Q2 2026 Agora Inc Earnings Call

August 14, 2026

Operator: Good day, and thank you for standing by. Welcome to the Agora, Inc. second quarter 2026 financial results conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during this 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 CFO.

Speaker #1: After the speaker's presentation, there will be a question-and-answer session. To ask a question during this session, you will need to press star 11 on your telephone.

Speaker #1: You will then hear an automated message advising that your hand is raised. To withdraw your question, please press star 11 again. Please be advised that today's conference is being recorded.

Speaker #1: 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.

Speaker #1: Joining me today are Tony Zhao, Founder, Chairman, and CEO; and Jing Bo Weng, the Company CFO. During this call, the Company will make forward-looking statements about its future financial performance and other future events and trends.

Operator: 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 we based on what the company believes today, and actual results may differ materially. 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 in which the company discussed in detail in its filings with the SEC, including today's press release and the risk factors of other information contained in the final prospectus relating to the initial public offering. Agora, Inc. remains no obligation to update any forward-looking statements the company may make on today's call. With that, let me turn the call over to Tony. Hi, Tony.

Speaker #1: These statements are only predictions that we base on what the company believes today, and actual results may differ materially. 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 which the company discusses in detail in its filings with the SEC.

Speaker #1: Including today's press release and the risk factors or other information contained in the final prospectus relating to the initial public offering, Agora, Inc. assumes no obligation to update any forward-looking statements the company may make on today's call.

Speaker #1: With that, let me turn the call over to Tony. Hi, Tony.

Tony Zhao: Hey, thank you, operator, and welcome everyone to our earnings call. Let me begin with a review of our operating results for the quarter. I am pleased to report another quarter of accelerating top-line growth, as well as our seventh consecutive quarter of GAAP profitability. Total revenues for the second quarter of 2026 reached $40.4 million, an increase of 18% year over year. This performance reflects both the continued strength of our core real-time engagement business and the growing contribution from our conversational AI products as more customers move from proof of concept to commercial production. Our GAAP net profit for the quarter was $2.2 million, up 50% year over year, which demonstrates improved operating leverage and disciplined cost management across the organization. Our most important progress this quarter occurred in call center across the globe.

Speaker #2: Hey, thanks, all, for being here. And welcome, everyone, to our earnings call. Let me begin with a review of our operating results for the quarter.

Speaker #2: I'm pleased to report another quarter of strong top-line growth, as well as our seventh consecutive quarter of GAAP profitability. Total revenues for the second quarter of 2026 reached $40.4 million, an increase of 18% year over year.

Speaker #2: This performance reflects both the continued strength of our core real-time engagement business and the growing contribution from our conversational AI product, as more customers move from proof of concept to commercial production.

Speaker #2: Our GAAP net profit for the quarter was $2.2 million, up 50% year over year, which demonstrates improved operating leverage and disciplined cost management across the organization.

Speaker #2: Our most important progress this quarter occurred in cost centers across the globe. We are seeing strong momentum in adoption of our voice AI agents.

Tony Zhao: We are seeing strong momentum in adoption of our Voice AI agents. Trained on the best sales and customer service playbooks, these agents deliver consistent, high-quality performance across every conversation. They do not experience fatigue, lose focus, or vary in performance based on workload or time of day. They also maintain calm and steady interactions, even during challenging calls. Further, customers are now seeing substantial cost savings from deploying our Voice AI agents. Indeed, we are beginning to see them match or even surpass human performance in an increasing number of tasks in achieving targeted business outcomes. The first example is outbound marketing and buyer interest capture. Our Voice AI agents are now being used to initiate calls, qualifying leads, collect information, and schedule meetings with prospect customers.

Speaker #2: Trained on the best sales and customer service playbooks, these agents deliver consistent, high-quality performance across every conversation. They do not experience fatigue, lose focus, or vary in performance based on workload or time of day.

Speaker #2: They also maintain timing and steady interactions, even during challenging calls. Furthermore, customers are now seeing substantial cost savings from deploying our voice AI agents.

Speaker #2: Indeed, we're beginning to see them match or even surpass human performance in an increasing number of tasks in achieving target business outcomes. The first example is outbound marketing and buyer interest capture.

Speaker #2: Our voice AI agents are now being used to initiate calls, qualify leads, collect information, and schedule meetings with prospective customers. At a similar conversion rate to human reps, our voice AI agent also outperformed in two other important areas.

Tony Zhao: At a similar conversion rate with human reps, our Voice AI agent also outperform in two other important areas: the volume of calls they can handle and the unit economics they deliver. The second example is market survey. Our Voice AI agent can conduct in-depth interviews for consumer insights and product feedbacks while capturing structured data throughout each conversation. The high concurrency of our solution compresses the time it takes to conduct large-scale surveys that traditionally takes weeks or days into just a few hours. Marketing and surveying are only two examples of how Voice AI agents can reshape call center worldwide. We see similar opportunities in financial services outreach, gaming user acquisition and retention, debt collection, and many other areas. We are already working with customers across these sectors, and we expect several of them to move from proof of concept to large-scale deployment in the coming quarters.

Speaker #2: The volume of calls they can handle and the unit economics they deliver. The second example is marketing service. Our voice AI agent can conduct in-depth interviews for consumer insights and product feedback.

Speaker #2: While capturing structured data throughout each conversation, the high concurrency of our solution compresses the time it takes to conduct large-scale surveys that traditionally take weeks or days into just a few hours.

Speaker #2: Marketing and serving are only two examples of how voice AI agents can reshape cost centers worldwide. We see similar opportunities in financial services outreach, gaming user acquisition and retention, data collection, and many other areas.

Speaker #2: We are already working with customers across this sector, and we expect several of them to move from proof of concept to large-scale deployment in the coming quarters.

Tony Zhao: At the same time, we continue to invest in our developer ecosystem. This quarter, we launched Agora Skills and Agora CLI. Agora Skills package our platform knowledge so that AI coding assistants, including Claude Code, Cursor, or Codex, can work with our latest SDKs and best practices when building real-time engagement or conversational AI applications. The Agora CLI complements this with a simple command line interface for coding agents to do their work. Together, these tools make it easier for both human developers and AI coding agents to build and deploy real-time engagement applications with us. We are also continuing to strengthen our technology ecosystem through strategic partnerships. This quarter, we announced a partnership with Gradient, a leading Voice AI platform recently founded by the research team behind Moshi and Tibiki, two speech models with strong recognition in the open source community.

Speaker #2: At the same time, we continue to invest in our developer ecosystem. This quarter, we launched Agora Skills and the Agora CRI. Agora Skills packages our platform knowledge so that AI coding assistants—including Cloud Code, Cursor, or Codex—can work with our latest SDKs and best practices when building real-time engagement or conversational AI applications.

Speaker #2: The Agora CRI complements this with a simple command-line interface for coding agents to do their work. Together, these tools make it easier for both human developers and AI coding agents to build and deploy real-time engagement applications with us.

Speaker #2: We're also continuing to strengthen our technology ecosystem through strategic partnerships. This quarter, we announced a partnership with Gravium, a leading voice AI platform recently founded by the research team behind Mushi and Hibiki.

Speaker #2: Two speech models with strong recognition in the open-source community. Through our partnership, developers can enable Gravium TTS within our conversational AI engine through a simple configuration, without introducing additional latency hops.

Tony Zhao: Through our partnership, developers can enable Gradient TDFs within our conversational AI engine through a simple configuration without introducing additional latency hops. Looking ahead, we will first remain laser-focused on accelerating the transition of our conversational AI solutions from pilot to production across use cases. Each use case will present its own set of challenges, but each will also help us refine our technology. We believe that continued improvements in our solutions will unlock additional demand and drive industry shift towards AI-led workflows in call centers. Second, we will continue to invest in our real-time infrastructure. Our software-defined real-time network, or SDRTN, has long been a foundational advantage for us. As we expand into human-to-AI interactions, the importance of this infrastructure does not diminish. On the contrary, it becomes more critical, because smooth conversations require ultra-low latency inference and transmission.

Speaker #2: Looking ahead, we will first remain focused on accelerating the transition of our conversational AI solutions from pilot to production across use cases. Each use case will present its own set of challenges, but each will also help us refine our technology.

Speaker #2: We believe that continued improvements in our solutions will unlock additional demand and drive industry shift towards AI-led workflows in cost centers. Second, we will continue to invest in our real-time infrastructure.

Speaker #2: Our software-defined real-time network, or SDRTN, has long been a foundational advantage for us. As we expand into human-to-AI interactions, the importance of this infrastructure does not diminish.

Speaker #2: On the contrary, it becomes more critical, because smooth conversations require ultra-low latency inference and transmission. We are confident that our investment in real-time inference and communication infrastructure will serve as a decisive factor in our ability to compete and succeed in the conversational AI arena.

Tony Zhao: We are confident that our investment in real-time inference and the communication infrastructure will serve as a decisive factor in our ability to compete and succeed in the conversational AI arena. Third, we will continue to strengthen our partner ecosystem and build our developer motion. On 23 and 24 October, we will host our iconic annual conference, IRTE, or Intelligent Real-Time Engagement, in Beijing. We look forward to bringing together developers, partners, enterprises, and industry leaders to explore the next phase of real-time engagement and conversational AI. In summary, we believe the center of gravity in the AI industry is increasingly shifting from model capabilities towards infrastructure and harness layer required to operate with AI agents reliably at scale.

Speaker #2: And third, we will continue to strengthen our partner ecosystem and build up developer momentum. On October 23 and 24, we will host our iconic annual conference, IRTE—or Intelligent Real-Time Engagement—in Beijing.

Speaker #2: We look forward to bringing together developers, partners, enterprises, and industry leaders to explore the next phase of real-time engagement and conversational AI. In summary, we believe the center of gravity in the AI industry is increasingly shifting from model capabilities towards the infrastructure and harness layers required to operate voice AI agents reliably at scale.

Tony Zhao: At the intersection of real-time engagement, AI, and global infrastructure, we believe Agora is uniquely positioned to help enterprise make this transition and create sustainable long-term value for both our customers and shareholders. Before I conclude, I would like to thank our customers, developers, partners, and shareholders for their continued trust and support, and our global Agora and Shengwang teams for their dedication and innovation. With that, let me turn it over to Jingbo, who will reveal our financial results.

Speaker #2: At the intersection of real-time engagement, AI, and global infrastructure, we believe Agora is immediately positioned to help enterprise make this transition and create sustainable, long-term value for both our customers and shareholders.

Speaker #2: Before I conclude, I would like to thank our customers, developers, partners, and shareholders for their continued trust and support, and our global Agora and Shenwang teams for their dedication and innovation.

Speaker #2: With that, let me turn it over to Jinbo, who will reveal our financial results.

Jingbo Wang: Thanks, Tony. Hello, everyone. Let me start by first reviewing financial results for Q2 2026. Then I will discuss outlook for Q3. Total revenue for Q2 reached $40.4 million, above the high end of the guidance range, and representing 18% year-over-year growth. This marks our third consecutive quarter of accelerating growth, driven by continued expansion of our real-time engagement services across sectors such as e-commerce, as well as growing customer adoption of our conversational AI solutions. Our dollar-based net retention rate Q4 was 104%, compared to 94% in Q2 2025. This represents a meaningful improvement and moves us back above 100%. Gross profit Q4 was $25.7 million, representing 12.5% increase year-over-year. Gross margin was 63.7%, compared to 66.8% in the same period last year, and 63.4% in Q1 2026.

Speaker #3: Okay, thanks, Tony. Hello, everyone. Let me start by first revealing financial results for the second quarter of 2026. Then I will discuss the outlook for the third quarter.

Speaker #3: Total revenue for the second quarter reached $40.4 million, above the high end of the guidance range and representing 18% year-over-year growth. This marks a third consecutive quarter of accelerating growth, driven by continued expansion of our real-time engagement services across sectors such as e-commerce, as well as growing customer adoption of our conversational AI solutions.

Speaker #3: Dollar-based net retention rate for the fourth quarter was 104%, compared to 94% in the second quarter of 2025. This represents a meaningful improvement and moved us back above 100%.

Speaker #3: Gross profit for the fourth quarter was $25.7 million, representing a 12.5% increase year over year. Gross margin was 63.7%, compared to 66.8% in the same period last year.

Speaker #3: And 63.4% in the first quarter of 2026. On a year-over-year basis, the decline was primarily due to a product mix change, as conversational AI products continued to see growing usage during the quarter, but remained at a sub-scale stage.

Jingbo Wang: On a year-over-year basis, the decline was primarily due to product mix change, as conversational AI products continue to see growing usage during the quarter, but has remained at a subscale stage. On a sequential basis, the increase was mainly driven by technical optimization. Turning to expenses. R&D expenses were $15.4 million in Q2, up 10.2% year-over-year. R&D expenses represented 38.1% of total revenue in the quarter, compared to 40.8% in the same period last year. The increase was primarily due to our continued investment in conversational AI products. Sales and marketing expenses were $6.4 million in Q2, down 1.5% year-over-year. Sales and marketing expenses represented 15.9% of total revenues in the quarter, compared to 19% in the same period last year. The decrease was primarily due to disciplined expense management. General and administrative expenses were $5.5 million in Q2, down 9.5% year-over-year.

Speaker #3: Based on the screenshot, the increase was mainly driven by technical optimization. Hourly expenses before expenses were $15.4 million in Q2, up 10.2% year over year.

Speaker #3: Hourly expenses represented 38.1% of total revenue in the quarter, compared to 40.8% in the same period last year. The increase was primarily due to a continued investment in conversational AI products.

Speaker #3: So, the marketing census was $6.4 million in Q2, down 1.5% year over year. Sales and marketing census represented 15.9% of total revenues in the quarter.

Speaker #3: Compared to 19% in the same period last year. The decrease was primarily due to disciplined expense management. General administrative expenses were $5.5 million in Q2, down 9.5% year over year.

Speaker #3: G&A expenses represented 13.5% of total revenues in the quarter, compared to 17.6% in the same period last year. The decrease was primarily due to a lower allowance for current expected credit loss, as customer credit conditions and collection outcomes improved.

Jingbo Wang: G&A expenses represented 13.5% of total revenue in the quarter, compared to 17.6% in the same period last year. The decrease was primarily due to a lower allowance for covering expected credit loss as customer credit conditions and collection outcomes improved. Turning to operating results, we recorded GAAP operating loss of $1 million in Q2, compared to a loss of $3.1 million in the same period last year, thanks to continued improvement in operating leverage. Based on our current business momentum, our goal is to achieve quarterly GAAP operating profitability by the end of this year. Moving on to the bottom line, we delivered net income of $2.2 million in Q2, up 50.3% year-over-year, and representing a net income margin of 5.4%. Now turning to cash flow. Operating cash flow was negative $2.1 million in Q2, compared to negative $0.4 million in Q2 2025.

Speaker #3: Prior to operating results, we recorded GAAP operating loss of $1 million in the second quarter, compared to a loss of $3.1 million in the same period last year.

Speaker #3: Thanks to continued improvement in operating leverage, and based on our current business momentum, our goal is to achieve quarterly GAAP operating profitability by the end of this year.

Speaker #3: Moving on to the bottom line, we delivered net income of $2.2 million in Q2, up 15.3% year over year, and representing a net income margin of 5.4%.

Speaker #3: Now, turning to cash flow, operating cash flow was negative $2.1 million in Q2, compared to negative $0.4 million in the second quarter of 2025.

Jingbo Wang: Moving on to the balance sheet. We ended Q2 with $361.7 million in cash equivalents, bank deposits, and financial products issued by banks. The decrease in our cash balance was mainly due to annual bonus payment, as well as share repurchase during the quarter. During Q2, we repurchased approximately 1 million ADS for approximately $2.7 million. As of 30 June 2026, we had repurchased approximately 44.6 million ADS in total for approximately $159.9 million under the current share repurchase program. As of 30 June 2026, we had 83.8 million ADS outstanding, compared to 87.3 million ADS at the end of 2025. The current share repurchase program will expire at the end of February 2027. Now turning to guidance. Based on currently available information, we expect total revenue for Q3 2026 to be between $41 and $42 million, representing year-over-year growth of 15.8% to 18.6%.

Speaker #3: Moving on to the balance sheet, we ended Q2 with $361.7 million in cash, cash equivalents, bank deposits, and financial products issued by banks. The decrease in our cash balance was mainly due to the annual bonus payment, as well as share purchases during the quarter.

Speaker #3: During Q2, we repurchased approximately 1 million ADS for about $3.7 million. As of June 30, 2026, we had repurchased approximately 44.6 million ADS in total, for about $159.9 million under the current share repurchase program.

Speaker #3: As of June 30, 2026, we had 83.8 million ADS outstanding, compared to 87.3 million ADS at the end of 2025. The current share repurchase program will expire at the end of February 2027.

Speaker #3: Now, turning to guidance—based on currently available information, we expect total revenue for the third quarter of 2026 to be between $41 million and $42 million.

Speaker #3: Representing year-over-year growth of 15.8% to 18.6%. This outlook reflects our current and preliminary views on the market and operational conditions, which are subject to change.

Jingbo Wang: This outlook reflects our current and preliminary views on the market and operational conditions, which are subject to change. In closing, this was another strong quarter for us, both in terms of revenue growth and profitability. At the same time, we are increasingly encouraged by the usage momentum and commercial potential in conversational AI, and we will continue to invest with discipline to support our long-term growth. Thank you all for joining today's call. Let's open it up for questions.

Speaker #3: In closing, this was another strong quarter for us, both in terms of revenue growth and profitability. At the same time, I am increasingly encouraged by the usage momentum and commercial potential in conversational AI, and we will continue to invest with discipline to support our long-term growth.

Speaker #3: Thank you all for joining today's call. Let's open it up for questions.

Operator: Thank you. As a reminder, to ask a question, please press *11 on your telephone and wait for your name to be announced. To withdraw your question, please press *11 again. Please stand by while we compile our Q&A roster. Our first question is going to come from the line of Harry Zhou with BofA Securities. Your line is open. Please go ahead.

Speaker #2: Thank you. As a reminder, to ask a question, please press *11 on your telephone and wait for your name to be announced. To withdraw your question, please press *11 again.

Speaker #2: Please stand by while we compile our Q&A roster. Our first question will come from the line of Harry Zow with BofA Securities.

Speaker #2: Your line is open. Please go ahead.

Harry Zhou: Hi, and thanks management for taking my questions, and congratulations on the strong results and guidance. I have three questions. The first one is regarding the demand. How do you see demand trend in overseas and domestic market, and what are the key sectors driving the growth? The second one is regarding AI. We are happy to see that the call center application scenario is growing really fast. What are the other potential scenarios that could drive meaningful conversational AI demand growth? What will be the revenue contribution from conversational AI by end of the year and the gross margin trend? Lastly, about the competition, could management share the latest competitive landscape in overseas market against our major competitors? Thank you.

Harry Zhuang: Hi, and thanks management for taking my questions, and congratulations on the strong results and guidance. I have three questions. The first one is regarding the demand. How do you see demand trend in overseas and domestic market, and what are the key sectors driving the growth? The second one is regarding AI. We are happy to see that the call center application scenario is growing really fast. What are the other potential scenarios that could drive meaningful conversational AI demand growth? What will be the revenue contribution from conversational AI by end of the year and the gross margin trend? Lastly, about the competition, could management share the latest competitive landscape in overseas market against our major competitors? Thank you.

Speaker #4: Hi. Thanks, management, for taking my questions, and congratulations on the strong results and guidance. I have three questions. The first one is regarding demand and how the demand trends are in the overseas and domestic markets.

Speaker #4: And what are the key sectors driving the growth? The second question is regarding AI. We're happy to see that the call center application scenario is growing really fast.

Speaker #4: And what are the other potential scenarios that could drive meaningful conversational AI demand growth? And what will be the revenue contribution from conversational AI by the end of the year?

Speaker #4: And the gross margin trend? And lastly, regarding the competition, could management share the latest competitive landscape in overseas markets against our major competitors? Thank you.

Speaker #3: Okay. In terms of the demand, I will talk about the RTE side, and Tony can talk about the AI side. So on the RTE side, actually, things haven't changed that much.

Jingbo Wang: Okay, in terms of the demand, I will talk about the RTE side and Tony can talk about the AI side. On the RTE side, actually things haven't changed that much. Overall, what we see this quarter, in both China, US, and international markets, are largely the same as the last quarter. In China, thanks to a more stable operating environment, demand from social, entertainment, and education customers continue to recover. Our single-lens camera is looking pretty stable here. On the US and international side, demand from live shopping, financial services, gaming use cases continue to grow. Demand looks healthy on the RT side.

Speaker #3: Overall, what we see this quarter in both China, the US, and international markets is largely the same as last quarter. So in China, thanks to a more stable operating environment, demand from social entertainment and education customers continues to recover.

Speaker #3: So, things are looking pretty stable here. On the U.S. and international side, financial services and gaming use cases continue to grow. So, demand looks healthy on the RTE side.

Tony Zhao: Yes, and on AI side, I think it is fair to say our vision has been validated and reinforced on a daily basis with the rapid development and continued improvement we achieve on the ground. In call centers, as I mentioned in the remarks, with our agents matching and sometimes even surpassing human reps on certain tasks with solid measurable business outcome for the enterprise customers. This is just the beginning of a very, very long run, and I believe we will witness the transition from human call center reps to voice agents around the world, just like how large language model has reshaped the software engineering. This is actually a very good thing for people and the society because it will free people from the very tedious and stressful line of work.

Speaker #4: Yes, and on the AI side, I think it's fair to say our vision has been validated and reinforced on a daily basis with rapid development and continued improvement.

Speaker #4: We achieve this on the ground, in call centers, as I mentioned in the remarks, with our agents—matching and sometimes even surpassing human labs on certain tasks.

Speaker #4: With solid, measurable business outcomes for enterprise customers, this is just the beginning of a very, very long run. And I believe we will witness the transition from human call center reps to voice AI agents around the world.

Speaker #4: Just like how large language models have reshaped software engineering, this is actually a very good thing for people and society because it will free people from very tedious and stressful lines of work.

Tony Zhao: Keeping talking to different persons for hours about the same task and keeping the conversation strictly professional is very exhausting and emotionally draining.

Speaker #4: Keeping conversations strictly professional while talking to different people for hours about the same task is very exhausting and emotionally draining.

Speaker #3: Yes. So, in terms of the use case for conversational AI, I can talk about two verticals: call centers and companionship devices.

Jingbo Wang: Yep. So in term of the use case for conversational AI, I can talk about two verticals, call center and the companionship devices. Tony already talked about a lot, covered a lot on the call centers. I want to highlight one point. When we talk about call centers, it is not a single use case. It is a collection of many, many use cases, each with different features and different domain knowledge. When we talk about these use cases, actually, in term of the difficulty for replacement by Voice AI agents, actually they form a spectrum from the easy one on the left-hand side to the hard one on the right-hand side. Now we are only beginning to explore a few use cases on the left-hand side, such as outbound marketing and survey. These are the low-hanging fruits.

Speaker #3: But like Tony already talked about, he covered a lot on the call centers. But I want to highlight one point. When we talk about call centers, it's not a single use case.

Speaker #3: It's a collection of many, many use cases, each with different features and different domain knowledge. And when we talk about these use cases, actually, in terms of the difficulty for replacement by voice AI agents, they actually form a spectrum, from the easy ones on the left-hand side to the hard ones on the right-hand side.

Speaker #3: And now we are only beginning to explore a few use cases on the left-hand side, such as open marketing and survey. But these are the low-hanging fruits.

Jingbo Wang: As we continue to refine our solutions and accumulate more experience of working with our customers, we will convert more and more use cases from impossible to proof of concept to real-world production. So it has a very long runway. It is not a similar use case we can conquer in one quarter, in one year. It is going to be a multi-year process. Secondly, on the companionship device, we talked about customer RoboQuoi in the past. In this quarter, they actually expanded into new markets in Japan and other countries, and the initial market feedback has been quite encouraging. We also partner with several chip makers to make our solution compatible with more chips because these are not mobile phone chips. These are very specialized LTE chips, and this will make our solution available on a wide range of smart devices, including robots even.

Speaker #3: As we continue to refine our solutions and accumulate more experience working with our customers, we will convert more and more use cases from impossible, to proof of concept, to real-world production.

Speaker #3: So, it has a very long runway. It's not a single use case we can conquer in one quarter or one year. It's going to be a multi-year process.

Speaker #3: And secondly, on the companionship device, we talked about customer overpoint in the past. In this quarter, they actually expanded into new markets in Japan and other countries.

Speaker #3: And the initial market feedback has been quite encouraging. We also partnered with several chip makers to make our solution compatible with more chips.

Speaker #3: Because these are not mobile phone chips—these are very specialized IoT chips. And this will make our solution available on a wide range of smart devices, including robots.

Speaker #3: So overall, we are still targeting 5% revenue contribution from conversational AI by the end of this year. Competition. Tony, want to talk about competition?

Jingbo Wang: Overall, we are still targeting 5% revenue contribution from conversational AI by the end of this year. Competition, Tony. Want to talk about competition?

Tony Zhao: Okay. You want to talk about gross margin or not?

Speaker #4: Okay. Do you want to talk about gross margin, or not?

Jingbo Wang: No, that's fine.

Speaker #3: No. That's fine.

Tony Zhao: Okay. About competition, especially on conversational AI. Conversational AI has several distinct technology layers, from agent layer that orchestrates and optimize the call center or the call experience to model layer that includes large language model and voice models such as ASR or TTS, and finally, infra layer such as telecom APIs and cloud. Different players attack this market from different angles. For example, Twilio would leverage its strength in telecom APIs and phone numbers from their CPaaS business, and we are focused on the voice models, audio pre-processing and post-processing, low latency cloud infrastructure, and agent layer to deliver the best possible call experience. Given the huge potential of the conversational AI market, it is natural to have competition. In fact, a lot of the technology in conversational AI involves audio processing, such as handling noise, echoes, or packet loss.

Speaker #4: Okay, so about competition, especially in conversational AI. Conversational AI has several distinct technology layers: from the agent layer, which streamlines and optimizes the call center and the call experience, to the model layer that includes large language models and voice models, such as ASR or TTS, and finally, the infrastructure layer, such as telecom APIs and cloud.

Speaker #4: Different layers, different players attack this market from different angles. For example, Twilio would leverage its strengths in telecom APIs and phone numbers from their CCaaS business.

Speaker #4: And we are focused on the voice models, audio pre-processing and post-processing, low-latency cloud infrastructure, and agent layer to deliver the best possible call experience.

Speaker #4: Given the huge potential of the conversational AI market, it is natural to have competition. In fact, a lot of the technology in conversational AI involves audio processing, such as handling noise, echoes, or packet loss.

Tony Zhao: Obviously, we have a lot of experience in those areas, which can hugely improve conversational AI experience. We remain confident about our position in this market.

Speaker #4: Obviously, we have a lot of experience in those areas, which can hugely improve the conversational AI experience. So, we remain confident about our position in this market.

Jingbo Wang: Harry, got this on the recording.

Speaker #3: Harry, can you answer your question?

Harry Zhou: Yeah, thanks. Yes, very helpful. Thanks, Tony and Jingbo. Congratulations again on the results. Thank you.

Harry Zhuang: Yeah, thanks. Yes, very helpful. Thanks, Tony and Jingbo. Congratulations again on the results. Thank you.

Speaker #4: Yeah. Thanks. Yes. Very helpful.

Speaker #1: Thanks, Tony and Jimbo. Congratulations again on the results. Thank you.

Speaker #2: Thank you. And one moment for our next question. Our next question comes from the line of Yushu with China Securities Co. Your line is open.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Yu Shu with China Security Co. Your line is open. Please go ahead.

Speaker #2: Please go ahead.

Yu Shu: Hi, management team. Thanks for taking my question, and congrats on another strong quarter. My first question regards Convo AI. Could you please update on Convo AI revenue progress and its projected contribution to full year revenue? My second question is the conversion cycle for AI use cases. Could you disclose the current backlog for these AI use cases, or maybe just customer accounts? How would you view the trend for AI revenue for the coming quarters, maybe next year?

Yue Xu: Hi, management team. Thanks for taking my question, and congrats on another strong quarter. My first question regards Convo AI. Could you please update on Convo AI revenue progress and its projected contribution to full year revenue? My second question is the conversion cycle for AI use cases. Could you disclose the current backlog for these AI use cases, or maybe just customer accounts? How would you view the trend for AI revenue for the coming quarters, maybe next year?

Speaker #5: Hi Nancy, thanks for taking my question. And congrats on another strong quarter. My first question is regarding Kernel AI—could you please update us on Kernel AI's revenue progress and its projected contribution to full-year revenue?

Speaker #5: My first, second question is about the conversion cycle for AI use cases. Could you disclose the current backlog for these AI use cases, or maybe just the number of customer accounts?

Speaker #5: And how would you view the trend for AI revenue for the coming quarters, maybe next year?

Speaker #3: Thank you. I'll take the question. So we already talked about a lot talk a lot about the use cases. So first of all, I want to explain that it actually takes quite some time for a use case to really ramp up from the startup, the POC, to the point where the AI agent can deliver consistent performance and can be deployed at scale.

Jingbo Wang: Thank you. I will take the question. We already talked a lot about the use cases. First of all, I want to explain that it actually takes quite some time for a use case to really ramp up from the start of the POC to the point where AI agents can deliver consistent performance and can be deployed at scale. It usually takes several months. I talked about there are many use cases. We need to attack them one by one. We can do a few in parallel, but it is going to be a gradual process. As I mentioned earlier, we are targeting 5% revenue contribution by the end of the year. Basically, our goal is in Q4, or in terms of the run rate, ARR run rate, we want to achieve 5% by the end of the year.

Speaker #3: It usually takes several months. And I talk about there are many, many use cases we need to attack them one by one. Also, we can do a few in parallel, but still, it's going to take it's going to be a gradual process.

Speaker #3: So, as I mentioned earlier, we're targeting a 5% revenue contribution by the end of the year. So basically, our goal is in Q4, or in terms of the ARR run rate, we want to achieve 5% by the end of the year.

Jingbo Wang: Obviously, that means for the full year of 2026, it is not going to be 5%, it is going to be smaller than that. If we achieve 5% by the end of the year, and given the strong pipeline we already have on hand, which will only become bigger by the end of the year, we believe there will be still significant room for growth next year. We will remain quite optimistic about the outlook in this market.

Speaker #3: Obviously, that means for the full year of 2026, it's not going to be 5%. It's going to be smaller than that. But if we achieve 5% by the end of the year, and given the strong pipeline we already have on hand, it will only become bigger by the end of the year.

Speaker #3: We believe there will still be significant room for growth next year. So we remain quite optimistic about the outlook in this market.

Speaker #2: Thank you. And one moment for our next question. Our next question comes from the line of Zongxuan Yang with CITIC Securities. Your line is open.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Zhong Xin Yang with CITIC Securities. Your line is open. Please go ahead.

Speaker #2: Please go ahead.

Speaker #4: Okay, so thanks for taking my question. I just have one question regarding our AI business. Have we ever given any guidance on the long term, about three to five years, for the AI penetration rate in our total revenue?

Zhong Xin Yang: Okay. Thanks for taking my question. I just have one question regarding to our AI business. Have you ever given a guidance on the long term, for about three to five years, for the AI penetration rate for our total revenue and also for the gross margin guidance? Thank you.

Zongxuan Yang: Okay. Thanks for taking my question. I just have one question regarding to our AI business. Have you ever given a guidance on the long term, for about three to five years, for the AI penetration rate for our total revenue and also for the gross margin guidance? Thank you.

Speaker #4: And also for the gross margin guidance. Thank you.

Tony Zhao: All right. I will take the question. In the end, the call center market will have three segments. First is the easiest tasks, such as simple notifications. This will be handled by NLP-based technology, which has no real intelligence but can understand simple keywords from human. The second would be the hardest tasks or most important tasks, such as handling complaints from high-value customers or emergency situations, which will continue to be handled by human. Even if AI agent is technically able to handle the task, in some cases, only humans can take certain responsibilities, such as in a 911 call. The third would be everything else in the middle of the previous two. Those will be handled by Voice AI agents with real intelligence. It is hard to say exactly how big this part will be, but it will be a significant portion of the entire market.

Speaker #5: All right. I'll take the question. In the end, the call center market will have three segments. First is the easiest tasks, such as simple notifications.

Speaker #5: This will be handled by NLP-based technology, which has no real intelligence but can understand simple keywords from humans. The second would be the hardest tasks, or the most important tasks, such as handling complaints from high-value customers or emergency situations.

Speaker #5: Some tasks will continue to be handled by humans, even if an AI agent is technically able to handle them. In some cases, only humans can take certain responsibilities, such as in a 911 call.

Speaker #5: The third would be everything else in the middle—between the previous two. Those will be handled by voice AI agents, with real intelligence.

Speaker #5: It's hard to say exactly how big this part will be, but it will be a significant portion of the entire market.

Speaker #3: So yeah. So Tony, talk about the sort of the certified outlook for the call center market, which is a huge market. There are literally close to 20 million people working in call centers today in the world.

Jingbo Wang: So yeah. Tony talked about the sort of five-year outlook for the call center market, which is a huge market. There are literally close to 20 million people working in call centers today in the world. As Tony said, there will be three categories in the future, and probably the middle category will be the biggest, and that will be handled by Voice AI agents. So even taking a small part of that market, that would be transformational for our company. So at this point, it is hard to give a clear number as this market is still at a very early stage. The overall penetration of Voice AI agents is still very low. So it is hard to say exactly how big this will become, but it certainly will be transformational for us.

Speaker #3: And as Tony said, there will be three categories in the future, and probably the middle category will be the biggest. That will be handled by voice AI agents.

Speaker #3: So even taking a small part of that market would be transformational for our company. At this point, it's hard to give a clear number, as this market is still at a very, very early stage.

Speaker #3: And the overall penetration of AI voice AI agents is still very low, so it's hard to say exactly how big this will become. But it certainly will be transformational for us.

Speaker #3: And in terms of the gross margin, today the gross margin is not high for us. We talked about that last quarter. It's crossing the next positive line, right?

Jingbo Wang: In terms of the gross margin, today, the gross margin is not high for us. We talked about that last quarter. It is crossing the maximum possible line, but it is still around there. It is not because any fundamental reason. It is because, one, we are subscale. The volume is small, and the volume is happening at different geographies. So at each single geography, the volume is even smaller. Subscale. Secondly, we have not really focused that much on the technical optimization. Right now, our optimization is more focused on the experience than on the cost. So once we have a larger scale and also be more focused on the technical optimization on cost, we believe in the end, the gross margin will be similar to, if not higher, than what we have right now in the RTE business.

Speaker #3: It's still around there, but it's not because of any fundamental reason. It's because, one, we are subscale—the volume is small—and the volume happens in different geographies.

Speaker #3: So, at each single geography, the volume is even smaller, so it's subscale. And secondly, we haven't really focused that much on the technical optimization.

Speaker #3: Right now, all the optimization is more focused on the experience, not the cost. So once we have a larger scale and also are more focused on the technical optimization of cost, we believe, in the end, the gross margin will be similar to, if not higher than, what we have right now in the RTE business.

Speaker #4: Great. Sorry to cut in. No more questions.

Zhong Xin Yang: Great. It is very clear. Thank you. No more questions.

Zongxuan Yang: Great. It is very clear. Thank you. No more questions.

Speaker #2: Thank you. And as a reminder, if you would like to ask a question at this time, please press star one one on your telephone. Our next question comes from the line of Tristan Yang with 99 Capital.

Operator: Thank you. As a reminder, if you would like to ask a question at this time, please press star 1 1 on your telephone. Our next question comes from the line of Tristan Yang with DoubleLine Capital. Your line is open. Please go ahead.

Speaker #2: Your line is open. Please go ahead.

Tristan Yang: Hey, nice results today. Tony, regarding your announcement to purchase the additional $20 million of shares on the open market, I am wondering how much have you purchased to date? What valuation do you believe appropriately reflects Agora's intrinsic value? Given your existing ownership stake, have you considered taking the company private or returning additional capital to shareholders through a special dividend for an accelerated buyback program? Thank you.

Speaker #5: Hey, nice results today. Tony, regarding your announcement to purchase the additional $20 million of shares on the open market, I'm wondering how much you have purchased to date?

Speaker #5: And then, what valuation do you believe appropriately reflects Agora's intrinsic value? And given your existing ownership stake, have you considered taking the company private or returning additional capital to shareholders through a special dividend or an accelerated buyback program?

Speaker #5: Thank you.

Jingbo Wang: Let me answer this question because it is quite technical. Basically, Tony has not started due to certain blackout and legal restrictions. Once these are cleared, he will start the repurchase. As he is certainly obviously an insider, and he has previous purchases in the past, beginning of this year, there are certain legal restrictions. As to the $20 million, that has not started yet. We have returned up to this point about $160 million of capital back to the shareholders through share repurchase. That compares to about $400 million to $350 million of market cap of the company, which is substantial and probably among the most substantial among any public company in the world. We will continue to do that.

Speaker #3: Let me ask this question because it's quite technical. So basically, Tony has not started due to certain blackout and legal restrictions. But once these are cleared, he will start the repurchase.

Speaker #3: So as he is obviously an insider, and he has a previous purchase in the past at the beginning of this year. So there are certain legal restrictions.

Speaker #3: So, as to the $20 million that has not started yet, we have returned, up to this point, about $160 million of capital back to the shareholders.

Speaker #3: So share repurchase. And that compares to what about 400 million dollars, 350 million dollars of market cap of the company. Which is a substantial and probably among the most substantial among any public company in the world.

Speaker #3: So, we will continue to do that. But at this point, we have not considered a special dividend, which we might consider in the future, but not at present.

Jingbo Wang: At this point, we have not considered a special dividend, which we might consider in the future, but not at present.

Speaker #5: Yeah, I think my purchase will start in, like, two or three weeks, right? September.

Tony Zhao: Yeah, I think my purchase will start in 2, 3 weeks, right?

Tony Zhao: September.

Jingbo Wang: Yeah. Subject to certain conditions.

Speaker #3: Yeah. September 2, certain conditions.

Tony Zhao: Okay. I don't think we will consider take the company off the market. We will want to keep communicate with capital market. For ourselves, focus on business operation and improve our overall technical and operation strengths. We feel very confident that the future of our direction has a very big potential. We think by focus on our business operations and technical advancement, we will be able to make a lot of value for our customers, our shareholders, and our employees.

Speaker #5: Okay. And I don't think—we don't think—we will consider taking the company off the market. We will want to keep communicating with the capital market, and for ourselves, focus on business operations and improve our overall technical and operational strengths.

Speaker #5: We are still very confident that the future of our direction has very big potential. And we think by focusing on our business operations and technical advancement, we will be able to create a lot of value for our customers, our shareholders, and our employees.

Tristan Yang: Got it. Very clear. Thank you.

Speaker #4: Got it. Very clear. Thank you.

Operator: Showing no further questions, this will conclude today's Q&A session. Thank you everybody for attending the company's call today. As a reminder, a recording and the earnings release will be available on the company's website at investor.agora.io. If you have any questions, please feel free to email the company. Thank you. You may now disconnect. Everyone, have a great day.

Speaker #2: Seeing no further questions, this will conclude today's Q&A session. Thank you, everybody, for attending the company's call today. As a reminder, a recording and the earnings release will be available on the company's website at investor.agora.io.

Speaker #2: And if you have any questions, please feel free to email the company. Thank you. You may now disconnect. Everyone, have a great day.

Jingbo Wang: Bye-bye.

Speaker #3: Bye-bye.

Tony Zhao: Bye.