Q1 2026 Agora Inc Earnings Call
Operator: results conference call. To ask a question during the session, you will need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. The company's earnings results, press release, earnings presentation, SEC filings, and a replay of today's call can be found on its IR website at investor.agora.io. Joining me today are Tony Zhao, Founder, Chairman, and CEO, Jingbo Wang, the company's CFO. During this call, the company will make forward-looking statements about its future financial performance and other future events and trends. These statements are only predictions that are based on what the company believes today. The actual results may differ materially.
Speaker #1: Results conference call. To ask the 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.
Speaker #1: To withdraw your question, please press star 11 again. Please be advised that today's conference is being recorded. The conference earnings results press release earnings presentation SEC filings and a replay of today's call can be found on the IR website at investor.agora.io.
Speaker #1: Joining me today are Tony Zhao, founder, chairman, and CEO; Jimbo Wang, the company CFO; joining this call, the company will make forward-looking statements about its future financial performance and other future events and trends.
Speaker #1: These statements are only predictions, data based on what the company believes today. The actual results may differ materially. These forward-looking statements are subject to risk, uncertainties, assumptions, and other factors that could affect the company's financial results, and the performance of its business, and in which the company discuss in details in its filings with the SEC.
Operator: These forward-looking statements are subject to risks, uncertainties, assumptions, and other factors that could affect the company's financial results and the performance of its business, and in which the company discuss in details in its filings with the SEC, including today's call, earnings press release, and the risk factors and other information contained in a final prospect relating to its initial public offering. Agora, Inc. remains no obligations to update any forward-looking statements the company may make on today's call. With that, let me turn it over to Tony. Hi, Tony.
Speaker #1: Including today's call, earnings press release, and their risk factors, and other information contained in the final prospect relating to its initial public offering. Agora, Inc. remains no obligations to update any forward-looking statements the company may make on today's call.
Speaker #1: Now, with that, let me turn it over to Tony. Hi, Tony.
Speaker #2: Hey, thank you, Operator. And welcome, everyone, to our earnings call. I'll start with a review of our operating results for the quarter. I'm pleased to report our six consecutive quarter of gap profitability, alongside another quarter of strong top-line growth.
Tony Zhao: Thank you, operator. Welcome everyone to our earnings call. I'll start with a review of our operating results for the quarter. I'm pleased to report our sixth consecutive quarter of GAAP profitability alongside another quarter of strong top-line growth. Total revenue for Q1 2026 reached $37.7 million, up 13.5% year over year. Growth further accelerating our prior quarters. GAAP net profit was $1.1 million, more than double the level of Q1 last year. These results reflect the continued expansion of our real-time engagement use cases globally, as well as the increasing contribution from AI-related applications and products built with our solutions. Now, let me turn to our business product and technology update for the quarter. Over the past several months, we continue to make progress in bringing conversational AI to real-world production, deepening the capabilities with our real-time engagement infrastructure and expanding our ecosystem partnerships.
Speaker #2: Total revenue for the first quarter of 2026 reached $37.7 million. Up 13.5% year over year. Gross further accelerating our prior quarters. Gap net profit was $1.1 million.
Speaker #2: More than double the level of Q1 last year. These results reflect the continued expansion of our real-time As well as the increasing contribution from AI-related applications and products built with our solutions.
Speaker #2: Now, let me turn to our business product and technology update for the quarter. Over the past several months, we continued to make progress in bringing conversational AI to real-world production.
Speaker #2: Deepening the capabilities with our real-time engagement infrastructure and expanding our ecosystem partnerships. In March, we officially launched an agent studio. A visual no-code environment that enables developers and enterprise to rapidly build, test, and deploy with AI agents at scale.
Tony Zhao: In March, we officially launched Agent Studio, a visual no-code environment that enables developers and enterprises to rapidly build, test, and deploy voice AI agents at scale. We also introduced conversational AI agents for inbound use cases such as customer service, as well as outbound use cases focused on sales and marketing. The market opportunity here is enormous. According to Gartner, conversational agents are expected to automate 70% of customer interactions by 2027, and by 2028, AI agents are projected to outnumber human sellers by 10 to one. At the same time, many enterprises still struggle to deploy voice AI in production environments. The challenge is not simply the AI model itself, but the complexity of orchestrating multiple technology layers while maintaining low latency, reliability, and the natural conversational experience at scale. In addition, effective enterprise deployment require domain-specific expertise.
Speaker #2: We also introduced conversational AI agents for inbound use cases such as customer service, as well as outbound use cases focused on sales and marketing.
Speaker #2: The market opportunity here is enormous. According to Gartner, conversational agents are expected to automate 70% of customer interactions by 2027. And by 2028, AI agents are projected to outnumber human sellers by 10 to 1.
Speaker #2: At the same time, many enterprises still struggle to deploy with AI in production environments. The challenge is not simply the AI model itself. But the complexity of outreaching multiple technology layers while maintaining low latency reliability and the natural conversational experience at scale.
Speaker #2: In addition, expected enterprise deployment requires domain-specific expertise. A successful voice AI agent must do more than respond accurately and must reflect the tone, personality, and workflow of the industry.
Tony Zhao: A successful voice AI agent must do more than respond accurately. It must reflect the tone, personality, and workflow of the industry it serves. For example, a car sales assistant and a debt collection agent need very different conversational styles, confidence levels, and customer engagement approaches. Our solution is designed to eliminate this complexity through a fully integrated stack that combines three core components, that allows enterprise to design, test, and deploy AI agents in minutes rather than weeks or months. Second, our conversational AI agent orchestrates ASR, large language model, and TTS capabilities with intelligent interaction handling, noise suppression, multilingual support, and domain-aware conversation design, enabling more natural and human-like interactions. Third, our global real-time network infrastructure delivers sub-second latency and carrier-grade reliability worldwide.
Speaker #2: It serves. For example, a car sales assistant and the stat collection agent need very different conversational styles. Conference guardrails and customer engagement approaches. Our solution is designed to eliminate this complexity through a fully integrated stack that combines three core components.
Speaker #2: That allows enterprise to design, test, and deploy AI agents in minutes rather than weeks or months. Second, our conversational AI agent outstrips ASR, large language model, and TTS capabilities with intelligent interaction handling.
Speaker #2: Noise suppression, multilingual support, and domain-aware conversation design. Enabling more natural and human-like interactions. Third, our global real-time network infrastructure delivers subsecond latency and carrier grid reliability worldwide.
Speaker #2: We are already seeing strong early validation from real-world deployments. In Q1, one customer implemented a survey and polling agent that matched 10% conversion rate of human agents.
Tony Zhao: We are already seeing strong early validation from real-world deployments. In Q1, one customer implemented a survey and polling agent that matched 10% conversion rate of human agents. This allowed them to scale data collection and reward distribution far more cost-effectively without adding operational headcount. Overall, enterprise feedback has been highly encouraging. Customers increasingly recognize that scalable conversational AI requires not only powerful models, but also real-time infrastructures capability of delivering and seamless interaction and integration. We believe we are uniquely positioned at the intersection of these capabilities. Last month, we also strengthened our position in the enterprise collaboration market with the launch of our Intelligent Meeting Engine product. Intelligent Meeting Engine offers end-to-end encryption, flexible deployment options, including on-premises and private cloud, and a full data isolation to help ensure that customer meeting content remains entirely within their controlled infrastructure.
Speaker #2: This allowed them to scale data collection and reward distribution far more cost-effectively. Without adding operational headcounts. Overall, enterprise feedback has been highly encouraging. Customers increasingly recognize that scalable conversational AI requires not only powerful models but also real-time infrastructures capability of delivering and seamless and seamless interaction and integration.
Speaker #2: We believe we are uniquely positioned as the intersection of this capabilities. Last month, we also strengthened our position in the enterprise collaboration market with the launch of our intelligent meeting engine product.
Speaker #2: Intelligent meeting engine offers end-to-end encryption, flexible deployment options, including on-premises and private cloud, and a full data isolation to help ensure that customer meeting content remains entirely within their controlled infrastructure.
Tony Zhao: At the same time, it increased AI power capabilities such as real-time transcription, translation, intelligent meeting summaries, and automated follow-up workflows that can connect with customers' existing business system. This solution addresses growing enterprise demand around content, data sovereignty, and intelligent workflow automation, and has been well-received in industries including finance, government, and healthcare. Turning to ecosystem partnerships. We continue to integrate the latest AI models such as Google's Gemini line and xAI's Grok models into our conversational AI solutions. In particular, Google has featured Agora as a recommended partner for building real-time conversational AI, validating our technology leadership in this space. In addition, we recently entered a strategic partnership with NetEase Enterprise Service Division, NetEase Smart Enterprise. Together, we will provide integrated solutions spanning real-time video, content moderation, and AI agents. This partnership combines NetEase expertise in AI and content moderation with our leadership in real-time engagement infrastructure.
Speaker #2: At the same time, it increased AI-powered capabilities such as real-time transcription, translation, intelligent meeting summaries, and automated follow-up workflows that can connect with customers' existing business systems.
Speaker #2: This solution addresses growing enterprise demand around contents, data sovereignty, and intelligent workflow automation, and has been well received in industries including finance, government, and healthcare.
Speaker #2: Turning to ecosystem partnerships, we continue to integrate the latest AI models such as Google's Gemini Live and XAI Squawk models into our conversational AI solutions.
Speaker #2: In particular, Google has featured Agora as a recommended partner for building real-time conversational AI. Validating our technology leadership in this space. In addition, we recently entered a strategic partnership with NetEase Enterprise Service Division.
Speaker #2: NetEase Smart Enterprise. Today, together, we will provide integrated solutions spanning real-time video, content moderation, and AI agents. This partnership combines NetEase expertise in AI and content moderation with our leadership in real-time engagement infrastructure.
Tony Zhao: We believe this partnership is meaningful validation of our technology from one of China's leading Internet companies, while also expanding our go-to-market opportunities across education, customer service, digital entertainment, and enterprise collaboration. Before I conclude, I want to thank the Agora and Xunlong teams for their continued dedication and execution, and thank our shareholders for their ongoing trust and support. Globally, conversational AI is rapidly moving from proof of concept to large-scale deployment. Since the official launch of our Conversational AI Engine product last year, usage has demonstrated remarkable momentum, with over 160% sequential growth every single quarter. Enterprises today are no longer asking whether they should adopt conversational AI. Instead, they are asking how to deploy it at scale with reliability, low latency, and seamless integration. We believe our decade of experience in Real-Time Engagement infrastructure uniquely position us to help customers solve exactly these challenges.
Speaker #2: We believe this partnership is meaningful allegation of our technology from one of China's leading internet companies. While also expanding our go-to-market opportunities across education, customer service, digital entertainment, and enterprise collaboration.
Speaker #2: Before I conclude, I want to send Agora and Shenwang teams for their continued dedication and execution. And thank our shareholders for their ongoing trust and support.
Speaker #2: Globally, conversational AI is rapidly moving from proof of concept to large-scale deployment. Since the official launch of our conversational AI engine product last year, usage has demonstrated remarkable momentum.
Speaker #2: With over 150% sequential growth every single quarter, enterprises today are no longer asking whether they should adopt conversational AI. Instead, they are asking how to deploy it at scale with reliability, low latency, and seamless integration.
Speaker #2: We believe our decade of experience in real-time engagement infrastructure uniquely positions us to help customers solve exactly this challenge. With that, let me turn things over to Jinwoo, who will reveal our financial results.
Tony Zhao: With that, let me turn things over to Jingbo, who will reveal our financial results.
Speaker #3: Thank you, Tony. Hello, everyone. Let me start by first reviewing financial results for the first quarter of 2026. Then I will discuss outlook for the second quarter.
Jingbo Wang: Thank you, Tony. Hello, everyone. Let me start by first reviewing financial results for Q1 of 2026. I will discuss outlook for Q2. Starting this quarter, we have simplified our disclosure approach for revenues and active customers, and we will no longer separately disclose these metrics for Agora and Shengwang. We've also refined our dollar-based net retention rate or DBANR methodology. We now compare quarterly revenue from the same cohort of paying customers year over year to calculate DBANR. This change aligns DBANR more closely with our quarterly revenue growth rate, making it easier for investors to compare the two. Total revenue for Q1 reached $37.7 million, representing 13.5% year-over-year growth.
Speaker #3: Starting this quarter, we have simplified our disclosure approach for revenues and active customers. And we will no longer separately disclose these metrics for Agora and Shenwang.
Speaker #3: We've also refined our dollar-based net retention rate, or DBNER, methodology. We now compare quarterly revenue from the same cohort of paying customers year over year to calculate DBNER.
Speaker #3: This change aligns DBNER more closely with our quarterly revenue growth rate making it easier for investors to compare the two. Total revenue for the first quarter reached $37.7 million representing 13.5% year-over-year growth.
Jingbo Wang: This result exceeded the high end of our guidance range of $36 to $37 million, and reflected continued expansion and usage growth of our real-time engagement services in sectors such as US live shopping, social and entertainment, and financial services. DBANR Q1 was 99%, compared to 95% in Q1 of 2025. Gross profit, Q1 was $23.9 million, representing a 5.7% year-over-year increase. Gross margin was 63.4%, compared to 68% in the same period last year, mainly due to product mix change, especially conversational AI products remaining at a subscale stage. Turning to expenses. R&D expenses were $14.4 million in Q1, up 2.9% year-over-year. R&D expenses accounted for 38.1% of total revenues, compared to 42.1% in the same period last year. The increase was primarily due to continued investment in conversational AI products. The marketing expenses were $5.9 million in Q1, down 4.8% year-over-year.
Speaker #3: This result exceeded the high end of our guidance range of $36 to $37 million. And reflected continued expansion and usage growth of our real-time engagement services in sectors such as US live shopping, social and entertainment, and financial services.
Speaker #3: DBNER for this quarter was 99% compared to 95% in the first quarter of 2025. Gross profit for this quarter was $23.9 million. Representing a 5.7% year-over-year increase.
Speaker #3: Gross margin was $63.4% compared to $68% in the same period last year. Mainly due to product mix change especially conversational AI products remaining as a sub-scale stage.
Speaker #3: Turning to expenses, R&D expenses were $14.4 million in Q1. Up 2.9% year over year. R&D expenses accounted for $38.1% of total revenues compared to $42.1% in the same period last year.
Speaker #3: The increase was primarily due to continued investment in conversational AI products. So the marketing census was $5.9 million in Q1 down 4.8% year over year.
Speaker #3: So the marketing census represented $15.6% of total revenues in the quarter. Compared to $18.7% in Q1 last year. The decrease was primarily due to this planned expense management including lower personnel and promotion expenses.
Jingbo Wang: The marketing expenses represented 15.6% of total revenues in the quarter, compared to 18.7% in Q1 last year. The decrease was primarily due to disciplined expense management, including lower personnel and promotion expenses. General and administrative expenses were $6 million in Q1, down 3.4% year-over-year. G&A expenses represented 15.9% of total revenues, compared to 18.8% in Q1 last year. The decrease was primarily due to a lower allowance for current expected credit losses, mainly as a result of improved customer credit conditions and collection outcomes. Moving on to the bottom line. We delivered net income of $1.1 million in Q1, more than double the net income in Q1 last year, representing a 2.9% net income margin. This marks our sixth consecutive quarter of GAAP profitability and reflects continued improvement in our operating leverage. Now turning to cash flow.
Speaker #3: General and administrative expenses were $6 million in Q1 down 3.4% year over year. G&A expenses represented $15.9% of total revenues compared to $18.8% in Q1 last year.
Speaker #3: The decrease was primarily due to a lower allowance for current expected credit losses mainly as a result of improved customer credit conditions and collection outcomes.
Speaker #3: Moving on to the bottom line, we delivered net income of $1.1 million in Q1 more than double the net income in the first quarter last year.
Speaker #3: Representing a 2.9% net income margin. This marks a sixth consecutive quarter of gap profitability and reflects continued improvement in our operating leverage. Now turning to cash flow.
Speaker #3: Operating cash flow was $5.7 million in Q1. Including interest received of $4.3 million. Compared to $17.6 million in Q1 last year, which included interest received of $17.8 million.
Jingbo Wang: Operating cash flow was $5.7 million in Q1, including interest received of $4.3 million, compared to $17.6 million in Q1 last year, which included interest received of $17.8 million. Moving on to balance sheet. We ended Q1 with $366.1 million in cash equivalents and deposits, and financial products issued by banks. Net cash outflow in the quarter was mainly due to share repurchase. During the quarter, we repurchased approximately 12.5 million Class A ordinary shares or 3.1 million ADS, representing approximately 3.6% of our total outstanding shares at the beginning of the quarter, for approximately $13.1 million. As of 31 March 2026, we have repurchased 174.7 million Class A ordinary shares or 743.7 million ADS for approximately $156.2 million under our share repurchase program, which represented 78.1% of our $200 million share repurchase program. The current program will expire at the end of February 2027. Now turning to guidance.
Speaker #3: Moving on to balance sheet, we ended Q1 with $366.1 million in cash. Cash equivalents and deposits and financial products issued by banks. Net cash outflow in the quarter was mainly due to share repurchase.
Speaker #3: During the quarter, we repurchased approximately $12.5 million class A ordinary shares for $3.1 million ADS. Representing approximately $3.6% of our total outstanding shares. That's the beginning of the quarter.
Speaker #3: For approximately $13.1 million. As of March 31st, 2026, we had repurchased $174.7 million class A ordinary shares or $43.7 million ADS. For approximately $156.2 million under our share repurchase program.
Speaker #3: Which represented $78.1% of a $200 million share repurchase program. The current program will expire at the end of February 2027. Now turning to guidance.
Speaker #3: Based on currently available information, we expect total revenues for the second quarter of 2026 to be between $39 and $40 million. Compared to $34.3 million in the second quarter of 2025.
Jingbo Wang: Based on currently available information, we expect total revenues for Q2 2026 to be between $39 and $40 million, compared to $34.3 million in Q2 2025, representing year-over-year growth of 13.7% to 16.6%. Notably, even at the low end of this range, we expect to deliver faster revenue growth than we did in Q1. In closing, I want to thank our teams for their focused execution in Q1. We beat revenue guidance and net income more than doubled year-over-year. Our Q2 outlook also points to a further acceleration in revenue growth. We will continue to invest in AI with discipline, and we're confident that it will become an increasingly important driver of long-term growth. Thank you all for joining today's call. Let's open it up for questions.
Speaker #3: Representing year over year growth of $13.7 to $16.6%. Notably, even as a low end of this range, we expect to deliver faster revenue growth than we did in the first quarter.
Speaker #3: In closing, I want to thank our teams for their focused execution in the first quarter. We beat revenue guidance and net income more than doubled year over year.
Speaker #3: Our second quarter outlook also points to a further acceleration in revenue growth. We will continue to invest in AI with discipline. And we are confident that it will become increasingly important driver of long-term growth.
Speaker #3: Thank you all for joining today's call. Let's open it up for questions.
Speaker #1: Thank you, as a reminder to ask a question, please press star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 11 again.
Operator: Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. Please stand by as we compile the Q&A roster. First question comes from the line of Harry Zhou from Bank of America Securities. Please go ahead.
Speaker #1: Please stand by if you compile the Q&A roster. First question comes from the line of Harry Zhao from Bank of America Securities. Please go ahead.
Harry Zhou: Hi. Thanks management for taking my questions, and congratulations on the strong Q1 results and solid Q2 guidance. I have three questions here. The first one, since the company did not disclose the revenue breakdowns by region. We would like to know the growth trend in overseas and China market, and what are the verticals driving the growth behind? Secondly, in terms of the conversational AI, we would like to know the primary application scenarios at current stage, and what revenue scale could the company achieve by the end of 2024? Thirdly, it's about the profit guidance. What is the operating profit target for 2026 and any timeline for operating level breakeven? Thank you.
Speaker #4: Hi. Thanks for mentioning from taking my questions. And congratulations on the strong post-quarter results and solid two-quarter guidance. I have three questions here. The first one, since the company did not disclose the breakdowns by region, so we would like to know the growth trend in overseas and China market.
Speaker #4: And what are the verticals driving the growth behind? And secondly, in terms of the conversational AI, we would like to know the primary application scenarios at the current stage and what revenue scale could the company achieve by the end of this year.
Speaker #4: And thirdly, it's about the profit guidance. What is the operating profit target for '26? And any timeline for operating level breakeven? Thank you.
Jingbo Wang: Thank you. On the first question, first of all, in this quarter, both the China business and the US international business are growing very rapidly. The growth rate, the US business is still a little bit faster, but the two are approaching both at very healthy rates. In terms of the demand in both markets, I'll talk about the demand in the RTE market first, and Tony will talk about demand in the AI market. For RTE in China, demand for the traditional verticals, social, entertainment, education, from all these verticals, demand continued to recover. In the US and international markets, demand from live shopping, financial services, and gaming use cases are among the strongest. We have a very healthy pipeline of new customers in these verticals as well. Overall, RTE demand looks quite healthy.
Speaker #5: Thank you. On the first question, first of all, in this quarter, both the China business and the US international business are growing very rapidly.
Speaker #5: So the growth rate the US business still is still a little bit faster. But the two are approaching both at very healthy rates. So in terms of the demand, in both markets, I'll talk about the demand in the RTE market first.
Speaker #5: And Tony, we'll talk about demand in the AI market. So for RTE in China, demand from a traditional vertical, social entertainment, education, from all these verticals, demand continues to recover.
Speaker #5: And in the US international markets, demand from live shopping, financial services, and gaming use cases are among the strongest. And we have a very healthy pipeline of new customers in these verticals as well.
Speaker #5: So overall, RTE demand looks quite healthy.
Tony Zhao: About the demand on AI side. From the beginning of this closely watching the progress on all front. We were the first to introduce AI into the whole RTE technology stack and offer the first generation of products empowered by those capabilities. Since then, we've been closely working with customers on practical demand. The thing is, in the last few years, there has been a lot of hype around how AI can change people's lives. Those claims are not fake, but many of those claims are overstatements that far ahead of what's happening on the ground, mostly oversimplifying the practical challenge and actual adoption process. Since early last year, we've been seeing demand from call center, education, digital avatar, et cetera. I think we talked about that last year. This is happening over the past few quarters, in different regions.
Speaker #6: About the demand on AI side, from the beginning of this closely watching the progress on all fronts, we were the first to introduce AI into the whole RTE technology stack and offer the first generation of products empowered by those capabilities.
Speaker #6: Since then, we've been closely working with customers on practical demand. The thing is, in the last few years, there has been a lot of hype around how AI can change people's lives and those claims are not fake.
Speaker #6: But many of those claims are overstatements that far ahead of what's happening on the ground. Mostly oversimplify the practical challenge and actual adoption process.
Speaker #6: Since early last year, we've been seeing demand from call center education, digital avatar, etc. I think we talked about that last year. This is happening over the past few quarters.
Speaker #6: In different regions, in each of those areas, we had we actually had certain partners and customers to work with them to grow into real production.
Tony Zhao: In each of those areas, we actually have certain partners and customers to work with them to go into real production. With them, we make progress in the overall experience, practical token economy, and customer use case adoption. At this moment, we see fairly large demand from the call center side, as the technology of voice agent is increasingly able to communicate and resolve many communication tasks. Leveraging large language model intelligence is improving day by day. On IoT side, after successfully helping to launch the companion toy, Fuzozo, similar demand is expanding. Fuzozo's growth itself is also very promising. It can get enough monthly subscription revenue from the most sticky user group every month. It's not just a one-time sale of the hardware toy. We're seeing a similar trend in other use cases of conversational AI.
Speaker #6: With them, we made progress in the overall experience, practical token economy, and customer use case adoption. At this moment, we see fairly large demand from the call center side.
Speaker #6: As the technology of voice agent is increasingly able to communicate and resolve many communication tasks, leveraging large language model intelligence, it's improving day by day.
Speaker #6: On IoT side, after the successfully helping after successfully helping to launch the companion toy for Zuzu, similar demand is expanding. For Zuzu's growth itself is also very promising.
Speaker #6: It can get enough monthly subscription revenue from the most sticky user group every month. So it's not just a one-time sale of the hardware toy.
Speaker #6: We're seeing a similar trend in other use cases of conversational AI.
Speaker #5: Yeah. So Tony, just talk about the demand for conversational AI so that I can also answer partly the second question. So yes, for revenue contribution this year, we believe call center and IoT will be the biggest contributors.
Jingbo Wang: Yeah. Tony just talked about the demand for conversational AI. Actually, that's also answered partly the second question. Yes, for revenue contribution 2024, we believe call center and IoT will be the biggest contributors. I think Tony also talked about that in his opening remarks that since we released our Conversational AI Engine product in March 2023, its usage has been growing at more than 150% sequential growth rate every single quarter. Also the revenue contribution at the moment is still relatively low. We expect to see its revenue to quickly ramp up and towards the summer around 5% revenue contribution by then. In terms of the 2026 operating target, given the current growth trajectory and the seasonality, we expect operating income and net income to both grow sequentially every quarter from Q1 to Q4.
Speaker #5: And I think Tony also talked about that in his opening remarks that since we released our conversational AI engine product in March last year, its usage has been growing at more than 150% sequential growth rate every single quarter.
Speaker #5: So also the revenue contribution at the moment is still relatively low. We expect to see its revenue to quickly ramp up and towards the summer around 5% revenue contribution by then.
Speaker #5: So in terms of the 2026 operating target, so given the current growth trajectory and the seasonality, we expect operating income and net income to both grow sequentially every quarter from Q1 to Q4.
Speaker #5: And in terms of the full year, profit we expect the gap net income will be significantly higher than last year. And our goal is to achieve gap operating profit.
Jingbo Wang: In term of the full year profit, we expect the GAAP net income will be significantly higher than last year. Our goal is to achieve GAAP operating profit in H2 of this year.
Speaker #5: In the second half of the second half of this year.
Harry Zhou: Thanks, management. Very clear. Thank you.
Speaker #6: Thanks, Benjamin. Very clear. Thank you.
Speaker #1: Thank you. Just a moment for our next question, please. Next, we have Rachel Han from CICC. Please go ahead.
Operator: Thank you. Just a moment for our next question, please. Next, we have Rachel Han from CICC. Please go ahead.
Speaker #7: I think hi. This is Rihan. Rachel from CICC. Thanks for taking my questions. And congrats on another solid quarter. Especially with revenue coming above the high end of guidance.
Rachel Han: Thanks. Hi, this is Rachel Han from CICC. Thanks for taking my questions, congrats on another strong quarter, especially with revenue coming above the high end of guidance. My first question is on e-commerce overseas last quarter. I remember you highlighted Whatnot and the Super Bowl live shopping events. Could you give us an update on how this vertical has been developing since then? How should we think about the potential revenue contribution from overseas e-commerce for the rest of 2026? My second question is on domestic China business. I know we share some color on the growth drivers for the domestic business this year, I noticed we announced a NetEase Smart Enterprise partnership this quarter. How should we think about its potential impact on our Shengwang growth in 2026? Thank you.
Speaker #7: My first question is on e-commerce overseas. Last quarter, I remember you highlighted what not and the Super Bowl live shopping events. So could you give us an update on how this vertical has been developing since then?
Speaker #7: And how should we think about the potential revenue contribution from overseas e-commerce for the rest of 2026? My second question is on domestic China business.
Speaker #7: I know we shared some color on the growth drivers for the domestic business this year. But I noticed we announced net e-smart enterprise partnership this quarter.
Speaker #7: So how should we think about its potential impact on our Xunwang's growth in 2026? Thank you.
Speaker #5: Sure. So the first question on e-commerce use case. So I want to say that in the US market and in probably all developed markets in general, video-based live shopping is still a very new thing.
Jingbo Wang: Sure. The first question on commerce use case. I want to say that in the US market and in probably all developed markets in general, video-based live shopping is still a very new thing. We mentioned one last quarter. After that event, very successful event, actually it did perform well in terms of new user acquisition and customer user stickiness. We continue to see growing demand from that customer. In addition, we recently won over another fast-growing video-based e-commerce customer in the US market from a competitor. On top of that, in the last quarter was announced in the industry. Now everybody in the industry is watching, and several other players are trying to host similar events in the future, and we are discussing with a few of them already.
Speaker #5: So we mentioned one last quarter. So after that event, very successful event, actually the one of the in terms of user acquisition and customer user stickiness.
Speaker #5: So we continuously see growing demand from that customer. In addition, we recently won over another fast-growing video-based e-commerce customer. In the US market from a competitor.
Speaker #5: And on top of that, the last quarter was a milestone in the industry. So now everybody in the industry is watching. And several other players are trying to host similar events in the future.
Speaker #5: And we are discussing with a few of them. Already. So we do expect this vertical to have a lot of room for growth. And we are making solid progress on that front.
Jingbo Wang: We do expect this vertical to have a lot of room for growth, and we are making solid progress on that front. In terms of the business in China, as I said earlier, demand from these internet-based use cases, social entertainment, education, we see demand recovery also stay at a moderate rate and also from verticals such as IoT, cameras, doorbells, cars, and from wearable devices. Demand from IoT is growing very fast. It has been very fast in the past 2, 3 years. Also digital transformation customers with additional AI features. We also see renewed demand growth from digital transformation traditional enterprise customers. In terms of the price, I think it's certainly very helpful on its own, but also it reflected further consolidation of the RTE market in China.
Speaker #5: So in terms of the business in China, as I said, earlier, right, demand from these internet-based use cases, social entertainment, education, we see demand recovery also still at a moderate rate.
Speaker #5: And also from verticals such as IoT, cameras, right, doorbells, cars, right, from wearable devices. Demand from IoT is going very fast. It has been very fast in the past two, three years.
Speaker #5: And also digital transformation customers. With additional AI features, right, we also see renewed demand growth from digital transformation. Traditional enterprise customers. In terms of the 90s, I think it's certainly very helpful in its on its own, but also it reflects the further reflects a further consolidation of the RTE market in China, right?
Jingbo Wang: Recently, to just give some more examples, recently, a private competitor in this market repurchased all of its venture capital investments and started to focus more on profitability rather than scale. Right? That is used to be a competitor, now it is a partner. We also see another large public cloud competitor has further reduced its staff on the RTE business. We do believe this trend of consolidation will gradually help our revenue growth as well.
Speaker #5: So recently, just give some more examples, right? Just recently, a private competitor in this market repurchased all of its venture capital investors and started to focus more on profitability rather than scale, right?
Speaker #5: And that is used to be a competitor. Now it's a partner. And we also see another cloud large public cloud competitor has further reduced its staff on the RTE business.
Speaker #5: So we do believe this trend of easing this trend of consolidation will gradually help our revenue growth as well.
Speaker #7: Okay. Thanks, Jingguo. That's very helpful. And hope all the best going forward. Thanks.
Rachel Han: Okay, thanks, Pinbo. That's very helpful. All the best going forward. Thanks.
Speaker #1: Thank you. Just a moment for our next question, please. Last question comes from Yuxiu from China Securities. Please go ahead.
Operator: Thank you. Just a moment for our next question, please. Last question comes from Yu Xing from China Securities. Please go ahead.
Yu Xing: Hi, management. Thanks for taking my question. Congrats on the strong results. Just two quick ones. First, are we seeing further improvement in the domestic competitive landscape, and how should that translate into pricing power and revenue growth? Also excluding the initial gross margin drag from Coco AI, what is the online gross margin trend for our core business? Second question, as for Coco AI, how are its unit economics trending? If AI progression comes in below expectations, how should we think about our target operating margin positive by Q4 of 2026?
Speaker #6: Hi there, Jingguo. Thanks for taking my question and congrats on this one. Just two quick ones. First, are we seeing further improvements in the domestic competitive landscape?
Speaker #6: And how should that translate into client power and revenue growth? Also, excluding the initial growth margin drag from AI, what is the underlying growth margin trend for our core business?
Speaker #6: Second question, as the AI scale is hard, it's unique economic spending. If AI is progressing below expectations, how should we think about the target of turning OP margin positive by Q4 of 2026?
Jingbo Wang: Sure. First question on competition and the margin. I will talk about RT and Tony will talk about AI. Actually, I just talk a little bit about the competition in the China market. We see that the market is moving to further consolidation. Probably more players to no longer going after scale. We do believe that will help with revenue growth as well as margin improvement in the coming quarters. As you can see, overall, the gross margin this quarter was compared to the same quarter last year. That's mostly due to the initial negative gross margin of the conversational AI business. If we exclude the conversational AI gross margin of the core RT businesses remain actually relatively stable in the Q1.
Speaker #5: Sure. So first question on competition and the margin. So I will talk about RTE and Tony will talk about AI. So actually, I just talked about a little bit about the competition in the China market.
Speaker #5: We see that the market is moving further consolidation with more players to no longer going after scale, right? So we do believe that will help with revenue growth as well as margin improvement in the coming quarters.
Speaker #5: So as you can see, overall, the gross margin in this quarter was a few compared to the same quarter last year. But that's mostly due to the initial negative gross margin of the conversational AI business.
Speaker #5: If excluding conversational AI, the gross margin of the core RTE businesses remained actually relatively stable. In the first quarter.
Speaker #6: And on the AI side, there's a lot of competition for conversational AI in Silicon Valley and the US market. The market is still at the early stage.
Tony Zhao: On the AI side, there's a lot of competition for conversational AI in Silicon Valley and the US market. The market is still at the early stage, and there are different players trying to attack it from quite diverse angles. Because it's still a growth market, every company has a chance to attack from different angle and is still making progress. We are the ones who focus more on the fundamental technology, trying to enable the most promising use cases through the ultimate quality of conversation. The customer demand is strong. As we see, the status is actually adapting to those customer demands and improving the conversational quality so that it can resolve communication tasks at a higher and better level, making it more effective. China market is quite different.
Speaker #6: And there are different players trying to attack it from quite diverse angles. Because it's still a growth market, so every company has a chance to attack from different angles and still making progress.
Speaker #6: We have one who focused more on the fundamental technology, trying to enable the most promising use cases through the ultimate quality of conversation. The customer demand is strong.
Speaker #6: As we see, the status is actually adapting to those customer demands and improving the conversational quality so that it can resolve communication tasks at a higher and better level, making it more effective.
Speaker #6: China market is quite different. As you can see, most of the AI companies can only make a frictional of revenue in China market compared to their US peers.
Tony Zhao: As you can see, most of the AI companies can only make a fractional of revenue in China market compared to their US peers. The market is quite hard to get through at this moment. However, there is similar demand on conversational AI side, and the technology and product progress are also similar.
Speaker #6: The market is quite hard to get true at this moment. However, there is similar demand on conversational AI side. And the technology and the product progress are also similar.
Speaker #5: Okay. So yeah. So in terms of the unique economics of the conversational AI product, I think it is still too early to talk about UE.
Jingbo Wang: Okay. In terms of the unit economics of the conversational AI product, I think it is still too early to talk about. For example, in Q1, the reason we have a negative gross margin for this product is because we have a lot of POC customers, a lot of experimentation that basically generated no revenue but had a lot of cost. We believe as we continue to scale, as customers move from POC to deployment and scale usage by the end of the year, we expect to see a meaningful revenue contribution. At that point, the gross margin will certainly turn positive and also will be at a healthy level.
Speaker #5: For example, in the first quarter, the reason we had a negative gross margin for this product is because we have a lot of POC customers.
Speaker #5: A lot of experimentation. That basically generates no revenue, but has a lot of cost. So we believe as we continue to scale, as customers move from POC to deployment and scale usage, by the end of the year, we expect to see meaningful revenue contribution and at that point, the gross margin will certainly turn positive and also will be at a healthy level.
Speaker #5: In the long run, we actually expect the conversational AI business to generate similar if not higher gross margin than the current RTE products. Because of it, one higher pricing and to the more technical sophistication and value creation for customers.
Jingbo Wang: In the long run, we actually expect the conversational AI business to generate similar, if not higher gross margin than the current RTE products because of, one, higher pricing, and two, the more technical sophistication and value creation for customers. We talk about if the AI progress is below, but not meeting expectation. Actually, we have considered all the investments we need to make on that front, and it will not affect our goal of turning operating profitability in H2 of this year.
Speaker #5: So we talk about if the AI progress is below does not meet the expectation, but we actually have considered all the investments we need to make on that front.
Speaker #5: And it will not affect our goal of turning operating profitability in the second half of this year.
Speaker #6: Thank you.
Tony Zhao: Thank you.
Speaker #1: Thank you. As a reminder, to ask a question, please press star, one, one, on your telephone and wait for your name to be announced.
Operator: Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. Thank you. With that, this concludes today's Q&A session and conference call. Thank you again, everyone, for attending the company's call today. As a reminder, the recording and the earnings release will be available on the company's website at investor.agora.io. If there's any further questions, please feel free to email the company. Thank you.
Speaker #1: Thank you. With that, this concludes today's Q&A session and conference call. Thank you again, everyone, for attending the company's call today. As a reminder, the recording and the earning release will be available on the company's website at investor.agora.io.
