insurers, 30,000-plus repair facilities, over 6,000 parts suppliers, 14 of the 15 top OEMs and hundreds of software and service partners, all of them interacting and negotiating constantly throughout the day. These are not just workflows. They are the core operating rails of one of the largest industries on earth. The combination of our AI platform and network are contributing to customers increasingly looking to standardize their operations on CCC, and there are also many product advantages to doing so. For example, at the beginning of a claim, our AI can triage both damage to a vehicle and potential injuries to its occupants with substantial synergies in claims handling efficiency and customer experience. These benefits continue across the life of the claim or repair and are one of the reasons we are seeing auto physical damage customers increasingly choose CCC for casualty and also why we are seeing customers of all types purchase more of our core solutions in general. Over time, we anticipate that customers will increasingly want to leverage the full set of CCC solutions to maximize their investments in AI regardless of where or how those investments are developed. We fundamentally believe that AI is most valuable when it performs real work in our customers' businesses that impacts their end customers' lives. As customers increasingly embrace this reality, it drives greater reliance on CCC's platform, data and network. This dynamic is a massive long-term tailwind for both the industry and for CCC, and we are ready to enable it. I'd like to turn next to how this trend reinforces our durable economic model and long-term growth. While our AI has been battle tested and is in production across more than 125 insurers and over 15,000 collision repairs, we are still just scratching the surface of AI product penetration and monetization. Every client using our AI is different in terms of the particular AI products they've chosen to adopt, and they also differ in the velocity of that adoption. Over the past few years, our teams have spent considerable amount of time educating customers on AI and helping them work through the change management needed to leverage AI at scale within their organizations. This gave us great learnings from our early adopters, and we started to see a notable acceleration of AI adoption across our entire customer base in 2025. Our AI suite is the fastest-growing part of the CCC portfolio. AI has now grown to roughly 10% of total revenue, and we expect that contribution to increase over time. While adoption continues to scale, utilization today ranges from low single-digit to low double-digit percentages of total claims processed depending on the solution. This dynamic highlights both accelerating customer adoption and how early we remain in the adoption curve, giving us, in effect, a long runway for growth as usage scales. Because of our long track record in AI, we know how to build and deploy these solutions cost effectively. Our AI portfolio has a similar economic profile to the rest of our products, and they are configurable by customer instead of custom model builds. We have also seen strong results from the deployment of AI in our internal operations, and we anticipate additional gains as these grow in scope and usage. The strength of our business model has also enabled us to make other investments to capitalize on this opportunity. We developed and launched our event-based architecture IX Cloud to make it easier for customers to use our AI-enabled products across their businesses and have made substantial investments in talent to build on our leadership position. This includes key hires in sales and product management functions who bring deep experience in building, scaling and selling AI-driven solutions to enterprise and SMB clients. We have streamlined many of our packages and selling motions, and we'll continue to optimize these in the spirit of delivering top-tier value and reference level service. Our acquisition of EvolutionIQ didn't just bring world-class AI capabilities and a strong extension to our casualty portfolio, it also expanded CCC's addressable market beyond auto. EvolutionIQ's continued new logo wins in 2025 now gives us a customer roster of 9 of the top 15 disability carriers in the United States. EvolutionIQ also brought CCC into workers' compensation, the third largest P&C insurance line after auto and home. EvolutionIQ further expanded the scale of its workers' compensation opportunity by partnering with the largest TPA in the world to serve the self-insured market with strong early client traction. In addition, as we integrate EvolutionIQ more deeply into our auto casualty suite, we are beginning to see tangible progress in the cross-sell motion with our casualty customers. MedHub for casualty is gaining interest as insurers look to apply AI-driven medical record insights within complex injury claims. and we have signed our first casualty customer for this solution with several additional carriers in advanced stages of evaluation. We also cross-sold EvolutionIQ's workers' compensation offering to an existing CCC customer for the first time. This early traction supports our view that EvolutionIQ meaningfully expands our addressable opportunity in casualty and P&C in general over time. The strength of our economic model allowed us to deliver 41% EBITDA margins for the year despite making large-scale investments in R&D and absorbing some near-term losses from EvolutionIQ. The size of the opportunity ahead of us gives us confidence in our ability to grow at attractive rates while also increasing margins and free cash flow for many years to come. Finally, I'd like to make a few comments on capital allocation. We are incredibly excited about the growth pathways in front of us, and we are fortunate to have made many long-term investments ahead of this cycle to prepare us for this moment. While our top priority will always be product innovation, the strength of our business model enabled us to deliver more than $250 million in free cash flow last year, which affords us the flexibility to decide how we allocate excess cash and optimize our capital allocation. In recent years, we have been deliberate about returning cash to shareholders by buying back a significant number of shares. In Q4, we completed a $300 million share repurchase program, and our Board of Directors authorized an additional $500 million in repurchases, which we immediately activated by entering into a $300 million accelerated share repurchase transaction. We believe repurchasing shares is the best use of our excess cash, particularly at current levels that we believe meaningfully undervalues this business. As Brian will detail, CCC's strong fundamentals support ongoing top line growth, margin expansion and free cash flow generation. which will give us many opportunities to maximize total shareholder return while continuing to reinforce our position as the leader and product innovator in our industry. We look forward to a very exciting 2026. With that, I'll turn the call over to Brian, who will walk you through our financial results and outlook in more detail.

Thanks, Githesh. As Githesh outlined, 2025 was a year of important investments to support our long-term growth. From a financial perspective, revenue performance improved through the year, supported by strong momentum in our AI and emerging solutions, and we generated healthy adjusted EBITDA and free cash flow while maintaining a disciplined approach to capital allocation. Now let's turn to the numbers. I'll review our fiscal year and fourth quarter 2025 results and then provide guidance for the first quarter and full year 2026. For the fiscal year 2025, total revenue was $1.057 billion, which is up 12% over 2024. Adjusted EBITDA for the year was $436 million, up 10% year-over-year with an adjusted EBITDA margin of 41%. Excluding the impact of EvolutionIQ, adjusted EBITDA margin expanded over 200 basis points on a year-over-year basis in 2025. Now I'll turn to the fourth quarter results and detail out the performance. In the fourth quarter, total revenue was $278 million, which was up 13% from the prior year period and above the high end of our revenue range of $272 million to $277 million. Approximately 8 percentage points of revenue growth came from organic CCC and 5 points came from EvolutionIQ, which is consistent with our expectations. Of the 8% of growth, about 5.5 points were driven by cross-sell, upsell and the adoption of our solutions across our client base, including repair shop upgrades, the continued adoption of our emerging solutions and casualty. Approximately 2.5 points of growth came from new logos. In the quarter, emerging solutions contributed more than 2 points of total revenue growth, driven primarily by our AI-based APD solutions, subrogation, diagnostics and build sheets. Emerging solutions continue to represent an important and expanding part of our portfolio, accounting for approximately 5% of total revenue in the fourth quarter of 2025 and growing over 70% year-over-year. Industry claim volumes in Q4 declined 6% year-over-year. However, Q4 2024 had a large number of severe weather events. Normalizing out for those events, underlying claim volume in Q4 2025 were down less than 3% year-over-year. Claim volume decline continued to moderate throughout the year. Also, we have proactively been moving clients from transactional-based arrangement to subscription contracts on renewal. As a result, revenue tied to subscription contracts have continued to increase and now represent about 85% of total revenue. We expect the impact of claim volume fluctuation on our business to decrease over time. Turning to our metrics of software gross dollar retention or GDR and software net dollar retention of NDR. Please note that both of these metrics now include EvolutionIQ, and we are using annualized software revenue on a combined basis for the prior year to provide a prior year baseline for annualized revenue growth. GDR captures the amount of revenue retained from our client base compared to the prior year period. In Q4 2025, our gross dollar retention was 99%. This is in line with the past years. We believe the GDR reflects the value we provide and the significant benefits that accrue to our clients from participating in the broader CCC network. Our strong GDR is a core tenet of our predictable and resilient revenue model. Net dollar retention captures the amount of cross-sell and upsell from our existing client base compared to the prior year period as well as any movements in our auto physical damage client base. In Q4 2025, our NDR was 106, which is up from 105 in Q3 of 2025. Now I'll turn to the income statement in more detail. As a reminder, unless otherwise noted, all metrics are non-GAAP. We provide a reconciliation of GAAP to non-GAAP metrics in our press release. Adjusted gross profit was $211 million for the quarter with an adjusted gross profit margin of 76%. That's up sequentially and flat year-over-year. The underlying economics of the business continue to demonstrate leverage and scalability, and we remain confident in our ability to progress towards our long-term target of approximately 80% as newer solution revenue scales and offsets higher depreciation from recent investments. In terms of expenses, adjusted operating expense in Q4 2025 was $107 million, which is up 13% year-over-year, including the acquisition of EvolutionIQ. Excluding EvolutionIQ adjusted operating expense was flat year-over-year, reflecting cost discipline, flat year-over-year headcount and some phasing benefits. Adjusted EBITDA for the quarter was $119 million, up 12% year-over-year with an adjusted EBITDA margin of 43%. This was above the high end of the range, which was $106 million to $111 million, reflecting ongoing cost discipline, some phasing benefits, including the timing of hires that have moved into 2026 and stronger-than-expected revenue flow-through in the quarter. Excluding EvolutionIQ operating loss during 2025, full year adjusted EBITDA margins expanded over 200 basis points on a year-over-year basis. Stock-based compensation as a percent of revenue has come down throughout the year as we expected with Q4 being at 12% of revenue. Now let's turn to the balance sheet and cash flow. We ended the quarter with $111 million in cash and cash equivalents and $1.3 billion of debt. At the end of the quarter, net leverage was 2.7x adjusted EBITDA. We continue to deliver strong free cash flow generation. Free cash flow in Q4 was $105 million compared to $106 million in the prior year period. This reflects strong collections and favorable timing on working capital. Free cash flow on a trailing 12-month basis was $255 million, which is up 10% year-over-year. Our trailing 12-month free cash flow margin as of Q4 2025 was 24%, which is consistent with 24% at the end of 2024. We have used our strong free cash flow performance to return capital to shareholders through repurchases. In Q4, we completed the $300 million share repurchase program that we put in place in December of 2024 and announced a new $500 million share repurchase authorization. As a part of that authorization, we initiated a $300 million accelerated share repurchase program that delivered 80% of that value or approximately 33.2 million shares to CCC in mid-December. Upon completion of the ASR and the remaining $200 million buyback commitment, we will have returned over $1.1 billion to shareholders via repurchase over the last 2.5 years. We are committed to a disciplined capital allocation framework, which balances investment in the business and capital return to shareholders to deliver long-term shareholder value. Within the P&L, we will continue to prioritize organic investments in new product capabilities, including AI-based solutions, investments in top talent to execute against our strategic priorities and delivering efficiency across the business. Since going public, we have managed the balance sheet with net leverage under 3x, which we are comfortable operating with and given our growth trajectory and the strong free cash flow generation. We will continue to assess the best use of cash going forward, focused on returning capital to shareholders through share repurchases in the near term while being highly selective with inorganic investments. I'll now turn to guidance for 2026. As a reminder, this is a fully organic position now that we have anniversaried the acquisition of EvolutionIQ. For Q1 2026, we expect revenue of $273.5 million to $275.5 million representing 8.5% to 9.5% growth year-over-year. We expect adjusted EBITDA of $113 million to $115 million, a 42% adjusted EBITDA margin at the midpoint. For the full year 2026, we expect total revenue of $1.147 billion to $1.157 billion, which represents approximately 9% year-over-year growth at the midpoint. For adjusted EBITDA, we expect $477 million to $485 million, which implies a 42% adjusted EBITDA margin at the midpoint. So three things to keep in mind as you think about our Q1 and full year guide. First, we are seeing momentum and good progress across the business as we exited 2025, and we expect this momentum to carry into 2026. Demand across the portfolio remains healthy driven by continued adoption of our AI-enabled solutions, including EvolutionIQ as customers move from early-stage adoption to broader deployment and supported by ongoing cross-sell across our core platforms. Second, we remain confident in our ability to drive continued margin expansion in 2026, consistent with our demonstrated track record. We expect adjusted EBITDA margin in Q1 to expand by approximately 200 basis points year-over-year at the midpoint with expansion moderating down in Q2 due to phasing of spend and resuming year-over-year margin expansion in the second half of the year. This progression is driven by continued cost discipline and the operating leverage in the business. Third, we've made program changes to our equity plan, which, coupled with the business scaling positions stock-based compensation to decline as a percent of revenue. While we made the changes to the plan, we believe the program positions us to continue to attract and retain top talent. Share-based comp is expected to decrease from 17% of revenue in 2025 to 13% of revenue in 2026 with a path to single digits as we move into 2027. In closing, we feel good about the financial position of the business and the durability of our operating model. We crossed the $1 billion revenue milestone in 2025, supported by continued expansion within our existing client base. Our ongoing shift towards subscription revenue now approximately 85% of our total revenue continues to improve visibility and reduces sensitivity of claim volume fluctuations. We delivered solid margin performance and strong free cash flow generation, which enabled us to return meaningful capital to shareholders through share repurchases while maintaining a prudent leverage profile. The capital allocation framework remains consistent and disciplined, prioritizing organic investments to drive growth, maintaining balance sheet strength and returning excess capital to shareholders while highly selective on M&A and being focused on long-term value creation. The sustained margin discipline underscores the scalability and the efficiency of the core business as it continues to grow. Taken together, our predictable operating model, strong cash flow generation and the disciplined capital allocation positions us well as we move into 2026. Operator, we're now ready to take questions. Thank you.

[Operator Instructions] Our first question comes from Josh Baer from Morgan Stanley.

This is Lucas Cerisola on for Josh Baer. Touching on the debate around autonomous vehicles, there is a clear potential for claim volumes to be reduced at some point in the future. Could you anticipate your role, business model or the value you can provide to customers to change in the future?

Yes. This is Githesh. When we look at claims in general and we look at the business of our customers and how they operate, we look at really three things that are drivers. There's frequency of claims. There is severity, which is the dollars spent on claims. And third is complexity. What we have seen consistently is that while there's a small decline in claim frequency, what we see with indemnity or dollars spent on severity and complexity far outweighing any shift in frequency. And then, of course, we look at very specific places like San Francisco, where there's a lot more autonomous vehicles. And you may find this very interesting. Our data actually shows that there's actually slightly higher frequency of claims in San Francisco, for example, than the rest of California or the broader market in general.

Got it. That's super helpful. And then do you expect your large insurance carrier customers to in-house any software development for parts of the GCC workflows?

Our large customers have always built many components for themselves. So when you think about many of our customers, they have to build, whether it's a financial systems, claim reporting systems, it's a horizontal call center. It's a very broad set of solutions that go horizontally across the company. And where we come in is bring very deep vertical experience around claims, and we've integrated both of those two capabilities. And all our conversations with our customers that we've had over the last year, the last quarter continues to indicate that every customer is excited about expanding with us and with our AI and our solutions, working closely with their own systems.

Our next question comes from Shlomo Rosenbaum from Stifel.

Githesh, could you talk a little bit -- talk to us a little bit about the efforts that you made in the second half of the year and how they continued in the fourth quarter to get the EIQ deals implemented so that you could recognize the revenue because it seems like you had a very good selling motion, but there were some issues in terms of trying to get your customers to actually implement at the time frame that you were expecting. And if you can give us a little bit of a color on how that is progressing and how you expect it to progress in 2026?

I would say there were two lessons learned, Shlomo. One is that these are complex implementations. So what our team was able to do was to bring a lot of additional expertise and capability in terms of implementations and deployment. And we've also had significant learnings from the earlier deployments, and we were now able to apply that into the latest implementations. That's why you saw the significant bump in revenue from Q3 to Q4.

And then maybe you could talk a little bit more about some of the components of the EBITDA margin expansion. I understand there were some costs that were pushed forward, pushed into next year. But is there anything where you're getting just more leverage than expected or there's some kind of mix in what's going on that frankly, we're just seeing a faster margin expansion in the business that than expected. And I want to know if that's a trajectory that we should expect going through '26 as well.

Shlomo, it's Brian. I can take that. So I mean, we are very happy with the margin expansion that we saw in '25. When you strip out EvolutionIQ and the losses from them, we delivered about 200 basis points of margin progression year-over-year. And clearly, our EBITDA performance in Q4 was strong relative to the guide that we in the marketplace. So overall, feeling really good about the cost base and the margin progression. A couple of things to unpack. One is we did have flat headcount year-over-year. So we are seeing efficiency across the business. And we're putting substantial investment into the business. But at the same time, through productivity and the use of tools, we were able to maintain a flat headcount year-over-year. We also did have the benefit of some phasing. Some costs came out of '25 and into '26. I'd say that's not significant, but it did help the overall position. So yes, we're feeling good on the cost base as we move out of '25 into '26.

Our next question comes from Bill McNamara from Evercore.

This is Bill on for Kirk. Given the recent appointment of Josh Valdez and the accelerating pace of AI, how are you thinking about R&D spend in 2026?

Yes. This is Brian. Yes, we're continuing to focus on our investments in the business. There's a substantial road map of new solutions, product set that we're excited about. We'll continue to invest. At the same time, there are opportunities for efficiency, and we continue to deploy AI tools across the engineering teams. So we feel like we can invest in the business. At the same time, we'll see faster throughput and output. So we're feeling good about both the investment opportunities and being disciplined on our cost base.

On the one other point I'd add to what Brian is saying is that we are also in deep engagement across the board for every new solution we're building with clients and the receptivity has been nothing short of terrific. So we are very encouraged. And in terms of not only deployment implementations, but the feedback we're getting from customers about how excited they are about these new solutions.

Our next question comes from Dylan Becker from William Blair.

It's Faith on for Dylan. Obviously, a large opportunity ahead with AI. Any color on how you're thinking about the adoption curve going into 2026 and beyond now that you have a more solid base of early adopters that can service those early proof points? Kind of what does it take to get the rest of the network on board and expand deployment more broadly?

Yes. I would say maybe, Faith, two things to really think through, right? First and foremost, we are further along in terms of referenceable customers for pretty much every new AI solutions we have built, there are multiple customers, whether it's subrogation, whether it is casualty or our new solutions that came out for casualty with AI from -- with some of the AI work we've done with the EIQ team. So we are further along, more referenceable customers. So we are further along that curve. What we are seeing is the -- across our customer base, an increased propensity to want to deploy more AI more aggressively, but at the same time, super, super important for them that the controls, the transparency, all of that is super, super clear. And so those are really the two things we're seeing. So we are seeing that inflection point of customers starting to get much, much more excited about starting to roll this out into '26 as we roll from '25 into '26.

Our next question comes from Adam Hotchkiss from Goldman Sachs.

Githesh, I know you have AI solutions in a number of areas from repair to claims subrogation. Curious how you would qualitatively lay out for us where that $100 million of revenue from AI-based solutions is coming from most prevalently? And then where are you seeing the most incremental customer interest today over the last couple of months?

Sure. At a very macro level, I would say, as we pointed out, our emerging solutions grew 75% in Q4, and a big chunk of that was our AI solutions around auto physical damage. So if I break the business into -- at a very high level in terms of where we're deploying AI into three areas. auto fiscal damage for insurers. So we're seeing adoption of subrogation, reinspection, a whole bunch of tools for the insurance side. We're seeing adoption with repair facilities. I think we hit crossed the 15,000 mark of repairers starting to use our AI solutions. And of course, all of the solutions that our EIQ team develops, those are 100% AI, right? So as that scales and that continues to grow nicely, that is the second area, I would say. The third area of AI is really around casualty where we have introduced with MedHub, which is a medical synthesis solution that takes AI and really synthesizes medical documents. That's a very nice component to our traditional casualty solutions. We are seeing an interest there as well. So I would sequence my answer into those three buckets, AI for auto fiscal damage, AI for disability and workers' comp through the EIQ team and third for casualty.

Okay. Great. Really helpful, Githesh. Brian, one for you just on gross margin. A lot has been made industry-wide about how Gen AI will impact gross margins over the medium to long term. I guess, first, have you seen any impact from new solutions outgrowing the broader business on gross margin? And how do you think about the net impact of AI and other cost efficiency measures on gross margin over the medium term?

Yes. From a product perspective and a new solution perspective, I mean, the unit economics are strong. And when we look at the unit economics, they'll compare nicely to our existing product portfolio. So we think it will be additive to gross profit. It does cause a short-term gross profit pressure. When we launch the new product, we -- the support cost and we start to depreciate those new solutions, that cost outpaces the revenue until the revenue scales So we do have some pressure on gross profit just as we launch the new products. When those products get to scale, they'll start to be -- they'll contribute positive to the gross profit. As far as our tooling and internal production, that should be helpful to gross profit. And certainly, we think about that both at the gross profit level and at the margin level. And it's part of our ongoing guide as we think about getting to 100 bps of margin progression per year.

Our next question comes from John Barnidge from Piper Sandler.

My first question, going back to a comment I think you made, you cited frequency of claims in San Francisco being higher than the rest of the state. Can you talk about when that trend emerged, how much that is the case? And what correlation you think that has with introduction of autonomous driving vehicles within San Francisco?

This is really over a long period of time. When you look at -- we just looked at frequency in San Francisco in particular. And what we looked at, we looked at just a few quarters, right? We just looked at the last several quarters. And what we saw is that the claim frequency in general was slightly more elevated than the rest of California. So not too much more to draw or conclude from it other than with a lot more autonomous vehicles and a lot more taxi -- Waymos and the like, we just thought we'd do a little analysis of our data because we have full visibility to the country. And not more to add other than we just thought that was an interesting data point.

And then generally, Software-as-a-Service is kind of a dirty word these days. Can you maybe talk about why that concern is misplaced and how you actually have leverage being brought to you from that? I saw you mentioned headcount was flat year-over-year.

Yes. So let me start out with fundamentally how our business is architected, right? So first and foremost, our business, we have $2 trillion of historical hyper-local data. And that's an extraordinarily important piece because when you're settling an auto claim, it's not the price of the part or the availability on average around the country that matters. What matters is what is that price today for that particular labor rate for that particular car in that jurisdiction. So there's an enormous amount of hyper-local data that needs to be there. So our historical $2 trillion of data, daily transactions that we see that are continuing to update this data set in real time are an extraordinarily important piece of how this works in concert with our software. There are two other elements that are equally important. One is the network. the deep network of repair facilities interacting with parts providers, interacting with insurance companies, interacting with salvage yards, interacting with towers, interacting with rental, that interactivity across all the different participants is enabled by our software and that network capability makes it that for every customer being on that network, it creates a heck of a lot more value by being on that network. That's an extraordinarily important piece of it. And then last but not least, we then work with customers on very specific workflows that go across not only inside their company, but across different parts of the insurance economy to help move information, all of this ultimately feeding decision engines because at the end of the day, that's what people are doing is making a ton of decisions around the accuracy of the claim and the quality of the claim. And this is also an area where if you get it wrong, the threshold is a very, very high bar in terms of accuracy because you've got regulatory issues, you've got compliance issues, you've got a lot of these other issues. So we think the combination of having hyper-local data, a massive network with very, very deep workflows feeding these decision engines is really, really critical. So we think this combination of what we do makes us unique.

Our next question comes from Saket Kalia from Barclays.

Maybe I'll start with a financial question for you, Brian. I think we said that about 5% of revenue in Q4 came from the emerging products, and that grew, let's call it, at least 70% year-over-year. Can we just talk about which products are kind of driving that growth the most? And how you think about that growth in '26 as part of the guide?

Yes, absolutely, Saket. So within emerging solutions, we've seen really good progress on those solutions, the adoption. They are starting to scale. The areas or the products that are driving the majority of the growth, it's AI within our APD solutions. So that's key. Build sheets had a strong performance. Diagnostics had strong performance. So those are some of the key solutions that we're seeing that's scaling and growing fast. As we said, about 70% growth year-over-year. That will continue to contribute nicely as we go forward. We're not giving a hard number for the guide as far as what is being driven from emerging solutions, but we do expect it to continue to scale and be a larger part of the contribution going forward.

Got it. That makes a ton of sense. Githesh, maybe for my follow-up for you. You talked about the success of casualty within the APD base, and you've been talking about this for a while, and it seems like that's starting to gain a little bit of momentum. Can you just frame that opportunity a little bit for us? And what's driving some of that market share gains now in your view?

Yes. I would say when you look on a broad basis, out of x amount of dollars spent on an auto claim, roughly half and half is spent in terms of physical damage or the medical claim. So -- but what's happening is that there are two macro trends that we're seeing. One, the rate of medical inflation is running far stronger because inflation in physical damage is moderated. And so that's one aspect of it. The second aspect is that customers are really concerned, our insurance customers, in particular, very concerned about affordability of the policy for their policyholders. And as we've entered into these discussions, what we have been able to deploy and we now have more references of our customers using and deploying our casualty solutions and those references have actually created more references and more customers because we are able to actually perform and deliver performance in casualty for our customers. And we've also invested significantly in innovation over the years in addition to the latest component, which is the AI and the medical synthesis capability that came out of the work that we did with our EvolutionIQ team. So very simple, two points in terms of summary. We're seeing momentum because customers who are adopting, deploying are seeing great results that's creating momentum for other customers. And second, the innovation continues to be very strong.

Our next question comes from Alexei Gogolev from JPMorgan.

This is Bella on for Alexei. So, I wanted to ask, among your top 20 insurer customers, what percentage now have three or more AI modules live across the claim journey? And how strongly does multi-module attach correlate with overall product expansion?

I don't think we've given out that number on exactly how many modules by customer, but I will give you the macro trend that we're seeing across the board for every one of our large customers. What we are seeing is that the early adopters of our very first AI solution, Estimate-STP, have gained a lot of comfort and have gained a lot of confidence. And they have continued to roll that out across more states, more geographies and more customers are picking that up. But what that's also done is it's given us enormous amount of credibility using that visual AI capability to deploy solutions in reinspection in the front end of the claim, and we're also working with customers on subrogation. So I can tell you that across the board, we have more engagement across more products across all our top 20 customers.

Our next question comes from Gary Prestopino from Barrington.

I have two questions. Number one, Brian, in the guide, EvolutionIQ, what is that going to do? How much is that going to hit the margin? You said it was 200 basis points on adjusted EBITDA last year. I would assume it's going to diminish as we go forward. So...

Yes, Gary, we're not breaking EvolutionIQ out from an EBITDA perspective, but it's certainly part of the guide as we go forward. So when we think about the guide at the high end, it's 70 bps. At the midpoint, it's 50 bps. EvolutionIQ loss that was in '25 will continue to moderate out as we go through the year. as we further integrate the business, it's going to be less clear on the specific cost base of EvolutionIQ as we go forward. So we're going to just talk about it in our total EBITDA position and our total margin position. But it's baked into the guide that we gave.

But moderating, right?

Yes. Yes.

Okay. Then my other question surrounds AI, which seems like everybody is talking about. Does the fact that it's starting to -- you're seeing early positive proliferation throughout your client base. And obviously, it does -- it improves efficiencies. It helps to make better decisions. Does that eventually give you the ability to price that at a higher rate than your normal 5:1 for your standard products?

Yes, Gary, it's Brian. We certainly see the product launches and the work that we're doing with client, we're seeing really meaningful ROI benefits across those clients that are deploying the AI. So we feel really good on the return opportunities. We have not changed our pricing structure specifically for AI. We continue to focus on driving at the 5:1 ratio. And so that gives us a lot of confidence as we're going forward on the returns we're seeing and that our pricing structure is fit for purpose.

[Operator Instructions] Our next question comes from [ Peter Griffith ] from Citi.

It's Peter on the line for Tyler. Just a quick one here for me. Could you just talk about how customer deployment time lines trended with emerging solutions in the quarter and then just how you expect those to trend next year as well?

Did you say customer deployments? Could you repeat it? It broke up for me at the end.

Yes. Just the customer deployment time lines with emerging solutions, how that trended in the quarter and how you expect that to trend next year as well?

Yes. I would say what we saw in general is as we get further down the experience curve, our ability to deploy and implement these solutions are getting a lot better. And we also spent a lot of time, as we mentioned in the Q3 call and earlier that there's a lot of learning in terms of change management and other capabilities and many of the people we brought on board to help with it. So, we are seeing, I would say, better deployments and faster deployments. We would expect that with the experience curve anyway.

Our next question comes from Arvind Ramnani from Truist.

I guess lots of questions on AI. So I'll hop on to that. With some of these advancements in AI, particularly from folks such as Anthropic and OpenAI, is there like -- I mean, is there kind of a competitive threat that you worry about where some of your customers may kind of look to partner with them? Or do you think like kind of the industry has certain specific dynamics? Or is your data so unique where kind of a frontier model may not be able to really compete with what you're offering?

I'd say, Arvind, two or three things. So, first of all, this is not a hypothetical or a future. The fact is, as of today, our customers are all working with these companies. So this is something that's been going on for some period of time. We ourselves use models from all of these companies, whether it is in our software development or other areas, we use all of these tools. So, first and foremost, I would say this is not some new phenomenon. Our customers -- many of our customers have multibillion-dollar budgets. With that said, what we are seeing is that our customers are applying those capabilities on a more horizontal basis as it goes across their call centers, their policy systems, underwriting, claims, just a whole host of areas. And where they are working with us is on increasing and deepening the partnership around our specific models and AI and deployment around auto claims or casualty claims or disability claims or even workers' comp, where we just signed up one of the largest employers in the country to use our technology. So I think of this as not either/or, I think of this as and.

Terrific. That's helpful. And I guess, I mean, are you all doing anything kind of -- I mean, I guess, maybe you have not announced it, but are you all working with any of these frontier models kind of in a specific way?

Of course. The answer is we work with seven different companies of all kinds and have been for several years.

Terrific. And then just last question for me. Is that kind of pressuring the cost side? Or is there enough of revenue and margins where that hasn't really shown up in the financials?

Arvind, remember, we also have a decade worth of expertise in building, deploying AI. We get all the way down to whether certain calculations are FP8, FP16, FP32, which particular GPUs we're deploying for which particular models, whose cloud we're using for which models. So we have a fairly sophisticated approach to understanding the hardware of the deployment, the training and the inference models at a level of granularity and specificity. So after doing this for a decade, we have built that expertise in-house.

I'm showing no further questions at this time. I would now like to turn it back to Githesh Ramamurthy for closing remarks.

I just want to take the opportunity on behalf of all of us at CCC to say thank you. '25 was a milestone year for us in large part because of the tremendous trust that our customers have placed in us, a terrific group of people at CCC and a wonderful group of partners. 2025 was a strong year of execution and durable growth. And with the momentum that we have, we feel our platform is more essential than it's ever been. It's helped us deepen our customer relationships and with disciplined capital allocation, we have a lot of confidence in long-term growth and value creation. And I would just like to wrap up by saying a huge thank you for our shareholders for placing the trust that you do in us. Thank you.

Thank you for your participation in today's conference. This does conclude the program, and you may now disconnect.