UiPath (PATH.US) 2026财年第三季度业绩电话会

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会议摘要

Uipath reported its first GAAP profitable quarter with strong financial growth, focusing on agentic automation, strategic partnerships, and market expansion. The company highlighted advancements in AI solutions, expanded cloud presence, and vertical solutions for accelerated ROI, aiming for continued growth with fourth-quarter guidance.

会议速览

UiPath's Q3 Earnings Call: Financial Results and Forward-Looking Statements

The host, Elise Forlani, introduces UiPath's Q3 fiscal year earnings call, emphasizing non-GAAP metrics and forward-looking statements regarding financial guidance and growth strategies. The call includes a discussion on potential risks and uncertainties affecting actual results, with materials available on the investor relations website. Participants are reminded that the call is being recorded and are encouraged to seek operator assistance if needed.

UiPath's Automation Strategy Drives Growth and Customer Success

UiPath's focus on automation combining deterministic and agentic intelligence leads to improved execution and customer engagement. With strategic partnerships and advancements in technology, the company achieved a 16% revenue increase and demonstrated significant ROI for clients through scalable automation solutions.

Uipath's Unified Platform and Innovation Drive Industry Leadership in Automation and AI

Uipath's unified platform and innovation have led to third-party recognitions in intelligent document processing, AI-augmented software testing, and intelligent process automation. The company's expansion into new markets, partnerships with global technology leaders, and focus on vertical solutions are driving faster value for customers and expanding the reach of its platform. Uipath's Maestro orchestration engine, API workflows, and collaborations with Microsoft, OpenAI, and Google are enhancing the platform's capabilities and delivering measurable results for customers. The company's focus on federal sector performance and end-to-end platform architecture is positioning it for continued success in the public sector and beyond.

Q3 Financials and Operational Progress Highlighting GAAP Profitability and Strategic Execution

A quarterly update emphasizing improved sales team performance, customer alignment, and operational rigor, leading to GAAP profitability for the first time. Highlights include a successful cybersecurity company case study, enterprise logo signings, and guidance for Q4 with revenue and ARR expectations, alongside non-GAAP operating income and adjusted free cash flow projections.

AI Solutions Traction, Federal Business Resilience, and Net New ARR Growth Drivers

The dialogue discusses the traction of AI solutions, with a focus on agentic offerings driving platform adoption and customer engagement. It also addresses the resilience of federal business despite a government shutdown and outlines drivers for the anticipated return to growth in net new ARR, emphasizing improved execution, new product launches, and leadership consistency.

Exploring Partnerships, OpenAI Integration, and Federal Business Dynamics

Discussion highlights the company's federal business performance, OpenAI collaboration for AI advancements, and strategic partnerships with tech giants, focusing on technology enabling alliances driven by customer needs.

Shift Towards Third-Party Agents and Enhanced Channel Partnerships in Automation

Discussion highlights the growing interest in third-party agency involvement, particularly in code agent development, alongside strengthened partnerships with firms like Deloitte, enhancing AI product deployments and pipeline quality.

Strategic Opex Investment for AI Product Rollout and Monetization

Discussed strategic Opex management, emphasizing disciplined investment in key areas like engineering and sales, while driving efficiency elsewhere. This approach supports AI product rollout and broader monetization goals, enhancing operational leverage and execution focus.

Key Drivers for AI-Driven Sales Growth and Q4 Guidance Insights

The dialogue explores the factors contributing to successful AI sales, emphasizing broad customer engagement and execution improvements. It also clarifies Q4 guidance, attributing growth to enhanced execution, macroeconomic conditions, and organizational stability, excluding deal slippage or AI functionality as primary drivers.

Analysis of NRR Downturn and New Business Growth in Q&A Session

A discussion unfolds on the causes of a decrease in Net Revenue Retention (NRR), highlighting pressures at the lower segment and potential for recovery. The dialogue also explores the impact of increased customer engagement and agent development on sustaining NRR and mitigating weaknesses.

Shifts in Model Provider Competition and Integration Strategies

Discusses the evolving landscape of model provider competition, emphasizing the value of integration and orchestration. Highlights the use of diverse AI models for specific tasks and the importance of co-innovation with partners for future success, noting a focus on ROI and customer collaboration.

Verticalized Approach to Pre-Built Agentic Solutions in Healthcare and Financial Services

The company is accelerating its verticalized strategy, focusing on healthcare and financial services. It highlights strong interest in revenue cycle management in healthcare and financial crimes, including know your customer and anti-money laundering, in financial services. Recent restructuring of product and engineering teams supports the creation of industry-specific solutions.

Complementary Roles of Deterministic and LLM-Based Automation in Business Processes

Speakers discuss how deterministic automation and LLM-based automation serve different purposes in business workflows, with the former being ideal for well-defined tasks and the latter for complex, unstructured processes. They emphasize the importance of orchestration technology that integrates AI, deterministic systems, and human oversight to ensure secure and reliable enterprise solutions. Industry recognition of orchestration's critical role is highlighted.

Navigating AI Pricing Challenges: Insights on Predictability and Customer Adoption

Discussion revolves around addressing customer concerns over spend predictability with agentic consumption pricing, emphasizing ongoing evaluation of AI adoption trends and flexibility in pricing models to better align with customer needs and consumption patterns.

Accelerating Time to Value: Building Pre-Solutions for Rapid Deployment and Industry Replication

The discussion focuses on leveraging pre-solutions to expedite the deployment of agent-based PLC systems, aiming to reduce cycle times significantly. Emphasis is placed on developing solutions that can be replicated across various industries, accelerating the trend of rapid deployment and value realization.

Concluding Remarks and Holiday Wishes from Management

The dialogue concludes with management thanking participants for their questions, wishing them happy holidays, and expressing appreciation for their input, before officially ending the call.

要点回答

Q：How is Uipath's automation strategy performing?

A：Uipath's automation strategy, which combines deterministic automation with AI-driven adaptability, is performing well. The strategy aligns with customer needs for trusted enterprise-grade automation that delivers tangible ROI quickly. This quarter's results reinforced the value of the platform and improvements in execution.

Q：What are some examples of how Uipath's customers are achieving significant savings and improvements?

A：Uipath's customers are achieving significant savings and improvements through various initiatives. One investment management firm is using Uipath's platform to integrate systems and orchestrate workflows, leading to over $200 million in projected savings. Another company, Core Well Health, plans to use Uipath's intelligent extraction and processing to automate the processing of referral information into Epic, saving over $10 million in labor costs this year and expecting $15 million next year. Uipath is also helping NRG Energy address testing challenges with its Test Cloud, anticipating cost savings and improved testing coverage.

Q：What new capabilities were announced at Fusion?

A：At Fusion, Uipath announced new capabilities including Uipath CleanPlay, which combines traditional RPA with AI to automate complex UI tasks. The company also introduced enhanced features for the intelligent automation of documents, such as intelligent extraction and processing to handle complex non-deterministic scenarios, and Uipath Test Cloud for AI augmented software testing.

Q：What recognition has Uipath received from third-party assessors?

A：Uipath has received third-party recognition for its capabilities. It was named a leader in the inaugural Gartner Magic Quadrant for Intelligent Document Processing, and for AI augmented software testing tools. Uipath was also recognized by Everest Group as a leader and star performer in the Intelligent Process Automation Platform. These recognitions validate Uipath's unified platform, innovation in AI integration, and the business impact it delivers to customers.

Q：What new features are being added to Maestri and what are their purposes?

A：New features being added to Maestri include case management and process apps. Case management helps customers model and manage their running processes, while process apps enable the construction of tailored end-user experiences with real-time visibility and actionable insights to drive proactive operational improvement.

Q：How is Uipath expanding its global cloud presence?

A：Uipath is expanding its global cloud presence by launching Automation Cloud in the UAE and continuing to expand its cloud footprint in important markets like Switzerland.

Q：What are the benefits of Uipath's industry-specific solutions?

A：Uipath's industry-specific solutions, such as the combined pricing and inventory optimization technology with Maestri, help customers accelerate return on investment (ROI) and expand the reach of their platform across key verticals like merchandising, pricing, and inventory management.

Q：What recent collaborations and integrations have been announced by Uipath?

A：Recent collaborations and integrations by Uipath include expanded integrations with Microsoft, a ChatGPT connector with OpenAI, a new conversational agent with Google Gemini models, integration with Nvidia for enhanced workflows, and a partnership with Snowflake to combine AI automation with their AI Cortex solution.

Q：What is the impact of Uipath's unified platform on the federal sector?

A：Uipath's unified platform is positively impacting the federal sector, especially with efficiency mandates creating a long-term tailwind for automation. This includes expanding with the US Coast Guard, improving mission readiness through automation for the Department of Veterans Affairs, and migrating the Social Security Administration to the cloud with IDP solutions for faster benefits processing.

Q：What recent performance highlights are mentioned in Uipath's quarter operational update?

A：Recent performance highlights mentioned in Uipath's quarter operational update include meaningful progress in execution across strategic priorities, improved sales team performance, strengthened customer relationships, accelerated innovation, and improved operational rigor. These efforts contributed to another solid quarter with top-line and bottom-line growth, including the first GAAP profitable third quarter and year-to-date performance.

Q：What specific figures are provided for the fourth fiscal quarter and全年?

A：For the fourth fiscal quarter, the company expects revenue in the range of $462 million to $467 million, with an approximate $5 million dollar headwind from FX rate movements. The ARR is expected to be in the range of $1.844 billion to $1.849 billion, also reflecting an approximate $5 million dollar headwind from FX rate movements. Non-GAAP operating income is expected to be approximately $124 million, with a basic share count of approximately 124 million shares. The company continues to expect fiscal year-end non-GAAP adjusted free cash flow of approximately $1 billion and non-GAAP gross margin of approximately 80%.

Q：What was the impact of the federal government shutdown on the company's business?

A：The company's business was not directly impacted by the federal government shutdown as many of their projects are funded through bills and are considered critical operations in essential areas like the Department of Defense.

Q：What factors contributed to the return to growth in net new ARR?

A：The factors contributing to the return to growth in net new ARR include consistent execution across the board, improved focus, and the launch of new products that are expected to increase platform pull-through, stickiness, and drive deeper customer conversations. The stabilizing business environment and the addition of consistent leadership and talent are also factors contributing to this growth.

Q：What type of pricing uplift or monetization is the company experiencing from AI solutions in Maher processes and production?

A：The company is experiencing pricing uplift from AI solutions, though not as a result of any specific pricing strategy but rather from the value these solutions bring to Maher processes and production.

Q：What is the role of AI in the company's platform and how is it driving value for customers?

A：AI is not implemented in isolation but is paired with the rest of the platform to drive value for customers. The company emphasizes the importance of an 'agentic' approach that integrates with their platform to deepen its value. The monetization strategy involves increasing pricing, conviction, and a focus on the architecture of customers' businesses. The company highlights the road map for AI and how customers are seeing tangible ROI through the breadth of the platform.

Q：How have the results in the federal business compared to expectations at the beginning of the year, especially regarding DoOM and the OpenAI collaboration?

A：The federal business has shown pockets of strength, with progress in RPA and the company is encouraged by this development. The company is executing well on the mentioned scripts and focusing on efficiency and strategic positioning. They continue to be prudent in their guidance estimation regarding the OpenAI collaboration. The use of GPT-5 across the platform, particularly in the innovative 'screenplay' product, is highlighted. The company believes they are unique in delivering autonomous UI tasks using LLMs.

Q：What is the nature of the partnerships announced and how do they contribute to the company's AI strategy?

A：The partnerships announced are technology-enabling and are driven by customer needs. The company emphasizes an open platform that is flexible and customizable. Partnerships with companies like Snowflake, OpenAI, Google, Nvidia, and others provide different layers of a solid foundation for delivering reliable AI in a secure manner. The goal is to create a partnership that offers a reliable foundation for AI delivery. The company is seeing a mix of agents, both low-code and code-based, hosted and managed by their platform.

Q：How is the partnership with Deloitte contributing to the company's pipeline and what is the quality of the pipeline?

A：The partnership with Deloitte has led to a higher quality pipeline rather than just an increase in quantity. The partnership has Deloitte's presence in many customer conversations, particularly around large-scale transformation processes. The company indicates that the discussions with Deloitte are indicative of a much higher quality of pipeline.

Q：What is the company's strategy for Opex investment next year and how will it support the AI product rollout and monetization?

A：The company is not providing specific details regarding next year's Opex investment but comments on the strategy employed by the leadership team. The strategy involves hiring in engineering segments, expanding sales capacity, being selective about investments in overlay functions, and continuing to drive efficiency across processes. The company is focusing on investments in key areas such as deployed engineers, core engineering capabilities, and customer sites. This focus on cost structures, efficiency, and prioritization is expected to continue contributing to operational leverage and enhanced execution cadence.

Q：What are the key drivers or levers that can be used in current deal cycles based on the experience with pilots and proof of concepts?

A：The company has observed patterns emerging from pilots and proof of concepts but it's too early to pinpoint specific use cases with great, replicable potential. However, improved execution across the sales team, broad-based customer activities, and the stability in the pipeline suggest these could be beneficial for current deal cycles.

Q：What are the main factors contributing to the year-over-year growth in net new ARR mentioned in the fourth quarter guidance?

A：The main factors contributing to the year-over-year growth in net new ARR include improved execution from the sales team, good customer activities such as successful pilots, and renewals indicating the company's long-term position in the architecture. Additionally, the macroeconomic environment and currency fluctuations have an impact, and there's also an element of momentum from the stabilization achieved six to nine months post-restructuring and normalization in sectors like the public sector.

Q：How does the company expect the current trends in net new ARR to influence future results?

A：The company believes that the stabilization of net new ARR is indicative of a broader stabilization of other metrics. As the company has provided guidance that shows a stabilization and improvement, this is seen as a positive sign for future results.

Q：What was the reason behind the downtick in NRR and how does the new business strength relate to this?

A：The downtick in NRR was mainly due to pressure at the lower end of the customer segment. However, as the net new ARR stabilizes, the rest of the metrics begin to stabilize as well, which is reflected in the third quarter results and the guidance provided.

Q：What is the expected impact of the increase in customers developing agents and instance processes on future NRR?

A：The company expects the momentum in customer activity, which includes both direct and indirect engagement, to continue to support their platform as a scalable, long-term solution within enterprise architecture. The impact on future NRR, however, is not quantified as there is nothing material to report at this stage.

Q：Has there been a shift in perception regarding competition among model providers and the value of integration and orchestration?

A：The company has not observed a shift in perception regarding competition among model providers but acknowledges the increasing value of integration and orchestration. They continue to assess various models and utilize the best-of-breed across their platform.

Q：To what extent did the early partnerships and co-development of solutions translate into proof of results in Q?

A：The company has prioritized partnering and co-developing solutions this year, and while it's not explicitly quantified, such efforts are seen as important indicators for future success and are expected to contribute positively to future results.

Q：What is the perceived impact of engaging with customers and solving problems?

A：Engaging with customers and solving problems is seen as a way to build a relationship and provide meaningful impact, especially in terms of Return on Investment (ROI). Co-innovation and teaming up with partners around bigger problems can lead to significant impacts on ROI, validating the framework and product.

Q：What is the relevance of the Gena to customers and its effect on their investment?

A：The Gena's role in customers' long-term roadmaps and architecture shows its relevance, leading customers to be more willing to invest in the platform, thus creating a higher level of impact within their organization.

Q：Which verticals are adopting pre-built agentic solutions the fastest and is there a shift towards industry-specific packaged automation?

A：Pre-built agentic solutions are gaining traction in the EYP sector and vertical solutions are being reworked to focus on industries like healthcare and financial services, particularly in revenue cycle management and financial crimes. There is an indication of moving more aggressively into industry-specific packaged automation.

Q：What is the balance between deterministic automation and AI-based (AGI) automation?

A：The speaker believes deterministic automation and AI-based (AGI) automation are complementary and address different steps in business processes. Deterministic automation is used where tasks and workflows are well-defined, while AGI is beneficial in complex areas without clear rules, involving complex processes or large document reviews. Orchestration, combining both with human-in-the-loop, is seen as essential for delivering secure and reliable solutions.

Q：What is being done to address the hurdle of spend predictability for customers?

A：The company is continuously evaluating customer adoption of AI and aims for a pricing model that aligns with the consumption of AI. They are flexible, adaptive, and work with outcome-based pricing, recognizing the need to improve spend predictability.

Q：What is the typical cycle time from an agentic PLC to a production deployment?

A：The cycle time from an agentic prototype to a production deployment is expected to be less than a year, and the company plans to accelerate this process by using solutions accelerators that replicate experiences across industries and verticals. The goal is to significantly reduce the time to value by focusing on pre-solution deployment.

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