UiPath (NYSE:PATH) reported first-quarter financial results on Thursday. The transcript from the company's first-quarter earnings call has been provided below.
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The full earnings call is available at https://uipath-q1-2027-earnings-call.open-exchange.net/registration
Summary
UiPath Inc reported a strong start to fiscal 2027, exceeding guidance with Q1 ARR reaching $1.901 billion, up 12% year-over-year, and revenue of $418 million, up 17% year-over-year.
The company achieved its first GAAP profitable quarter with a non-GAAP operating income of $92 million, representing a 22% margin, driven by operational efficiency and disciplined execution.
Strategic initiatives include the expansion of AI products, with 16 of the top 20 deals incorporating AI, and the launch of UiPath for coding agents to accelerate automation deployment and reduce operational burdens.
Future guidance for Q2 2027 includes revenue between $395 million and $400 million, and ARR between $1.929 billion and $1.934 billion, with a non-GAAP operating income of approximately $75 million.
Management emphasized the integration of AI into customer discussions, the growing adoption of process orchestration, and the importance of maintaining a platform that combines deterministic automation with agentic AI solutions.
Full Transcript
Megan (Conference Operator)
Good day everyone. My name is Megan and I will be your conference operator today. At this time I would like to welcome you to the UiPath first quarter 2027 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time and if you have joined via the webinar, please use the Raise hand icon which can be found on the bottom of your webinar application. If you have dialed in by phone, please press star 5 to raise your hand. Please note that all participants will be limited to one question and one follow up. At this time I would like to turn the call over to Elise Verlani, Vice President of Investor Relations.
Elise Verlani (Vice President of Investor Relations)
Good afternoon and thank you for joining us today to review UiPath's first quarter fiscal 2027 financial results which we announced in our earnings press release issued after the close of the market today. On the call with me are Daniel Dynes, Founder and Chief Executive Officer, and Ashin Gupta, Chief Operating and Financial Officer to deliver our prepared comments and answer questions. Our earnings press release and financial supplemental materials are posted on the UiPath investor relations website. These materials include GAAP to non GAAP reconciliations. We will be discussing non GAAP metrics on today's call. This afternoon's call includes forward looking statements regarding our financial guidance for the second quarter and full year fiscal 2027 and our ability to drive and accelerate future growth and operational efficiency and grow our platform, product offerings and market opportunity. Actual results may differ materially from those expressed in the forward looking statements due to many factors and therefore investors should not place undue reliance on these statements for a discussion of the material risks and uncertainties that could affect our actual results. Please refer to our annual report on Form 10K for the year ended January 31, 2026 and our subsequent reports filed with the SEC. Forward looking statements made on this call reflect our views as of today. We undertake no obligation to update them. I would like to highlight that this webcast is being accompanied by slides. We will post the slides and a copy of our prepared remarks to our Investor Relations website immediately following the conclusion of this call. In addition, please note that all comparisons are year over year unless otherwise indicated. Now I would like to hand the call over to Daniel.
Daniel Dynes (Founder and Chief Executive Officer)
Thank you. Elise Good afternoon everyone. Thanks for joining us. We deliver a strong start to fiscal 2027, once again exceeding our guidance across all key financial metrics. Before I dive into the results, I want to take a moment to reflect on our progress over the last year. In May of last year we launched our agentic and business process orchestration products into general availability. One year in adoption has moved from early experimentation to production deployment. We are seeing this play out across three areas in install based expansion, process orchestration adoption and vertical AI workflows. A great example is one of the largest healthcare distribution companies in the US. One end to end workflow combining UiPath agents and deterministic automations is expected to drive multimillion dollar annual savings which led to a seven figure expansion in the quarter. One of the world's largest construction companies adopted our purchase to pay vertical solution and told us they chose UiPath not as a software vendor but as a strategic co development partner for their enterprise AI transformation and the Fortune 500 energy company placed UiPath at the center of a $70 million cost reduction initiative made possible by our ability to bring deterministic agenda and process orchestration together as a single platform. Turning to the quarter, first quarter ARR reached $1.901 billion up 12% year over year, driven by $49 million of net new ARR and revenue of $418 million up 17% year over year. We grew first quarter non GAAP operating income to $92 million at 22% margin driven by improved operational efficiency and disciplined execution across the business and we deliver first quarter GAAP profitability for the first time in company history. This quarter's performance is built on the strength of our enterprise automation install base, thousands of customers with deep platform adoption, proven ROI and a track record of expanding with us over time and it reflects continued momentum with our AI products. In the quarter, 16 out of top 20 deals included AI and expansion deals that included AI were six times larger than those that did not. The drivers behind these results are the same core differentiators we outlined last quarter our platform that brings together deterministic and agentic automation with enterprise grade process orchestration, our install based flywheel, our governance foundation and our ability to combine a horizontal automation platform with deep vertical solutions. I saw that momentum firsthand across our global events, including in India at our annual Fusion event and DEFCON Developer conference. Across customers, developers and partners, the message was consistent. Enterprises increasingly need a platform that can govern and orchestrate humans, agents, workflows, automations and systems, an area where UiPath has a structural advantage. At DEFCON, we launched UiPath for coding agents, enabling developers to connect their coding agent of choice to create, test, deploy and manage automations across the full lifecycle. On the UiPath platform with enterprise grade governance and reliability built in. This matters because nearly every customer conversation surfaces the same constraint. An automation backlog that outpaces their capacity to build and maintain implementation is often the hardest part, particularly in complex enterprise environments where upstream system changes can drive maintenance costs over time. By combining coding agents with the governance, orchestration and self healing capabilities built into our platform, we can dramatically reduce that operational burden and compress deployment timelines from quarters to weeks. We expect this to accelerate time to value for our customers, drive deeper adoption and strengthen long term retention across our customer base. Our internal teams and customers are also seeing great results with coding agents, including one of the world's largest consumer electronics companies which reduced a four week project built to three hours and one of the world's largest chip manufacturers reduced a two month project built to a few days. What stood out most this quarter is how clearly customer priorities have evolved with the focus consistently centered on process orchestration. As one customer put it during DEFCON, models are easy, orchestration is not that directly reflects what we hear across our customer base. Customers are no longer asking us simply to deploy more agents or generate more code. They are asking us to transform how entire business functions operate through end to end workflows that span departments, connect systems and deliver measurable operational outcomes. And delivering that kind of transformation requires more than individual AI agents. It requires a platform that can orchestrate agents, automations, APIs, systems and people together within secure governed enterprise workflows. A great example is one of the world's largest telecommunications companies with nearly 2000 processes already automated and over $30 million in annual cost savings. They are now expanding their deterministic base further and moving into agentic workflows, building a pipeline of more than 200 additional deterministic automations and over 20 agentic use cases. That same process orchestration capability also drove a competitive displacement with the Fortune Global 500 electronics manufacturer, where we were the only platform that could take them from task based automation to enterprise wide business process orchestration. Building on a strong deterministic foundation, they are now expanding across manufacturing and supply chain workflows, using Maestro to coordinate automations, agent systems and human decisioning globally. Maestro already excels at structured workflows like invoice approvals and deployment pipelines where the process itself is clearly defined. But increasingly enterprise work is nonlinear and it's dynamic, exception driven and centered around decisions that move across teams and systems. This is why at DEVCON we launched Maestro Case into Public preview, extending Maestro beyond traditional process orchestration into the orchestration of unstructured enterprise work. The breadth is what makes UiPath the most complete process orchestration and automation platform in the market and it's already driving broader customer adoption, including Sonic Automotive, an early adopter of our Genti products. They initially deployed UiPath to automate vehicle stocking and sales lead follow up. They are now standardizing their genetic automation strategy on the UiPath platform under a broader C suite initiative and expanding into workflows such month end close and employee onboarding. The key driver of the expansion was Maestro Case's ability to orchestrate complex multi stage workflows across agents, automations and people. Beyond process orchestration documents remain one of the biggest sources of friction in enterprise work and customers are increasingly turning to UiPath IXP to automate document intensive workflows at enterprise scale. In May we were named a leader in the Forrester Wave document mining and analytics platforms Q2 2026. We are seeing that momentum translate directly into largest enterprise deployments and competitive wins. A great example is the leading medical technology company that is standardizing on UiPath IXP to automate high volume unstructured documents like invoices and purchase orders. The customer is already realizing approximately $5 million in annual savings and expects that to grow to $10 million as they scale. Demand for industry specific governed workflows continues to grow as enterprises increasingly adopt purpose built AI solutions tailored to their business. What differentiates UiPath is our ability to combine those deep domain specific solutions with the same process orchestration, automations and governance platform. This quarter we expanded our portfolio across financial services, retail and manufacturing and the office of the CFO. We are already seeing momentum in health care in a seven figure new logo win, a leading Latin American health care provider, selected our vertical solutions to support revenue cycle management, medical records summarization and claim denial management and expect $12 million in cumulative benefits. Customers are also realizing meaningful operational benefits from these vertical solutions. A leading healthcare technology company reduced clinical summary review times by 90% using our Medical record summarization solution. We are seeing similar momentum in financial services. Original bank is now automating 61% of sanctions hit reviews with our transaction screening alert review solution processing roughly 14,000 alerts per month. AI is accelerating software creation but is also accelerating the need to validate it. As code volume grows, so does the testing burden. Independent research work has consistently recognized UiPath as a leader in this space and we believe that validation reflects a real and growing structural advantage. Test Cloud is at the center of that, helping customers move testing from a downstream bottleneck to a continuous intelligent function embedded across the delivery lifecycle. One example this quarter is a leading US utility provider that adopted UiPath Test Cloud for agentic testing to streamline customer platform support launch. The solution is expected to significantly reduce manual testing while generating nearly $3 million in savings during the port. We continue to deepen our partnerships across both go to market and technical integrations. This included our expanded collaborations with Deloitte embedding UiPath Test Cloud into their Ascend delivery platform, bringing agentic testing capabilities to Deloitte's global client base. We are seeing similar momentum with Accenture, a Life Sciences customer we highlighted last quarter, worked with Accenture to deploy a global agentic sales entry solution and has now scaled this across 70 countries. Building on that success, they signed a seven figure expansion and are now partnering with us to design an office of the CIO intake solution built on our process orchestration platform. On the technical side, we continue to broaden our reach across key enterprise ecosystems. With Microsoft, we integrated UiPath with their security test suite to help automate threat detection and response. With Salesforce, we launched a new Agent Exchange offering that extend Maestro process orchestration across Salesforce and back office systems. With Google Cloud we brought our IXP solution to their marketplace. And with Databricks we connected their data intelligence platform directly with UiPath process orchestration to help enterprises move from data insights to automated action within governed workflows. In summary, this quarter reflected disciplined execution across the business, continued AI adoption and growing momentum across our platform. No other vendor can bring together deterministic automation, agentic AI document intelligence and business process orchestration on a single platform, and that complexness is what customers are standardizing on. We believe we are uniquely positioned for this next phase of enterprise AI adoption, and our strong start to fiscal 2027 reinforces both the durability of our business and the scale of the opportunity ahead. Before I turn it over to Ashim, I want to take a moment to acknowledge the loss of our dear friend and board member Soma Segar. Soma was the longtime investor in UiPath and rejoined our board just eight months ago. His impact on UiPath was immediate and profound. He was a mentor, trusted advisor and someone I deeply admire both professionally and personally. I will miss him greatly and I know our entire board and leadership team share that feeling. Our hearts are with his family. With that, I'll turn the call over to Ashin.
Ashim Gupta
Thank you Daniel and good afternoon everyone. Before turning to the financials, I'd like to provide a quick operational update. We continue to make meaningful progress across the key priorities we outlined last year Our partner ecosystem is becoming more deeply integrated with both our go to market motion and customer adoption efforts helping us scale larger enterprise deployments across industries. As Daniel mentioned, partners like Deloitte and Accenture are increasingly instrumental not just in selling but in helping customers operationalize and scale AI driven workloads and we are seeing that play out across financial services, healthcare and other key verticals. At the same time, our internal focus on customer adoption remains a central operating priority. We continue to invest in our services, organization and industry expertise to help customers accelerate deployment and expand platform usage. A key part of that effort is our Forward Deployed Engineer program which we launched six months ago. FTEs are proving to be an effective bridge between product innovation and customer deployment, shaping vertical workflows directly in customer environments and accelerating time to value. In addition to adoption, our go to market teams are executing with discipline and customer centricity. AI is now part of virtually every strategic customer conversation and those discussions are increasingly expanded into platform orchestration and vertical solutions. The deal data Daniel mentioned reflects that AI was included in 16 of our top 20 deals and expansion deals that include AI were six times larger than those that did not. Finally, on operational efficiency, AI is changing how we run the business. Internally, we are seeing increased operating leverage across the organization while continuing to invest deliberately in R and D vertical solutions and customer facing functions. Turning to the Quarter Unless otherwise indicated, I will be discussing results on a non GAAP basis and all growth rates are year over year. I also want to note that since we price and sell in local currency, fluctuations in FX rates impact results. Since the time of our last earnings call through the end of the first quarter, rates remained largely stable and resulted in an incremental tailwind to our first quarter arrangement and revenue results of less than $1 million. First quarter revenue grew to $418 million, an increase of 17%. Normalizing for the year over year FX tailwind of approximately $7 million. Revenue grew 15%. ARR totaled $1.901 billion, an increase of 11%. This included a $9 million year over year FX tailwind. Net new ARR was $49 million normalized for foreign exchange and the impact of M and a net new ARR improved on a year over year basis. Our dollar based gross retention rates remained best in class and 97% and our dollar based net retention rate was 109%, underscoring the durability of our customer base as they embrace our agentic automation solutions. Adjusting for FX, dollar based net retention rate was 108% demonstrating stabilization across our business. We ended the quarter with approximately 10,550 customers. Attrition continues to be concentrated amongst our smallest customers. While customers generating more than $30,000 in ARR grew 7% year over year. That dynamic is also reflected in our cohort performance. Customers with $100,000 or more in ARR increased 11% to 2,624 and customers with a million dollars or more in ARR increased 18% to 374. Our customer strategy has continued to focus on deepening our presence within the world's most complex enterprises where we see the greatest opportunity for long term expansion. Consistent with that strategy, we continue to add new enterprise customers with significant long term expansion potential including new logos like Candela Medical Tire Rack, shoprite Holdings and a global semiconductor company who is replacing a legacy rpa vendor with UiPath as their strategic automation platform. Our cross system integration and end to end process orchestration capabilities give them a scalable foundation. They need to migrate their existing automation program beyond task based automation into broader agentic workflows. Remaining performance obligations increased to $1.413 billion up 15%. Normalizing for the FX headwind which was approximately $9 million. RPO grew 16%. Current RPO increased to $908 million up 17%. Turning to expenses, we delivered first quarter overall gross margin of 83% and software gross margin was 90%. First quarter operating expenses were $256 million. For the first time in company history we delivered a gap profitable first quarter with GAAP operating income of $28 million up from the prior year GAAP operating loss of $16 million. GAAP operating income included $53 million of stock based compensation expenses. First quarter non GAAP operating income was $92 million representing a 22% margin, up over 200 and 50 basis points year over year and driven by our continued focus on operational efficiency. First quarter non GAAP adjusted free cash flow was $130 million. We ended the quarter with a healthy balance sheet of $1.4 billion in cash, cash equivalents and marketable securities and no debt. During the first quarter we repurchased 20 million shares at an average price of 11.47 $11.47. Since April 30th under our 10B51 plan, we have repurchased an additional 2 million shares at an average price of $9.63 through May 27th, 2026. Now turning to guidance, we are pleased with the team's execution of what continues to be a variable macroeconomic environment, we continue to maintain a prudent outlook and guide to what we see in front of us. Since we provided guidance on our last call, the euro has remained largely stable while other currencies such as INR and Romanian LEY have experienced volatility. As a result, for the second quarter and full year, we expect a nominal incremental FX headwind to ARR and revenue. Despite the incremental FX headwind, we are raising guidance for the progress we've made on our operating priorities. Turning to the specifics of our guide for the second fiscal quarter 2027, we expect revenue in the range of $395 million to $400 million ARR in the range of $1.929 billion to $1.934 billion, non GAAP operating income of approximately $75 million and we expect second quarter basic share counterpart to be approximately 518 million shares. For the fiscal full year 2027, we expect revenue in the range of $1.776 billion to $1.781 billion ARR in the range of $2.058 billion to $2.063 billion non GAAP operating income of approximately$430 million and finally, we continue to expect fiscal year 2027 non GAAP adjusted free cash flow of approximately $425 million and non GAAP gross margin approximately 84%. Thank you for joining us today and we look forward to speaking to with many of you during the quarter. With that, I will now turn the call over to the operator. Operator please Poll for Questions we will
Operator
now move to our question and answer session. If you've joined via the webinar, please use the raise hand icon which can be found at the bottom of your webinar application. If you have dialed in by phone, please press star 5 to raise your hand. When you are called upon, please unmute your line and ask your question. Please note that participants will be limited to one question and one follow up. We will now pause briefly to assemble the queue. Our first question will come from Brian Burgin with TD Cowan. Your line is open. Please ask your question.
Brian Burgin (Equity Analyst)
Hey guys, good afternoon. Thank you. Maybe just to start on the overall demand environment, any interesting changes in the underlying demand trends and pipeline conversion? Anything as it relates to deal timing, sales cycles, things like that? Just as this conflict has been extended? No, we we actually feel like the environment has stayed relatively stable versus what we saw in the first quarter. Sorry, when we when we got into the first quarter earlier this year, Brian, I think we actually feel very positive about the momentum in the business. The health of our pipeline and the conversion rates and the predictability. The customer conversations are going really well. A lot of the pilots are beginning to now starting to convert, which we feel really positive about. So overall, we're actually very positive overall on our pipeline and the environment remains variable, has been, it feels like a new normal is the way we kind of think about it. Okay. And then on ARR, AI product, ARR levels, any, any sizing you can update us there and how the pricing conversation across those solutions is evolving.
Ashim Gupta
Yeah, you know, we'll disclose the product IR periodically here. We feel really good about the momentum. I think we pointed to it in terms of 16 of the top 20 deals for the quarter you know, involved AI. I think Agentic and our AI products in general just have, have really good, strong momentum. And our vertical solutions are also starting to really, you know, get traction both from customer interest and pipeline, particularly in health care and financial services. And then lastly I think test, which you know, is, you know, our gentic testing solutions, you know, that has, has really good traction as well. We look forward to update the numbers here and in the coming periods. But right now we feel really good momentum and I think, you know, the deal traction kind of speaks to the overall trajectory for the AI products.
Operator
Your next question will come from Scott Berg with Needham. Your line is open. Please go ahead.
Daniel Dynes (Founder and Chief Executive Officer)
Hi everyone. Nice quarter. Thanks for taking my questions. Daniel, you spoke extensively about orchestration and it's a key topic that comes up in our work on the space consistently over the last probably year or two. When you think about Maestro and the deals that you have out there, is there any reason why Maestro isn't a part of basically every deal that has AI or is there some combination that would suggest that that's not going to be a part of every deal going forward? I don't think Maestro can be part of every deal. The way we, the way we are looking at our business, it's. We have a entire platform that can address the whole spectrum of task and process orchestration. Maestro is a solution that comes into play when customers are doing process orchestration and automation and end to end process orchestration and automation. But we have customers out there that are happy to start with the task automation product. And task automation can also be deterministic and cognitive. I would say that RPA and API automation plays into deterministic task automation while we have agents that can be applied to task level. Maestro comes into place when you need more complex orchestration of work that involves humans, task automations, enterprise workflows, systems and agents. So it's, it's naturally more for our more, you know, evolve customers. Maestro helps us landing bigger deals, makes our install base stickier to the customers. But I cannot say it can be deployed in every single deal.
Scott Berg (Equity Analyst)
Got it. Helpful. And then Ashim, a follow up to the last questions that were out there. I think what we're all trying to understand is the impact of obviously some of your AI modules on the business and the bookings and what the general trajectory is. I understand that you don't want to necessarily report that AI metric every quarter, but if I ask a question a slightly different way is if I think about those 16 deals in the top 20 that had an AI component of them, how significant of those transactions is coming from some of the AI functionality. I think we're all trying to understand is it still, you know, traditional RPA heavy in those transactions or if we're seeing a bigger impact from some of the AI function?
Ashim Gupta
No, we're seeing a bigger impact. You know, I think for the way I look at it is I kind of, I would divide it into three areas like our top customers and our top deals. The majority of our transactions have, have a significant AI, if not a majority AI component. Scott, that's driving it. They're not piecemeal where it's kind of like one or two SKUs that get moved in or small quantities. They are materially what we are selling right to our customers. I think there is a mid tier of customers where you see actually a continued demand in traditional RPA and deterministic automation. And those are companies that either have embraced agentic and AI in a major way and they are actually pulling forward more deterministic automations, you know, as they weigh both the cost and the trust and governance that, you know, agents versus deterministic automations give you. And then really the kind of some of the, the drag that we talked about is really from the low end of the market, you know, smaller customers and personal productivity. That's kind of the way I would divide up the quarter. So we are actually really pleased with the pull that we're getting on the agentix side and its contribution to our growth.
Operator
Your next question will come from Sanjay Singh with Morgan Stanley. Your line is open. Please go ahead. Sanjit Singh with Morgan Stanley. Please go ahead.
Abhishek Murlian
This is Abhishek Murlian for Sanjit Singh. Thanks for taking the question. We'd love to hear a little more on the beat and kind of dig into given Q1 revenue. Upside was strong, but then the beat was largely driven by license revenue and then ARR was relatively in line. So can you kind of help us understand the quality of that revenue beat? Was there anything unusual in license timing or customer behavior that we should be aware of? And then how should we think about the relationship between license performance and AR trajectory for the rest of the year?
Ashim Gupta
Yeah, I mean I would say two things. One is we feel really good about the quality of that revenue both in terms of the products as well as the deal quality and structures. I would say it's, you know, our quarters have been very clean and we feel very good about the overall deal quality and construction. You know, remember the revenue is a quarterly performance metric when you're looking at the growth rates and we are on ASC 606 versus ARR, which is a 12 month metric. Right. So if I break down the question, know you look at revenue growth at 17%. When you look at a trailing twelve month period, the revenue growth rate is 15%. So actually which makes me feel very good about 15% growth on a trailing twelve month basis. And it, you know, it's, it's relatively in line with the ARR growth at 12% in terms of IAR beat versus revenue beat. It's really just the mix of deals with 606 timing and you know, the license revenue being, you know, a factor in that is a sign actually of really good quality revenue overall. Thank you. And then as a follow up, anything you can share in terms of the mix between consumption based revenue and per seat, we don't, you know, consumption based revenue is a very small part of what we do. We still have subscription really dominates our pricing model and per se pricing as well. You know, that is not the majority of what we do. We are really selling executions as well as kind of our typical server based pricing that we have for unattended robots in particular. I just really emphasize again, personal productivity is, you know, a very small part of our portfolio. Simple task based automation. So what we sell is the larger complex use cases now. And that really makes us higher towards both server based and subscription based pricing.
Sonica Merchant
Your next question will come from Sanika Merchant with rbc. Your line is open. Please ask your question. Hey guys, this is Sonica Merchant on for Matt Hedberg from rbc. Thank you so much for taking the question. Could you talk a little bit about the broader competitive environment for orchestration and any changes or trends you're seeing. And there have also been a Lot of developments around frontier model capabilities. Could you talk through how you see these developments impacting the broader competitive landscape and the company specifically? Thanks.
Daniel Dynes (Founder and Chief Executive Officer)
Yeah, sure. I would like to start by saying that we have a really unique platform in the market and it's based on three major pillars. We have a very modern process orchestration technology that is built on a very innovative workflow engine capabilities. We have a proven of 10 years deployment of scales of automations in a secure and governed environments with some of the largest companies in the world. And we have a unique ability to connect to both modern API based systems and legacy systems. These three pillars make our platform quite unique in the market and in terms of, you know, the new developments that we are seeing, I think we all recognize the huge impact of the coding agents of the entire ecosystem. And I want to point you to an interesting phenomenon that's something that we spot with our customers and within our own UiPath operations. It's becoming increasingly easier to build deterministic automations. You are using coding agents to build deterministic automations and deploy them at scale. It's becoming really easier to address the long tail of opportunities of work and it was not economically feasible before coding agents to get to this level of automations and building automations. It's really creating the substrate for deploy, for deploying a gentic AI. Later on I would, I would point to why coding agents are so successful nowadays because they really combine models, the strengths of the models with the strength of deterministic automations. Cloud code. It's so good because there is this deterministic harness around it. So Claude generates code, but then it uses a compiler which is a deterministic piece of technology to compile the code and then it's using testing which, which are another deterministic piece of code to validate the code that is generated. So I think it's becoming more clear to everyone that the combination of deterministic automations and models are what makes, you know, the real deployments in production. And I would say that in this regard we do have tremendous advantage. Our platform is already enabled for coding agents and we showed that our DEFCON in India we showed that we can reduce significantly the implementation times, think for a second, weeks to hours. That really means a lot when you go and deploy automations to the long tail of possible work.
Sonica Merchant
Thanks guys, appreciate the color there. And as a quick follow up. So you've talked a lot about sort of profitability and last quarter you also updated your long term non GAAP operating margin target to 30% and keeping in mind the fact that growth remains a priority for the company, what are some keys to margin expansion in fiscal year 27 and is there any seasonality you would point out on that? Thanks.
Ashim Gupta
Look, I think on, on from a cost seasonality, nothing except for, you know, obviously the, our later parts of the year we have sales compensation, you know, which is just normal SaaS seasonality from an expense standpoint, otherwise I think we're pretty, you know, there's no real seasonality to mention. From my standpoint, I think, you know, we're looking as growth as our first priority. So we are investing in FTEs, we are investing in test, we are investing in vertical solutions, we are investing in coding agents as evidenced by the speed of the launch by which we're moving through things. And so from our standpoint, you know, that investment is our first priority. At the same time we updated our long term models because we are able to find increasing levels of efficiency both through continued discipline and scrutiny and then also from implementing both our platform as well as broader AI tools within the company. And so, you know, we're, I would say we're invest first mindset and a waste nothing mindset. And that combination I think gives us the ability to both grow and drive the strategic initiatives while expanding operating margins.
Operator
Your next question will come from Pat McIlwee with William Blair. Your line is open. Please go ahead.
Pat McIlwee (Equity Analyst)
Hi Daniel and Ashim, thanks for taking my questions. My first question, I thought the AI summit you put on earlier this year was very helpful in envisioning how customers can evolve from your traditional RPA workflows towards more agentic enabled workflows and specifically how they can choose their own autonomy level and then kind of use a feedback loop to evolve the level of automation in that process over time. So I know it's early on, but for your existing customers, where are they in that autonomy evolution right now? Are a lot of them content with the value they're getting from current RPA workflows and leveraging AI within newer workflows, or are they really racing towards these agentic solutions to maximize the ROI they're getting from the platform, both existing and new workflows alike?
Daniel Dynes (Founder and Chief Executive Officer)
Yeah, I would like to point out that despite the technology being very new, it is, it is hailed by our customers with a lot of enthusiasm. Even when we were in like closed preview, we, we got a lot of requirements from the customers. They, some of the customers even went to find online some of the skills that we publish and use them with the coding agents. And also I Would like to point out to the fact that basically coding agents solve two of the biggest hurdles in deployment of automations. Number one was always the implementation leading time to when until an enterprise would get value from automation. So that's been already proven internally by our own forward deployed engineers and externally by a few advanced customers that can be shrinked in many cases from weeks to hours, which is very, which is very significant. The second way that coding agents unlocks a bottleneck of automation is in maintenance. One of the apparent flaws of automations was always the fact that they are fragile and that and they break. If there is an upstream modification in an enterprise system that automations are not aware they might break. And that will require human intervention and many days of reviewing and understanding. Now we offer both a healing agent and the diagnosed agent. So the healing agent can do a lot of the work during runtime, during execution and in many cases the healing agent can fix the execution in itself and the processes run unaffected when there is an exception. We help tremendously developers with this diagnose agents to gather all the context around an automation and they can publish a fix in much faster than before. So yes, I would conclude that for us this is a really big unlock and we, we, we see the potential for a huge acceleration of customer adoption.
Pat McIlwee (Equity Analyst)
Right, okay, thanks Daniel for the thoughts there and to kind of continue on. It sounds like AI agents are largely extending, not replacing deterministic automation within your platform. But as we think about that, I wanted to ask, is there any sort of dynamic where you're seeing customers leverage agentic AI to somewhat cannibalize some of the traditional bot monetization? Or is it largely building incremental automation and you know, therefore incremental monetization on top of those workflows?
Daniel Dynes (Founder and Chief Executive Officer)
Yeah, I would like to say that perhaps this is one of the biggest confusion that AI brings into the table. The idea that non deterministic probabilistic technology can replace deterministic automations. This is not true. It's not true from the capability perspective and it's not true from an economical standpoint. And let me elaborate a bit on both. A probabilistic technology is not architecturally meant to follow a dozen of steps and sometimes hundreds of steps in the same order in the same sequence. Every step will have a probability. When you multiply these probabilities you will end up with something that is not reliable end of the day. And there are many regulated industries that cannot tolerate anything that is not 100% reliable. They will prefer an automation to fail as an exception rather than produce an unexpected result. So what determine deterministic bots cannot be replaced by non deterministic AI agents. Again, this is the architecture that is proven over and over again by all the AI agents that are out there. The most sophisticated agents like Cloud Code or OpenAI Codex are built on the foundation of deterministic tools that they call. So it's a hardness around the model and deterministic tools. This is, this is exactly how they work. This is exactly what we are proposing to our customers. Guys, reuse your investment in your existing deterministic automation and surround it with process orchestration, which is also deterministic that can orchestrate models agents in the context of determinism. That's really the only way to deploy it effectively into an enterprise context. And now to the second point about the economical aspect. Even if in certain cases an agent can replicate some steps that are deterministic, why would you do something that is costly and is going to consume tokens at every step in a process rather than generate a script that works and it costs nothing in order to run? So to my previous answer, this is the best combination between AI and deterministic. AI creates automation, sometimes maybe even on the flight AI will run those automations. It's very cheap to run, very deterministic, reliable, auditable, and only when these scripts break, you can invoke again AI to fix the scripts. But that's basically the right model to run agentic AI and automation into enterprise context.
Operator
Your next question will come from Raymau Lenshaw with Barclays. Your line is open, Please go ahead.
Raymau Lenshaw
Perfect, thank you. Thanks for squeezing in. Daniel, stay on that subject because that's obviously where a lot of the investor questions are coming around. So how does the world work then going forward? If you do the deterministic part and you have all the experience in the world, so you should do that. Who is doing then the probabilistic part? What are you seeing there in terms of work, customers thinking and how they think about you in that context? And then I had one follow up. Rashid.
Daniel Dynes (Founder and Chief Executive Officer)
Well, I think the answer varies in we are model agnostic in terms of how we see the world. So we provide deterministic orchestration and we can infuse that deterministic auto orchestration at any steps with Agent Ki that Agent Ki use behind the scene. You know, Frontier Lab models can use open weights models. We have a bring your own model policy. So we will accommodate every spectrum of requirements from our customers. But again, I think it's important to note that even on the Frontier Lab models the offering, it's a combination between deterministic and the model itself which is purely cognitive. We extend in a way that model into the enterprise work itself. And when you go and I think very important distinction to understand the enterprise work is to think of who initiates an agent where process automation, it's a big difference if it's initiated by a person and the agent work on a person desktop versus an automation is triggered by an event or by an enterprise workforce where you will need to have different degree of audit ability and reliability. And again this is where we really shine. We have this 10 years of experience in running a large scale unattended automations that work, you know, on event triggers and we are involving agent Ki and models into these workflows that can run unattended.
Raymau Lenshaw
Yeah, okay, makes sense. That's very clear. Thank you Daniel. And then cmd, the one other question I get from investors a lot at the moment is you're, you're doing really well on the revenue side. ARR is very steady but at some point they kind of need to kind of start lining up. So revenue at the moment keeps growing faster than than ARR. How do we need to think about that dynamic? Because in theory you would think that they should line up. I would think, yeah.
Ashim Gupta
I think remnant. The first piece is I again like when you look at it On a trailing twelve month basis the revenue growth rate is 15 versus the ARR growth rate of you know, 12% that you see. The second piece is within the revenue growth rate. There's obviously the license revenue growth rate and then there's you know, services and etc. You can see we actually had good services revenue as FTEs etc are in demand from our customers. So that's you know, that's a second piece that is there over time this has moved in different directions. There's been times where with 606 revenue has trailed as you know certain duration and mix has moved the growth rate and where it succeeded. But when you look at it on like an overall average over a longer period of time it's together I don't really see any major disconnect at this moment that is, you know, that is driven by a business specific area. It's really just a mix of 606 impacts on the on the business. And again I would emphasize to look at on a trailing twelve month basis versus you know, looking at it where it is just in a particular quarter because ARR is obviously an annual metric.
Operator
Your next question will come from Michael Turin with Wells Fargo, your line is open. Please go ahead.
Ashim Gupta
Hey, great. Thanks very much. Appreciate you taking the questions. I'll just ask two up up front and you can take them on whatever sequence you like. I guess the first is just in terms of public sector as we roll into mid year. Maybe just remind us how you're thinking about public sector this year. Any updates in terms of progress or deal progression from that vertical specifically and then maybe ashram, just on the net retention rate, just what you're seeing currently and the uptick there and how to think about the trend line obviously without guidance. But just thinking through the drivers there. Thanks very much. Yeah, let me answer the. I can answer both questions. I'll start with the net dollar retention rate. I'm actually super excited with the net dollar retention rate and the progress we've made on it. As you can see it's you know, have a two point increase, quarter over quarter. That's one of the first times we've had an increase as we've stabilized net new and beginning to point the trajectory up towards that re acceleration mark 1. You know, when you normalize for foreign exchange and the impact of M and A, that is you know, one point. But it's still a re acceleration of net dollar retention rate that you know we're, we're actually very encouraged by. And as I said as we start to stabilize net new arrival, the next step is re acceleration. So we're, we're moving into that territory and I think that's really great progress by the teams and speaks to the strategy and the operational execution that we, that you see in terms of public sector. I actually was at the public sector fusion event that we had. The energy was very strong. I think public sector in terms of disruption of budgets, et cetera. You know, we feel pretty, we feel like there is good stability obviously as funding moves with you know, different defense initiatives and wars etc. That are there, we stay on top of it. But within many agencies we actually have a very good presence, strong relationships with really good use cases, whether that is audit compliance within, you know, within the government, which we have a very strong set of solutions and partners that we're working with or other transactional areas. We actually feel like our relationships are very good in terms of what's in for. You know, as we talk about guidance, we continue to guide what's in front of us there, which is, you know, we're pretty measured and prudent. We know what projects are generally funded and you know, we're looking to execute against that.
Operator
Your Next question will come from Radi Sultan with ubs. Your line is open. Please go ahead.
Radi Sultan (Equity Analyst)
Awesome. Yeah, thanks for taking the question first for Daniel. Just on the UiPath for coding agents, you mentioned this would be targeted at the full software development life cycle, but I guess are there like one or two areas where you see the biggest pain points, where you think you can add the most value. And then you also mentioned this could strengthen retention. Maybe just how you imagine monetizing or bundling these agents into the broader suite.
Daniel Dynes (Founder and Chief Executive Officer)
So we plan to bring agents across, across the entire development life cycle. We are starting with an agent that helps with planning for an automation. So you, you can have a business analyst that can, with the help of the agent, interview different subject matter experts, gather all the information, create a process documentation document and then we will have like solution architect agent that will take this design document and convert it into code. And we'll have different agents for different types of code. We'll have an agent that can create enterprise user interface. We'll have an agent that will create rpa, another agent that can create API workforce, an agent that will create process orchestration based on Maestro. This can be deployed and tested again. It's fully agentic. Once they are in production, we have agents that monitor the entire execution and can fix proactively the errors that are coming and wondering once there is an exception. We have also agents that help our developers to diagnose faster the exception and fix them faster. So the entire life cycle, there is no single point in the life cycle that is not touched by agents. In fact, we believe that the entire authoring surface of our platform is basically agentic. First, humans, we think are mostly going to do validation. They will inject goals to the agents and they will do the validation and supervision of the work. But most of the work itself is going to be created by agents.
Radi Sultan (Equity Analyst)
Got it, got it. Maybe just one follow up for Ashim. Last quarter we talked about core RPA still growing and becoming increasingly strategic to the AI product offerings. If you just talk through how you think about how pricing should evolve for the RPA deterministic automation side of the business, given that it is becoming increasingly more strategic to customer AI initiatives to capture that incremental value.
Ashim Gupta
Yeah, look, I think that there's a lot of discussions around outcome based pricing that are real and active more than they ever have been before. So I think like that is one tier of pricing to our top, you know, to our top customers that I think is, it's a, it's a real evolution. We see real line of path. And we see people, especially with their fears of, you know, about getting, getting ROI with, with AI, really looking for that. The second piece, the second piece I would say is I think where we're looking through is we also see like use case or process based pricing, where people are looking for restricted use cases so they can solve problems and have be able to use different parts of the platform that enable them to do so. Those are two evolutions that are there in terms of where we are with the deterministic side and overall.
Operator
This now concludes the Q and A session. I'd like to turn the call back over to management for closing remarks.
Daniel Dynes (Founder and Chief Executive Officer)
Thank you so much for the questions. And as usual, we would like to speak directly with many of you over the next few days. Thank you so much.
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