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DATE

Thursday, May 28, 2026 at 4:30 p.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — Daniel Mark Rogers
• Chief Financial Officer — Aziz Megji
• Head of Investor Relations — Eva Leung

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TAKEAWAYS

• Revenue -- $205.1 million, up 9.5% year over year, above the top end of company guidance.
• Non-GAAP Operating Margin -- 11.5%, a 720-basis point improvement year over year, and 27 basis points higher than the prior year.
• Net Income -- $24.4 million, or $0.10 per diluted share.
• Gross Margin -- 88% for the quarter.
• Core Customers -- 26,100 spending $5,000 or more annually, accounting for 76% of revenue, with revenue from this cohort up 10% year over year.
• $100 Thousand+ Customers -- 817 customers in this category, cohort revenue up 12% year over year; this number was sequentially flat compared to last quarter.
• Net Revenue Retention Rate (NRR) -- Overall NRR 96% on a trailing-four-quarter basis; in-quarter NRR improved to 97%, up for the fourth straight quarter.
• International Revenue -- Grew 12% year over year, driven by performance in EMEA and APAC regions.
• AI Product Bookings -- Represented 17% of net-new annual recurring revenue (ARR), exceeding the full-year 15% target pace.
• AI Studio Customers Spending $100 Thousand+ -- Nearly doubled during the quarter, excluding other customer additions.
• Operating Cash, Equivalents, and Marketable Securities -- $424.6 million at quarter-end, before accounting for the Stack.ai acquisition.
• Remaining Performance Obligations (RPO) -- $518.1 million, up 23% year over year; current RPO up 9% year over year and equals 79% of total RPO.
• Deferred Revenue -- $320.1 million, up 11% year over year.
• Adjusted Free Cash Flow -- $34.4 million, or 17% of revenue, with elevated collections cited as a temporary factor.
• Stock Repurchases -- $45 million (7.4 million shares at an average price of $6.11); $155 million remains available for further repurchases as of April 30.
• Stack.ai Acquisition -- Acquired for $75 million upfront cash and additional equity earn-outs, adding 50 employees and accelerating the AI roadmap by over a year.
• Tech Vertical -- Returned to positive year-over-year revenue growth for the first time in 8 quarters due to customer expansion in both seats and AI add-ons.
• Product Traction -- Tasks involving AI teammates are now completed nearly 9 times faster; customers using AI Studio exhibit superior seat expansion and NRR.
• Q2 2027 Guidance -- Revenue of $213 million–$215 million (8.2%-9.2% year-over-year growth), non-GAAP operating margin of 8.5%-9.3%, net income per share of $0.08–$0.09, with Stack.ai expected to add 50 basis points to growth and a 1-point margin drag in the second half.
• Fiscal Year 2027 Guidance -- Revenue of $855.5 million–$863.5 million (8.2%-9.2% growth), non-GAAP operating margin of at least 9.75%, and net income per share of $0.37.

SUMMARY

Management announced the acquisition of Stack.ai, stating it accelerates the company’s AI workflow orchestration roadmap by over a year and extends automation capabilities across enterprise systems like CRMs and ERPs. CEO Daniel Mark Rogers described unique platform advantages such as the first is really this idea of the work graph. So what is the work graph? Well, a work graph is the place that brings together every person every task, every ticket, request, project, goal, and dependency onto a single living plan. Think of it as a neural network. So why is this important for human-to-agent collaboration? Because it turns out agents are also going to need a ledger of who is doing what by when towards which goal has it been done, who is up next, That ledger is what we have already built. So think of the work graph not just as a knowledge graph, or as a graph for a single person. But really as the living context the living plan that any actor can operate on. The second thing that we have mastered is also architecturally very difficult. Which is multiplayer mode. Multiplayer mode is the idea that humans and other humans can interact with a single agent with multiple agents. They can program the agent coach the agent, give feedback to the agent, Multiplayer mode is a difficult trick to pull off because, remember, you have got contention of whose instructions actually matter most. Who gave it last, how do you build and compound that instruction set, With our AI Teammates, you see we have solved that difficult technical challenge. Which keeping everyone congruent in a multiplayer world. The third thing that we have is a thing called shared memory. And this is the idea that every decision that has been made contributes to the next run or the next cycle of that workflow. as key to Asana’s position as the operating system for human-agent teams. CFO Aziz Megji detailed a margin improvement strategy rooted in disciplined spend, use of AI across internal workflows, and operational efficiency from both AI automation and geographic talent shifts. Management confirmed that AI product bookings already outpace the year’s target, and plans for incremental updates on AI contribution will be provided after more market data is gathered from expanded AI Teammate and Stack.ai go-to-market integration in the next quarter.

• Stack.ai’s enterprise customer base and cross-system automation platform enable Asana to address new AI buying centers within organizations, such as strategic operations and AI centers of excellence.
• Asana’s AI Studio customers exhibit the highest net revenue retention and seat expansion, providing a notable lead indicator for future ARR growth dynamics.
• Self-service product-led growth (PLG) continues to create a 2‑point drag on ARR, with guidance reflecting only modest NRR improvement and no assumptions of continued tech vertical outperformance despite recent positive trends.
• Company leaders described proactive customer engagement and earlier renewal interventions as contributors to improved gross retention, while sales pipeline quality is enhanced by AI-assisted prospecting and account planning.
• Enterprise use cases from FedEx and COS were cited to demonstrate operational impact, including “9 x improvement in speed to market” and “90% reduction in campaign setup time,” respectively.
• Management noted that future margin expansion should continue through ongoing AI deployment in product, sales, security, support, and G&A functions, with security workflow automation cited as achieving “10x to 15x greater security coverage without a corresponding increase in head count.”

INDUSTRY GLOSSARY

• Work Graph: Asana’s unified data model connecting people, tasks, projects, goals, requests, and dependencies to create a collaborative operational “ledger” for both humans and agents within workflows.
• AI Studio: A no-code Asana module that lets users embed AI-driven automations into business-critical work processes (e.g., intake, routing, reporting).
• AI Teammates: Prebuilt or custom AI agents operating within Asana’s collaborative platform to assist with tasks and automate work with context, governance, and shared memory.
• Stack.ai: A newly acquired platform enabling no-code enterprise AI workflow orchestration across systems (CRMs, ERPs, databases), with governance and automation capabilities for complex, cross-functional processes.
• ICP (Ideal Customer Profile): A segmentation used by Asana to target solutions for specific customer verticals and buying centers based on firmographic fit and workflow needs.
• PLG (Product-Led Growth): Strategy where user adoption and expansion are driven by the product experience, rather than by direct sales.
• RPO (Remaining Performance Obligations): Total contracted future revenue yet to be recognized, consisting of both billed and unbilled portions.

Full Conference Call Transcript

Eva Leung: Good afternoon, and thank you for joining us on today's conference call to discuss the financial results for Asana's First Quarter fiscal year 27. With me on today's call are Daniel Mark Rogers, our chief executive officer, and Aziz Megji, our chief financial officer. Today's call will include forward looking statements including statements regarding the expected release and benefit of our product offerings, and our expectation for revenue to be generated by those offerings, our retention and expansion opportunities, our expectation for our financial outlook, including our FY27 full year guidance, strategic plans, including with respect to current or future M&A activity, our market position and growth opportunities, and our capital allocation, including our stock repurchase program, among other items.

Forward looking statements include risks, uncertainties, and assumptions that may cause our actual result to be materially different from those expressed or implied by the forward looking statements. Please refer to our filings with the SEC, including our most recent annual report on Form 10-K and quarterly report on Form 10-Q for additional information on risks, uncertainties, and assumptions that might cause actual results to differ materially from those set forth in such statements. In addition, during today's call, we will discuss non GAAP financial measures. These non GAAP financial measures are in addition to and not a substitute for or superior to measures of financial performance prepared in accordance with GAAP.

A reconciliation between GAAP and non GAAP financial measures and a discussion of the limitations of using non GAAP measures versus the closest GAAP equivalents are available in our earnings release which is posted on our investor relation web page at investors.asana.com. And with that, I would like to turn the call over to Daniel.

Daniel Mark Rogers: We delivered a strong start to the year. Revenue of $205.1 million up 9.5% year-over-year and above the high end of our guidance. We also exceeded expectations on profitability with non GAAP operating margin expanding up to 11.5% up 27 basis points year over year. Reflects continued progress in driving both growth and operating efficiency across the business. Importantly, we are seeing positive trends across customer retention, expansion, and AI product adoption. We believe these are encouraging indicators of improving business health. 1 of the clearest indicators of this progress is net retention rate or NRR. Our reported rolling 4 quarter NRRs improved across all cohorts.

While overall in quarter NRR improved for the fourth consecutive quarter to 97% This improvement was broad based across both gross retention and expansion activity. This reflects a healthier seat adoption trend improved customer engagement, and continued early traction from our AI products. In the technology sector, we returned to positive year over year growth for the first time in 8 quarters. This is an encouraging sign that this vertical that had been a headwind over the past couple of years is now seeing improvement driven by adoption across multiple products. Customers such as CoreWeave and Epson expanded with additional seats and AI products this quarter. Growth in non tech sectors continued to outpace overall company growth.

This reflects our diversification across industries and customer use cases. We continue to see strong engagement where we tailor our solutions to customer specific ICPs and industry workflows. During the quarter, customers like 1 of the nation's premier consulting firms, and a Fortune 500 industrial technology company, both expanded their seat deployment and adopted our AI products. International revenue grew 12% year over year, which outpaced the overall business led by strong performance in both EMEA and APAC. We also added several notable customers during the quarter. Including a British athletic apparel brand, and IKEA Australia. These underscore the growing global demand for our platform, and AI solutions.

On reflection, our Q1 performance reflects the deliberate choices we made across go to market and product strategies over the past several quarters. Beginning to see measurable benefits from initiatives that have been focused on AI monetization, customer retention, sales productivity, and operational efficiency. Within our product led motion, while the business remains a near term headwind to growth, our ongoing initiatives have us well positioned for stronger long term acceleration. Asana's strategy is to become the operating system for human agent teams. We have all experienced the personal productivity uplift from working with AI chat bots. But for many organizations, that has not yet translated into real productive uplift. For their teams or their company.

This is the great AI gap today. At Asana, we believe this real enterprise productivity unlock comes from humans and agents working together on critical workflows that run the business. We see 4 reasons why most companies have not yet crossed this great AI gap. Firstly, it is hard for teams to discover agents and to visualize their current processes and workflows. Number 2, really no framework for individuals to interact with agents in a multiplayer mode with the rest of their teams. Number 3, most agents are not onboarded with context of how their teams operate and what they care about. Number 4, CIOs and IT leaders are very worried about agent-palooza.

This is agents running a mock with full access to data and with very limited cost oversight. Asana is the solution We are the operating system. For humans and agents to workflow together. Let's address each of these 4 blockers. Firstly, with Alan, our agents, Asana teammates make themselves known offering to help you as you work. So you can easily discover them and quickly visualize your workflows with no code builders. Architecturally, Asana is multiplayer from the get go. This is a fundamentally hard concept to deliver. With Alan, it means all teammates can now train and improve the agents they work with. While agents learn ambiently from tasks, and conversations with all of their human teammates.

Number 3, with shared memory and more than 20 ready-to-go agents across marketing, IT, and operations. Our teammates can scan all of the existing work in your Work Graph to pretrain themselves. Then over time, they compound their learning. Operating on a common enterprise ledger to stay coordinated. And fourth, because of our agents operating on the same coordination paradigm, built for human collaboration, it is very easy to manage their data access approve their actions, and provide cost guardrails. So what does this look like in practice? Imagine a manufacturing team launching a new product for Asana. Program manager might kick off a new product introduction process. Using our AI Studio workflow.

Then that might invoke an AI teammate to create the project draft plan, and assign the workout. Some of those tasks might lend up with humans, engineers for example. Some might be delegated to agents to handle spec reviews and supplier checks. As decisions get made, the team teaches the agents what good looks like, and the next launch runs that much sharper. This is engineering, operations, and marketing and agents all working off the same plan and moving together. Humans and agents moving work faster. Looking at our AI products, it is been roughly 1 year since the AI Studio became generally available. Adoption trends continue to strengthen.

Customers are embedding automations into their core operational workflows, AI Studio automates the repeatable work, like intake, classification, routing, quality checks, and reporting. And because Asana is no-code and embedded directly into existing workflows, customers can deploy and scale it quickly. In fact, customers are embedding AI Studio automation into their business critical workflows today. And this contributes to strong retention dynamics. Early data shows customers adopting AI Studio have higher retention and stronger net revenue retention. Relative to the broader customer base. The primary driver of NRR outperformance is seat expansion, not simply lower churn, Customers who embed AI Studio into their workflows are not only staying, they are expanding. Adding seats, and deepening their investment in the platform.

During the quarter, the number of customers spending over $100 thousand annually on AI Studio nearly doubled. This includes expansion with the largest managed health care companies in the U.S. and a multinational media and entertainment conglomerate. Now let's talk about AI teammates. Remember, these are the shared agents assigned to real projects. Working alongside real people. What differentiates AI teammates is they operate within the shared context of Asana's enterprise Work Graph with shared memory. Governance coordination, and multiplayer mode, across teams. These capabilities become increasingly important as enterprises move from experimenting with the AI to operationalizing it across real businesses to deliver real productivity.

While still early, we are encouraged by the initial customer response Paid conversion from our beta cohort has been strong, and the productivity impact is tangible. In fact, tasks involving AI teammate are now completed nearly 9x faster. Today, we offer more than 20 out-of-the-box teammates across functions, including marketing, operations, and planning. Taken together, our AI product bookings Now represent 17% of net-new ARR in Q1. This is ahead of the pace required to achieve our 15% full year target. What is particularly encouraging is the level of engagement we are seeing our AI products across some of the leading innovators in AI. Including Anthropic, and CoreWeave. Anthropic has grown with Asana as they have scaled as a company.

Building on their existing investments in AI Studio, Anthropic is also 1 of our newest AI teammates customers. And employees are now connecting Claude directly into the Work Graph to Asana's MCP integration. CoreWave, a leading AI cloud provider, has expanded its use of Asana over the past 2 years. Growing from 15 seats to more than 1 thousand across teams. And they are now an AI teammates customer. COWI uses Asana across data center operations, IT, supply chain, technical program management, and marketing. In the next 2 customer examples, FedEx and COS, we will demonstrate the operating system for human agent teams and what that looks like in practice.

In both cases, Asana's powering business critical workflows where humans and AI teammates work together with a shared context. Shared memory, multiplayer mode, and governance that enterprises require. FedEx purchased AI Studio last year. Joined the AI teammates beta at inception. And they since deployed AI powered workflows across marketing, sales, strategy, product and operations. Driving 9 x improvement in speed to market and hundreds of thousands of dollars of operational savings. Here's how it works in practice. FedEx Marketing uses AirStudio to consolidate intake from more than 24 forms into a single intelligent workflow. That analyzes submissions removes duplicate work, and routes requests to the right strategy lead. AI teammates then picks up the work.

It drafts go to market plans and creative briefs reducing cycle time from weeks to days, and reclaiming over 1.2 thousand hours annually. Looking at sales enablement, FedEx Sales was fielding high volume requests from global teams. With no standardized process for evaluating or sequencing work. Requests were assessed manually and in isolation. Making it nearly impossible to identify redundant efforts or coordinate across markets. With AI Studio, incoming requests are now automatically matched against the work graph to flag overlapping work and bundle together related initiatives before any human review. Intake review time dropped from 90 minutes to 30 minutes per request. From there, an embedded AI teammate generates go to market materials. Competitive intelligence materials, automatically.

While automated portfolios handle cross-region sequencing in real time, So seller capacity flows to the highest priority launches rather than being managed through spreadsheets. And at the leadership level, FedEx deployed AI teammates across their global portfolios. Achieving a 100% visibility into global initiatives and reclaiming over 300 hours per year previously spent on manual alignment compressing planning timelines from weeks to days. Looking at costs, COS is the global fashion brand within the H&M Group. They deployed AI Studio and AI teammates to automate campaign production across marketing, ecommerce, and regional teams worldwide.

Using AI powered intake and workflow automation, COS automatically generates full campaign projects with more than 50 structured subtasks They dynamically assign work based on asset type, region, and team capacity. And they manage cascading deadlines across the product life cycle. Preserving workflow context as work moves between departments. The quality check AI teammates then proactively reviews all completed assets. Identifies issues before they cascade, and helps coordinate execution across their global teams. This results in a 90% reduction in campaign setup time for them. A doubling of asset output to more than 1 thousand assets per campaign, and adds up to nearly 3 thousand hours of annual manual work eliminated. Freeing teams to focus on strategic and creative execution.

As COS described it, Asana has not really improved our processes, It has redefined how we work. We have established a unified and transparent ecosystem where all work is seamlessly visible. At Asana, we believe the great productivity unlock from AI comes when humans and agents work together in your business critical workflows. Stories we just heard from customers like FedEx and COS show the huge increase in velocity and output as possible, when real workflows are optimized to the AI era. And as we all know, the most complex workflows do not stay with inside a single system. They span CRMs, contracts, ERPs, collaboration tools, and every platform where work actually lives.

And that is why today, we are announcing the acquisition of Stack.ai. Stack.ai is a privately held AI software company. That offers a no code AI workflow platform that enables organizations to design, test, deploy, and govern custom AI agents and intelligent automations within business critical workflows. This platform connects workflows, data, and actions across enterprise systems to automate complex operational processes such as customer support, IT service requests, compliance workflows, and broader cross functional business operations at scale. Their customers range from small businesses to large global enterprises, with deployments spanning to more than 1 thousand workflows running on the platform.

Based in San Francisco, Stack.ai has achieved commercial traction and built a strong roster of enterprise customers across industries, including within highly regulated industries where security, governance, reliability, and enterprise grade controls are critical. Stack.ai is the logical evolution of AI Studio. And accelerates our road map by over a year. AI Studio made it easy to create powerful automations around intake routing, and request processing. Stack.ai extends those workflows across the enterprise and data sources. Enabling customers to orchestrate and automate more complex cross functional workflows that span CRMs, ERPs, databases, support systems, contracts, and custom infrastructure.

Now our customers are going to be able to quickly recruit ramped agents into their everyday work by the AI Teammates, and create simple AI rules and automations with AI Studio, and orchestrate whole processes end to end with the power of stack.ai. Together, this allows us to deliver the operating system for human-agent teams. Delivering on the real productivity promise of AI. Now proof of concept with the Stack AI team, our marketing team were able to identify a really complex SEO process They created a bidirectional integrations with 5 marketing data stores summarized insights and then handed over to an AI teammate that had been trained by their human teammates to take action. Powerful stuff.

We hope our customers are going to be as wowed as we were. Companies led by cofounders, Tony Rossignol, and Bernard Acetuno. Both MIT PhDs and 2 of the sharpest minds shaping the future of the agentic enterprise. I could not be more excited to welcome Tony, Bernard, and the entire Stack.ai team to Asana. I am even more excited to introduce Stack.ai to our customers. This is the orchestration capability enterprises have been asking for. As their workflows grow more complex. More cross functional, and more agent driven. it is been almost a year since I joined Asana. And when I look at the business today, we are making meaningful progress against a very ambitious vision.

Asana pioneered collaborative work management Our next category defining opportunity is becoming the operating system for human agent teams. As organizations increasingly rethink how work gets coordinated, and executed in an agentic world. We are executing with significantly greater focus, velocity, and operating discipline. We are shipping products faster improving sales productivity, expanding margins, and going deeper with customers than ever before. Which is reflected in our improving retention rates. And within the last year, we have become a true multiproduct AI platform. With the launch of AI Studios, AI teammates, and now adding Stack.ai into our portfolio. On June 4, we are going to host the annual marquee customer event the Work Innovation Summit, in London.

There, we will unveil our vision for the agentic enterprise, showcase the next generation of innovations across our AI products, and our broader AI platform road map. We believe Wiz will mark an important moment in our customers in the market understand Asana's role as the OS for human agent teams. Following with us on June 8, we will host a webinar for investors and analysts focused on the future of human agent work and the role Asana's OS for human agent teams is going to play in enabling the self driving enterprise. We will showcase our latest product innovations and road map and demonstrate how customers are already realizing value. from AI Studio, AI teammates, and stack.ai.

Additional details about the webinar will be available on our investor relations website shortly. With that, I will turn things over to Aziz Megji.

Aziz Megji: Thanks, Daniel. Let me highlight the financial results for the first quarter and then comment on the outlook. Q1 revenues were at $205.1 million up 9.5% year-over-year. This includes an approximately 70 basis point tailwind to revenue growth on a constant currency basis, 10 basis points higher than our original guidance. We have 26.1 thousand core customers. We define as customers spending $5 thousand or more on an annualized basis. Revenues from core customers grew 10% year over year. This cohort represented 76% of our revenues in Q1. We have 817 customers spending $100 thousand or more on an annualized basis, and this customer cohort grew 12% year over year.

As a reminder, these customer cohorts are defined based on annualized GAAP revenues in a given quarter. Our overall dollar based net retention rate was 96%. Core customer NRR was 97%, among customers spending $100 thousand or more, NRR was 96%. And as a reminder, our NRR is a trailing 4 quarter average and therefore a lagging indicator of more recent trends. As Dan mentioned earlier, we saw rolling 4 quarter NRR improve across all cohorts, with in-quarter overall NRR of 97% improving for the fourth consecutive quarter. The improvement was driven by continued strength in gross retention and healthier expansion trends. Reflecting broader multiproduct adoption across the customer base.

Growing contribution from AI products, and continued seat expansion within our enterprise customers. We also continue to see benefits from the investments we have made in engaging customers proactively earlier in the renewal process, driving higher seat utilization, mitigating downgrade, risk with AI products, and ongoing improvements in CSAT. All of which are contributing positively to retention trends across our customer cohorts. Turning to our self-service business. Our guidance continues to assume approximately a 2-point drag on ARR growth from PLG reflecting an ongoing shift in how customers discover and evaluate software as AI search and LLM driven experiences continue to evolve.

We are beginning to see encouraging early signals from the initiatives we have been driving over the past 6 plus months. This includes organizational trial starts, trending up sequentially for the first time in over 5 quarters alongside improved trial conversion and stronger product qualified lead performance. Our focus has been on improving acquisition quality, aligning the funnel toward customers with stronger collaborative intent, and longer term retention characteristics, accelerating time to value. We also continue to see improving productivity across our sales organization. This is driven in part by investments in AI powered prospecting and account planning tools. This has also contributed stronger sales efficiency, improved inbound pipeline generation.

We also saw continued strong synergy between our product led and sales led motions through more targeted, higher converting product qualified leads that are being passed to our sales teams. Now moving to profitability. Where I will be discussing non GAAP results and year over year comparisons. Our gross margin was 88%. R&D expenses were $47.5 million or 23% of revenue, down 270 basis points. Sales and marketing expenses were $83.5 million or 41% of revenue, an improvement of 20 basis points. And G&A expenses were $26.7 million or 13% of revenue, an improvement of 360 basis points. We delivered an 11.5% non GAAP operating margin or a $23.6 million of operating income.

This represented a 720-basis point improvement year over year. Our results also benefit from approximately $3 million of operating expenses that shifted from Q1 into the second half due to the timing of spend related to our work innovation Summit events and their associated marketing campaigns. Net income was $24.4 million or $0.10 per share on a diluted basis. Our profitability improvements continue to be driven by operating leverage, disciplined allocation of spend toward our highest return go to market motions, optimization of infrastructure and cloud costs, and discipline around back filling and headcount growth as we realize increasing efficiency benefits from AI across the business.

In R&D, sales, marketing, support, and G&A workflows, we are deploying AI Studio, AI teammates, third party AI tools to automate work, accelerate execution, and reduce manual coordination. 1 example is our security team. The team could not scale headcount fast enough to keep pace with engineering. So they embedded AI teammates directly into their review processes. When a new feature is proposed, an AI teammate automatically surfaces risks prior prioritizes fixes, and collaborates with engineers before code is even written. With human reviewers finalizing each assessment. The result is 10x to 15x greater security coverage without a corresponding increase in head count.

And at the same time, we continue to align our talent footprint with more cost effective regions and organizational structures, creating a strong foundation for sustained efficiency, operating leverage, and multiyear margin expansion. Moving on to the balance sheet and cash flow. At the end of Q1, cash, cash equivalents, and marketable securities were approximately $424.6 million. Our remaining performance obligations or RPO, was $518.1 million, up 23% year over year, and current RPO grew 9% year over year over year. This represents 79% of total RPO and will be recognized over the next 12 months. Year over year growth rates accelerated for both RPO and CRPO relative to last quarter.

Our total ending Q1 deferred revenue was $320.1 million, up 11% year over year. Building on our operating margin strength in Q1, adjusted free cash flow was $34.4 million in the quarter or 17% of revenue on a margin basis. The stronger than expected free cash flow was partly due to earlier than expected collection activities in Q1, which we expect to normalize over the course of the year. This quarter, we bought back $45 million of our Class A common stock or 7.4 million shares at an average price of $6.11 per share. As of April 30, we have roughly $155 million available on our current program for future repurchases.

We continue to believe repurchasing shares at current levels represents an attractive use of capital relative to the long term value creation opportunity. Believe we can buy back shares while preserving the financial flexibility to invest in innovation, growth, and strategic opportunities. Now turning to our acquisition of Stack We are excited about the long term growth opportunity as we enable our go to market organization to bring these cross system AI workflows to our customer base over time. The transaction includes approximately $75 million in upfront cash consideration along with an additional equity based earn out opportunity. Structure was designed to support long term retention and align performance with long term incentives.

The acquisition also adds approximately 50 highly talented employees across engineering and AI focused go to market functions. This significantly strengthens our tech and go to market capabilities and accelerates execution against our AI road map. Importantly, even after adjusting our Q1 cash balance for the transaction, we would have over $350 million in cash, cash and cash equivalents, and marketable securities remaining on the balance sheet, which includes an assumption of $3 million of cash on Stack.ai's balance sheet. Transaction does not change our existing share repurchase authorization. Or plans to buy back stock or retire our outstanding term loan at maturity.

Transaction also does not change the directional assumptions we provided for stock based compensation, which we expect to remain in the low 20s as a percentage of revenue for the fiscal year. We recognize that stock based compensation and dilution remain elevated, As we balance driving toward GAAP profitability, attracting and retaining top talent, and executing against what we believe is the strongest product road map in the company's history, remain focused on proving our stock based compensation as a percentage of revenue. The same operational improvements driving margin expansion combined with discipline around equity grants, should drive down SBC and dilution over time.

Before I walk through the guidance, I want to reiterate that the core assumptions underlying the FY 27 outlook we shared last quarter remain largely unchanged. First, PLG remains a near term headwind, and our guidance still assumes approximately a 2-point drag on ARR growth from this motion. Second, we continue to assume only modest improvement in our net retention rates over the course of the year. Third, our guidance does not factor in the improvement we have seen in the tech vertical over the past few quarters, including the return to positive year over year growth we saw in Q1.

Lastly, we are maintaining our expectation that AI product bookings contribution to net new ARR will represent approximately 15% in FY 2027. Are encouraged by the momentum we are seeing across our AI products. We With Q1 AI product bookings contribution to net new ARR coming in ahead of our expectations, and Stack.ai expected to provide incremental AI contribution going forward. Instead of making incremental updates to our full year AI product contribution assumptions each quarter, we will provide a comprehensive outlook during our Q2 call.

This timing allows us to evaluate a full quarter of AI teammates in the market evaluate the launch, of AI Teammates into our PLG motion, which will happen in the beginning of the second half. And advance our go to market integration and enablement of stack.ai. Now turning to margins. We believe the structural efficiency improvements we have made and continue to make across the business create capacity to invest beyond our AI products while still expanding profitability. We expect Q4 exit operating margin for FY 2027 to be above our full year operating margin guidance. Stack.ai is expected to represent approximately a 1 percentage point drag on operating margins in Q2 and the second half of FY 27.

This is fully reflected in our guidance. Now moving to guidance. For Q2 fiscal year 2 thousand 27, we expect revenue of $213 million to $215 million representing 8.2% to 9.2% growth year over year. Our guidance includes an expected contribution from Stack.ai of 50 basis points to growth. We expect an immaterial impact from currency this quarter. non-GAAP operating income, we expect to be in the range of $18 million to $20 million representing an operating margin of 8.5% to 9.3%. For non-GAAP net income per share, we expect to be in the range of $0.08 to $0.09 assuming diluted fully weighted average shares outstanding of approximately 237 million shares.

For the fiscal year 2027, we expect revenue in the range of $855.5 million to $863.5 million representing growth of 8.2% to 9.2% year over year. Full year revenue guidance reflects the outperformance from Q1 results and includes an expected contribution from Stack.ai of approximately 50 basis points to growth. Based on current FX rates, we expect an immaterial currency impact for the remainder of the year and an approximately 20-basis point tailwind to our full year revenue growth in constant currency. Same as last quarter. For the full year, we expect non GAAP operating margin of at least 9.75%.

And we expect non GAAP net income of $0.37 per share, assuming diluted weighted average shares outstanding of approximately 239 million shares. We are seeing continued improvement across the business, including accelerated momentum across our AI products and deeper adoption of Asana in mission critical workflows. The addition of Stack.ai further strengthens our position as the operating system for human agent teams, and we remain very excited about the opportunity ahead. With that, operator, we are now ready for questions.

Operator: Thank you. As a reminder, if you would like to ask a question, please press *11 on your telephone. You will hear the automated message advising that your hand is raised. We also ask that you please limit yourself to 1 question and 1 follow-up. And wait for your name and company to be announced before proceeding with your question. 1 moment while we compile the Q and A roster. The first question of the day will be coming from the line of Robert Oliver of Baird. Your line is open.

Analyst (Robert Oliver): Brent. Thanks. Good afternoon, Aziz. Look forward to working with you. Daniel, I had 2 questions, and I will start with the first for you. So stack.ai, you called out it accelerates your roadmap. I think by a year. What was really the most compelling reason for you to do it now? And how quickly, can you integrate that into what you guys have currently? And then I had a quick follow-up.

Daniel Mark Rogers: Yeah. Hi, Robert. So all starts with our customers. You know, we launched AI Studio to our customer base and it was deeply adopted. And what we found is they wanted to automate more and more and more parts of their workflow. And extend those workflows to third party systems. So they wanted to create automations that bled into their CRM systems or into their databases or into some of their ordering systems. And when you think about that, we kinda said, look.

We can continue the AI Studio roadmap, and we kind of had a very nice plan about how we were gonna add all these third party integrations these orchestrations across multi-systems, or we can deliver that today to our customers. So when we found Stack.ai and we interviewed and spoke to many of their customers, this is exactly where they were getting the traction today. They had demonstrated already with their customers these complex operating environments across some of the most I would say, regulated industries and regulated use cases. So our ability to bring that to our customer base today was just something we were licking our lips at, honestly. So we are super excited.

In terms of acceleration, yeah, you know, we say this accelerates our roadmap by a year. They have built advanced workflow orchestration. Configurable knowledge bases, RAG layers, MCP infrastructure, all the things that we would love to have built ourselves and we are planning on doing but why not deliver it to our customers today? Some of their customers, as an example, have already adopted 1.4 thousand workflows in just a single customer So if you can imagine taking that to our user base, I think they are gonna be very excited.

Analyst (Robert Oliver): Brent. Really helpful. And then my follow-up is, you guys are clearly making some progress here in the efforts you have put into kind of restart the business on the growth side, in particular, with some of the non tech customers and more kind of specialized end markets. And I think you called it out in your prepared remarks that you are seeing nice success with those customers. I would be curious to know if you guys have made any changes to the go to market team to verticalize that since you are seeing some success there? And then as we get Stack.ai more integrated, does this motion require FTEs as well? Thank you.

Daniel Mark Rogers: Yes. So, again, I will take that question, Robert. So if you think about the groundwork that we have been laying over the last 9 months, The first piece has really been about multiproduct, and multiproduct for us is a way to get to multi buying center. And so you see AI Studio, AI teammates, and now Stack. Those are all part of the same ambition, which is to better serve those ICPs. And you will see this will continue in our innovation summit work innovation summit next week, where you will see directly how we are going to please and delight, more of those buying centers.

The second piece of the kinds of things we have been focused on is around customer health, which is about making sure that our customers adopt and enjoy our products which is what you are seeing start to show up in our results and seat expansion. The third has been around sales productivity, and sales productivity is about making sure we hit that sweet spot, that we hit the problems that our customers have today that we are clearly speaking in their language of jobs to be done, by both department and by vertical.

And then the final piece of, say, the things we have been doing over the last 9 months has really been about going faster, operating at velocity and operating, and executing pace. And so the combination of all of those things is definitely squarely focused on better serving our ICP and expanding the buying centers that we can talk to.

Operator: Thank you. 1 moment for the next question. And our next question will be coming from the line of Matt Bullock of Bank of America. Please go ahead.

Analyst (Matt Bullock): Oh, great. Thanks for taking the question. Wanted to ask about the technology vertical and some of the AI native printer model providers you mentioned in the prepared remarks. So I understand that the guidance does not contemplate continued positive growth in the tech vertical. Can you just help us understand what drove the return to positive growth this quarter? Whether or not customers like Anthropic adopting some of your AI products had any contribution to that? And then I have a follow-up.

Daniel Mark Rogers: Yeah. Well, maybe I will start with the Anthropic piece, and then I will I will let Aziz talk about broader technology. We love the partnership with Anthropic, and I characterize it as 3 things. 1, they are a customer of ours. So as they grow, we grow. So we have a number of broad use cases across Anthropic, including their usage of AI Studio and AI teammates, this kind of reiterates the point that we are the OS for human agent teams, a place where you can get things done across humans and agents. And, you know, we are that operating layer that sits on top of the AI layer as it were.

So that is them as a customer. They are also a product partner. And so, you know, we were 1 of the flagship workplace integrations, 1 of 9. That they launched with. And we have launched a great NCP service, which allows our joint customers to access the work graph directly there, in kind of the prompt window from Claude. And increasingly, they will become a distribution partner for us We presented at Claude.ai, 1 of the keynotes there. We were a part of their connector directory. And, of course, through our AEO efforts, they become an important distribution partner for us. So, yes, we love the partnership, with Anthropic and, you know, more of that to come.

Aziz Megji: I will hand over to Aziz Megji now. Yes. Yes. So on the tech vertical, we are really encouraged about now kind of 2 quarters in a row. Last quarter, kind of stabilized to flat growth. And then resumption of growth after 2 years to a positive growth. We have not factored that into our guidance. Our guidance still assumes trends from 2 quarters ago, you know, we are encouraged, but, you know, we need some additional, positive inflection to get more get more constructive and include in the guidance such as our philosophy. what is driving that? it is primarily expansion.

So our tech customers have been early adopters of AI Studio, and now we are seeing that again with AI teammates You know, Daniel called out Anthropic. CoreWeave, you know, a large portion of those early adopters of teammates have been in the tech vertical. So expansion with our add ons has been a key driver of that presumption to growth. And then secondly, we have seen seat expansion. So, you know, as these tech companies have gotten deeper adopted with AI Studio, that is also led to seat expansion, so we are super encouraged about that. And retention's also trending in a positive direction as well.

So it is, expansion and retention, but a lot of that driven by, adding on AI Studio and Teammates. Really helpful.

Analyst (Matt Bullock): And then if I could just sneak in a quick follow-up. Can you unpack some of the drivers of the 100 k plus customer count this quarter? It looked a little bit softer than, I think, some were expecting. Was that a function of more less customers graduating above that line, some selling down? Just trying to better understand that metric. Thanks.

Aziz Megji: Yeah. Maybe I will just I will start with a few general comments, and this is a pickup as well.

Daniel Mark Rogers: If you think about our multiproduct strategy, this is really, helping us expand those customers and have more reasons to talk to them about more things and more buying centers. And we are at the grassroots of many of those products. Right? So AI teammates is really just 60 days of GA. AI Studio, about 9 months. And, of course, with stack.ai, we are we are on day 1. And so, you know, that is that is gonna be a growing piece of that story. And then our customer health initiatives, which are very much around making sure that our customers are adopting all of our products and using them fully, is along the same lines.

And, similarly, how we are executing, prosecuting with our sales teams and our particularly our enterprise sales teams These are all going to be great drivers for a $100 thousand-plus lands, and then we will talk a little bit more about their expansion. But, yeah, generally, the theme is grassroots and a bit early on some of the transformation that we have been driving there.

Aziz Megji: Yeah. And just to add on to that, you know, the cohort grew 12% year over year. And as you pointed out, was sequentially flat. A couple of things there. We are seeing strong expansion within the cohort. So those NRR improvement and expansion drivers that I called out for tech, which also apply to nontech, as well, is showing up in actually the growth of our 100 k customers within the cohort, versus adding new ones. And then secondly, you know, we tend to view that metric on a year-over-year basis. there is some noise looking at it quarter to quarter. Especially Q4 to Q1.

You know, there is less days in Q1 versus Q4, so that just kinda changes the trajectory. So we look at the comparability on a year-over-year basis, but 12% growth is what we anchor to. And then the second thing I would add is if you look at the AI Studio cohort, and we do not break out the 100 k customers, but those almost doubled quarter over quarter. So we are seeing strong growth in $100 thousand-plus with AI Studio as they increase their adoption usage, and we add new customers into that cohort. So we are encouraged by those trends and we expect the cohort to continue to grow as those trends continue.

Operator: Thank you. 1 moment for the next question. Our next question will be coming from the line of Patrick Walravens of Citizens. Please go ahead.

Analyst (Patrick Walravens): Oh, great. Thank you. And, Daniel, it is good to see the progress. Under your tenure. 1 question I have for you is I like the strategy of an operating system for human AI teams. I think it is it is compelling. And it is just so noisy right now. Right? You have Microsoft with Copilot for Microsoft 365, ServiceNow with Control Tower, Workday with the agent of record, and, you know, the list goes on and on. How do you how do you break through all the clutter to deliver your message? What do your salespeople do? How do you do it?

Daniel Mark Rogers: So may maybe I will parse the question into 2 pieces. First is, like, how are we unique? So I will talk a little bit about our positioning. And the second is how do we get the message out to the world? So for the first part, in how are we unique in, you know, a crowded market, Look. I think the good news is we all understand that the future of work is humans and agents collaborating together. And that really is that workflow that is gonna be the great productivity unlock from AI.

So that is good news that we understand that is the place to be. it is particularly good news for Asana over the last 18 years, we have been building an operating system for human to human collaboration that lends itself very well and beginning today, we become the operating system for human agent collaboration. So what is it about our platform that has allowed us to become ubiquitous as a human to human collaboration. Well, the first is really this idea of the work graph. So what is the work graph? Well, a work graph is the place that brings together every person every task, every ticket, request, project, goal, and dependency onto a single living plan.

Think of it as a neural network. So why is this important for human-to-agent collaboration? Because it turns out agents are also going to need a ledger of who is doing what by when towards which goal has it been done, who is up next, That ledger is what we have already built. So think of the work graph not just as a knowledge graph, or as a graph for a single person. But really as the living context the living plan that any actor can operate on. The second thing that we have mastered is also architecturally very difficult. Which is multiplayer mode.

Multiplayer mode is the idea that humans and other humans can interact with a single agent with multiple agents. They can program the agent coach the agent, give feedback to the agent, Multiplayer mode is a difficult trick to pull off because, remember, you have got contention of whose instructions actually matter most. Who gave it last, how do you build and compound that instruction set, With our AI Teammates, you see we have solved that difficult technical challenge. Which keeping everyone congruent in a multiplayer world. The third thing that we have is a thing called shared memory.

And this is the idea that every decision that has been made contributes to the next run or the next cycle of that workflow. And then finally, again, I think we have a very clever and unique way of bringing enterprise governance into this agentic tapestry. Because we make sure that every agent has identity scope permissions, and audit trail and cost constraints, just as the humans do in the teams that they are operating within. So our AI agents literally drop into the same work graph as our humans have already been operating against. So this is very unique.

It unblocks some of the main blockers today, about why companies have not yet identified, why they have not all got teams of agents working alongside them. Those are some key, kind of, I would say, differentiators in our positioning. We were built for this. You know, I kind of said when I started, you know, maybe 6 or 9 months ago, that collaborative work management is about to see its day in the sun. And the day in the sun is yes. It turns out collaboration challenge actually grows exponentially with humans and agents operating alongside each other. So that is a little bit about positioning.

And as you think about how are we going to get our word out, well, it kind of starts today. You will see that us rolling into our work innovation summit on June 4 where we will share more of our ambition and more of our product road map with our customers. And then you will see us be a lot more vocal with our marketing and sales teams to make sure they understand how we can help customers get through this AI productivity gap that they have been experiencing and come out on the other side of it.

Analyst (Patrick Walravens): Oh, great. Well, thank you for all that all that color.

Operator: 1 moment. Thank you. 1 moment for the next question. And our next question will be coming from the line of Jackson Ader of KeyBanc. Your line is open.

Analyst (Jackson Ader): Brent. Thanks for taking our questions, guys. The first 1 was just a clarifying question on the $100 thousand customers that are AI Studio customers. Are these people spending $100 thousand on AI Studio or are they $100 thousand customers that also happen to be AI Studio customers.

Aziz Megji: No. They are a 100 thousand on the SKU for AI Studio. They spend with their seats would be greater than that. So it is it is just the AI Studio SKU.

Analyst (Jackson Ader): Okay. Wow. And then what is, like, the typical spend for 1 of those customers on, you know, I will call it, like, core Asana. Look like relative to It ranges. It ranges, but it can you know, it is double digit. The spend on AI Studio is a double digit percentage of what their core Asana spend is. Okay. Alright. Got it. I am counting that as only 1 So my second question is my second question is, you know, the Stack.ai acquisition it sounds like, okay. Part of the play is a little bit more embedded into enterprises, so you can kinda go to market there in a shared way.

But I am curious, like, you know, Daniel, you mentioned this a little bit, but who is the buyer for stack.ai? And is that persona is that budget, are those dollars coming from the same place in the enterprise where it would come from in order to buy the core Asana platform or these AI Studio or Teammates, SKUs. Thank you.

Daniel Mark Rogers: Yeah. No. Great question. So I would say increasingly, there are people in an organization responsible for AI transformation. Increasingly, there are actually AI centers of excellence. We find this to be a great place to start for AI transformation conversations. And so this idea that you can create cross enterprise workflows that are automated and identified really matches well with, I would say, that buying center. That buying center now can appear in operations teams. It can also appear in IT teams. And so those were already places that we had conversations, already places that we were, bringing the value of collaborative work management. This does allow us to go, let's say,, across and up in many cases.

So definitely new buying centers there is a new role that is responsible in many organizations for this left to right workflow orientation. But, really, anyone that is a strategic operations leader is very much, kind of in our sights.

Operator: Thank you. 1 moment for the next question. And our next question will be coming from the line of Steven Enders. Of Citi. Your line is open.

Analyst (Steven Enders): Great. Thanks for thanks for taking the questions here. I guess to start, I guess I wanna follow-up on some of the AI conversation and just maybe how does the I guess, customer behavior changing with the adoption of Studio? Like, how are you seeing seat ads or other kind of core usage of that change? And, I guess, any changes there as well with some of the early teammates feedback from the beta program. Well, maybe I will take the kind of, use case and jobs to be done around AI Studio.

Daniel Mark Rogers: So think of AI Studio as the way to bring automations and AI nodes into your automations to life. So think any intake process, routing, approvals, request processing, translation, quality control, operational coordination, all of those kind of, I would say, automations you can really supercharge, with AI Studio. So in doing so, that does more squarely place us into business critical workflows. And so it definitely allows us to have a richer and deeper relationship with our accounts, With the addition of Stack, that extends, of course, into cross system orchestration. So even more business criticality when it touches CRM, ERP, databases, support systems, contract management, you know, custom infrastructure, you kind of name it.

AI teammates is a more egalitarian idea. And this is about supercharging your teams, whichever team you are in. And it is really about helping people get work done with team members that they can bring in to help them with things like status reporting, launch planning, workflow optimization, research, coordination, execution support. And so we have a set of 20 to 25 prebuilt AI teammates that anyone can bring to light for them in their day to day work. This--

Aziz Megji: Just to add on to that, you know, we are seeing those customers so it is been a year, and we are seeing those customers who adopted AI Studio. They are actually being the strongest NRR cohort within our base. So the NRR for those customers that adopted AI Studio is stronger than those that have not by actually a pretty wide margin on both seat expansion, and we are seeing, you know, this 100 k cohort a lot of them have originated as, smaller cohorts, smaller buys, and then expanded in that. From a usage standpoint, you know, we have seen tremendous growth in usage.

We are not quantifying that, but we are seeing in those earlier cohorts greater usage by significant margin and we are encouraged by that. And, obviously, adding Stack, it is a natural expansion path for those studio customers over time. From kind of simple automations within Asana to more complex end to end executions with Stack.ai that are cross system. So we see a nice upgrade path for the current users and future AI Studio customers as we continue to grow that motion to stack. So that is another piece. But we are we are encouraged. And on teammates, it is early. You know, we are we are seeing good initial progress.

Only been a couple months, but the pipe is growing fairly rapidly there. Those who have adopted it, the usage has been fairly strong. Both on the out of the box teammates and even creating their own custom teammates, seeing good engagement there. And, you know, we are really excited about bringing that to our PLG base in the second half and opening up the SAM within our base to teammates.

Analyst (Steven Enders): Okay. that is that is great to hear. And maybe just a follow-up. Just on the tech vertical, think there is been quite a few, you know, layoffs so far. This year across the space. I guess when you kind of have those conversations with customers in that vertical, just how are those headcount changes maybe impacting Or, I guess, have you seen any impact yet from that vertical in terms of what that means for some of the go forward employee levels or seat levels within that cohort.

Aziz Megji: Yeah. So a couple things there. You know, as we said in the published remarks, on our NRR assumptions, like, we have only factored in modest improvement to NRR into the guidance. So that would imply we have been seeing pressure in the tech vertical for multiple years. A lot of that has been layoff activity in those tech customers or lack of headcount growth. So that would imply that is kinda implicitly factored in. But being a multiproduct company, we have mitigants to that now, which Studio and teammates, and we have seen success you know, customers downgrading seats because they let go of people. We are able to mitigate that with Studio.

And teammates to preserve that ARR and, in some cases, actually still accrete that ARR. So you know, that has been really an important motion for us. But as we think about the guide, like, we have been deliberate about how we factored NRR into the guide. To absorb some of this if it continues as we continue to scale those consumption based motions that are very early for us, but showing promise.

Operator: Thank you. 1 moment for the next question. And our next question is coming from the line of Josh Baer of Morgan Stanley. Please go ahead.

Analyst (Josh Baer): Brent. Thank you for the question. I mean, I know it is hard to talk about growth beyond this year's guidance, but I do think a return to 100% net retention rate, accelerating growth into know, double digits is really important for the stock, and an important milestone for rerating. I am assuming that, you that you believe that those you know, that path is possible. And so I am wondering if you could help frame the business case, the perspective around product and go-to-market. What needs to what needs to happen? What do we need to see in the coming years to kind of reach that better growth in the future. growth in the future.

Daniel Mark Rogers: Thanks, Josh. And, yeah, I agree that is a significant milestone from where we achieve that. So that is definitely in our scopes. If you think about the I guess, the leadership platform of, the things I have been doing, the first is become a multiproduct platform. And you saw us launch AI Studio AI Teammates, stack.ai, and now in, you know, in a couple of weeks, you will see even more ambition at our work innovation summit. So multiproduct platform is definitely a big part of NRR. The second 1 is customer health, which is really about making sure that we spend a lot of time with our customers, getting them to the value that they hoped to achieve.

And you will see a deliberateness around that, a concerted deliberateness around adoption and utilization. The third has been around our own sales productivity and making sure our sellers are as effective as they can be, and, you know, delivering more dollars per rep as we go out into the into the field. And then finally, operating velocity, which is really about us internally making sure that we are delivering everything on a faster cadence. So if you imagined you know, maybe our mindset was something was going to be delivered in 3 weeks or now we are trying to deliver the same thing in 1 week.

That all adds to more innovation, more innovation internally in our processes, but most importantly, innovation that customers are gonna be able to experience, and enjoy. So those are some of the levers. And I and I agree that will be a great milestone.

Analyst (Josh Baer): Great. Thank you very much.

Operator: Thank you. 1 moment for the next question. And our next question will be coming from the line of Billy Fitzsimmons of Piper Sandler. Your line is open.

Analyst (William Fitzsimmons): Hey, Daniel and Aziz. Hope you are doing well. Thanks for taking the question. Can we double click on the positive trends in NRR? And maybe it makes sense to kind of break it down into its components because it seems like it is both a combination of multiproduct adoption and importantly, seat growth. And on multiproduct adoption trends, a lot of the AI products you have talked about are still new. It seems like the strongest growth is coming from customers that are kind of AI first already, like a CoreWeave and Anthropic, but got to imagine there is a material portion of the base. Who is kind of much earlier in their general AI journey.

So help us think about the run rate and motion for those other outside AI companies. And then I have seen expansion and kind of the growth you are seeing. Is this just kind of your largest customers continue to add headcount, leaving to more seats? Or are there other factors there you would point to, like sales execution or your AI product portfolio leading to a difference in conversation that brings more people onto the platform. Thank you.

Aziz Megji: Yeah. So we are seeing an NRR improvement across both tech and nontech. You know, we called out FedEx and costs this quarter who expanded with seats and teammates. We are seeing it in both tech and nontech. And, know, on the NRR, for quarters of improvement in quarter to 97%. It was actually in that sequence of improvement. It was actually the largest degree of improvement, and that improvement from Q4 to Q1. And that is coming both on GRR and on expansion. So GRR actually also has improved for 4 straight quarters. So we are we are very encouraged by that.

And, you know, the larger piece of that expansion of the improvement in NRR has been on expansion. So that is not only with our AI products, that is early, but that is contributing nicely. But it is also seat expansion. As I said before, you know, we are seeing the greatest seat expansion with those that have adopted our AI products. there is a nice flywheel growing there that as we grow our AI products, we are seeing that associated growth in seats. And that compounds the expansion and thus the NRR. So that is been fairly positive. And the seat growth, has been both on expanding seats and also new logos.

We called out a couple new logos in the prepared remarks, but we still see strong new logo growth and new business, tech and nontech, which is super encouraging, and higher degrees of attach on those new logos with Studio and now increasingly teammates, which will be an important driver for us as we know, we are now as Daniel has said, we are multiproduct. That means that we can land larger ACVs on the outset and then expand from there. So you know, NRR is taking a nice trend. You know, next quarter, the large customer downgrade laps off.

So that is another catalyst for improvement along with, you know, continuing to improve expansion and customer health as Daniel called out.

Operator: Thank you. That does conclude today's Q and A session. And I would like to turn the call back over to Eva for closing remarks. Please go ahead.

Eva Leung: Thank you everyone for joining the call. We will be on the road attending the Bank of America and the Baird Conference next week. And of course, please join us for the investor webinar on June 8. Looking forward to seeing all of you. As always, if you have any questions, please reach out to me at [email protected]. Thank you very much.

Operator: This does conclude today's program. Thank you all for attending. You may now disconnect.