Appian Corporation

Good day and thank you for standing by. Welcome to the Appian First Quarter 2026 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 11 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 11 again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Brian Denue from ICR. Please go ahead.

Thank you. Good morning, and thank you for joining us. Today we'll review Appian's first quarter 2026 financial results. With me are Matt Calkins, Chairman and Chief Executive Officer, and Serge Tonga, Chief Financial Officer. After prepared remarks, we'll open the call for questions. During this call, we may make statements related to our business that are considered forward-looking. These include comments related to our financial results, trends, and guidance for the second quarter and full year 2026, the benefits of our platform, industry, and market trends, our go-to-market and growth strategy, our market opportunity and ability to expand our leadership position, our ability to maintain and upsell existing customers, and our ability to acquire new customers. These statements reflect our views only as of today and don't represent our views as of any subsequent date. We won't update these statements as a result of new information unless required by law. Actual results might differ materially from expectations due to the risks and uncertainties described in our SEC filings. Additionally, non-GAAP financial measures will be discussed in this conference call. Reconciliations of GAAP to non-GAAP financial measures are provided in the earnings release. With that, I'd like to turn the call over to our CEO, Matt Calkins. Matt?

Thanks, Brian, and thanks, everyone, for joining us today. In the first quarter of 2026, Appian's cloud subscriptions revenue grew 25% year-over-year to $124.5 million. Subscriptions revenue grew 19% to $160.3 million. Total revenue grew 21% to $202.2 million. Adjusted EBITDA was $26.6 million. Our weighted rule of 40 scored 42, the highest level since we introduced the metric last year. Our go-to-market efficiency metric posted its 11th straight quarter of improvement. Appian continues to build on our success in 2025. We met or exceeded financial expectations in Q1 and raised full-year guidance. Serge will share the details. Last week, Appian announced the results of a study done with the Harvard Business Review on the state of AI in the workplace. It captures this unique moment in which every organization intends to use AI, but many struggle to get value from it, especially in the most important use cases. HBR found that AI is used more for personal efficiency than it is for strategic applications. If an application is customer facing or makes business decisions, it's probably not benefiting from AI. Appian's purpose is to bring AI into mission critical applications at large regulated companies where errors are not acceptable. We make AI reliable enough for such use cases by wrapping it in a deterministic framework of process technology. AI is a probabilistic technology, unreliable by nature, while the most valuable use cases require complete dependability. HBR's study shows how corporate users know what's needed to make their AI reliable. 92% know they need guardrails for AI. though most have not created them. Most intend to integrate AI into process, though only 18% have done it. Organizations now understand how to equip AI for serious use cases, even if they haven't done it yet. HBR's conclusion states, and I quote, the next phase of AI maturity will depend on embedding AI directly into the core of how work gets done. Appian has been embedding AI into the core of how work gets done for years. with our leading process automation technology. My conversations with customers indicate that we've helped them move faster than the market as a whole. Nearly 40% of Appian customers have purchased our AI-inclusive license tiers. Driven by AI demand, our 2026 pipeline is above our expectations and a key factor in our increased guidance for the remainder of the year. Excitement over Appian AI was evident at our annual user conference, Appian World, which took place last week in Orlando. Our theme was serious AI, meaning AI used for strategic and valuable work. Our point, of course, was that serious AI requires process. Over 1,000 customers, prospects, partners heard from Appian experts and peer organizations, including Citi, Pfizer, Merck, GE Aerospace, GE Healthcare, NASA, AARP, Regeneron, Munich Re, CIBC Mellon. Customers reported that AI transformations are increasingly a board-level priority. AI alone operates at a low level of reliability. But with Appian's framework, AI can work and write applications at a high level of reliability. We've created technology that complements AI, enabling it to be used in the most valuable situations. Appian DocCenter is a great example of deploying AI within process. DocCenter automatically extracts data from incoming documents, then takes action accordingly. DocCenter runs at scale with over 95% accuracy, significantly higher than the 60% accuracy of traditional document recognition technology. Our customers processed more document pages in Q1 this year than they did in all 2025 combined. Production use cases span all major industries. I'll share a few customer examples. First, an international insurance company is automating processes and working to eliminate $100 million in operational costs by 2030. It named Appian its AI document intake standard after DocCenter processed complex unstructured physician statements with 98% accuracy. Next, a global medical devices company manages its order to installation processes on Appian. This quarter, it deployed DocCenter to automatically compare order packages against client documentation. It can now process items 80% faster. Once rolled out globally, Appian will validate 100,000 orders annually and save the firm an expected $16 million in operational costs over the next three years. Finally, a top oil and gas company has been an Appian customer for several years. It uses our platform to onboard customers and suppliers 70% faster than before. This quarter, its finance department chose Appian to spearhead its AI transformation and purchase a seven-figure software deal. Appian will automate the procure-to-pay process, starting with invoice payments. DocCenter will extract data from millions of supplier invoices annually and automatically reconcile them against the company's order management system. Appian will provide significant labor savings and help the company achieve its goal to reduce operating costs by $400 million by the end of 2027. Legacy modernization is a fast-growing component of our business and perhaps the most popular topic at our conference last week. C-level executives respond immediately to the promise that we can migrate their legacy apps to our modern platform. According to McKinsey, 70% of Fortune 500 software is over 20 years old. We've been doing modernization migrations for a decade with good results. The U.S. Air Force saved $80 million after modernizing its tech stack with Appian, and Hitachi consolidated over 500 systems into a single central Appian application. Legacy modernization may be an idea whose time has come. New AI technology has expanded the opportunity by lowering the cost and increasing urgency. The cost is lower because natural language development is now a mainstream way to compose applications in Appian. The urgency is higher because products like Anthropix Mythos threaten to expose security weaknesses in all applications, especially old code stacks without modern support. Many applications cannot be vibe-coded, written by AI alone. As I often say, code may be cheap, but mistakes are still expensive. Important applications will require a greater degree of reliability and precision, which Appian provides. We make AI enterprise-grade reliable in writing apps, just like we make it reliable in doing work. For example, a major European automotive manufacturer manages supply chain operations, finance, and warranty claims on our platform In Q1, it named Appian as its core modernization platform and purchased a seven-figure deal for more software licenses. The company's sprawling tech stack includes over 3,000 outdated and incomplete applications. Now Appian will unify the enterprise as the organization decommissions legacy systems. The manufacturer aims to reduce its application landscape by about 40% as it builds enhanced workflows on Appian. Customers have strong interest in Appian's agentic AI. Like all types of Appian AI, our agents are informed by our data fabric and deployed within the guardrails of our process. For example, a leading telecommunications company is using Appian to unify its digital advertisement operations. This quarter, it decided to automate compliance reviews and purchased more Appian licenses. Every network and streaming provider has unique rules about when and what type of content can be positioned on their channels. Before Appian, the company validated content manually. Now, Appian Data Fabric will unify client policies so our AI agents can reference a holistic data set. Our agents will verify thousands of ads every day and flag outliers that need human review. Early results suggest Appian agents will achieve 98% accuracy and require 33% fewer resources. The AI economy asks for transparency and openness. Appian is a longstanding believer in these values as shown in our Data Fabric that unifies distributed data sources without moving them. We've embraced what I call the three rules of the AI ecosystem, be useful, be open, and be safe. Our technology utilizes MCP inbound and outbound. Data Fabric is an ideal data source for AI agents because it is comprehensive, open, performant, and secure. You can now deploy, develop, you can now develop Appian applications without ever opening an Appian interface entirely from an AI command line in a product like Claude or Kiro. Our AI enabling layer is also AI agnostic, preventing AI lock-in, and empowering our clients to switch AI platforms in the background without losing any of their capabilities. Appian is off to a strong start in 2026. Our position as an essential enabler of AI continues to drive business momentum as customers gain real-world value from our platform. With that, I'll hand the call to Serge.