Agora - Earnings Call - Q3 2025

Transcript

Operator (participant)

Please be advised that today's conference is being recorded. The company's earning results press release, earning presentation, SEC filings, and the 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, and Jingbo Wang, the company's CFO. During this time, the company will make forward-looking statements about its future financial performance and future events and trends. These statements are only predictions that are based on what the company believes today, and 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, which the company discusses in detail in its filing with the SEC, including today's earnings press release and risk factors and other information contained in the final prospect relating to its initial public offering.

Agora 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. Please go ahead.

Tony Zhao (Founder, Chairman, and CEO)

Thanks, Operator. Welcome everyone to our earnings call. I'll first reveal our operating results from the past quarter. We're pleased to report our fourth consecutive quarter of GAAP profitability in Q3, supported by double-digit revenue growth and expanding margins. Total revenue in Q3 reached $35.4 million, up 12% year-over-year. Our GAAP net profit for the quarter was $2.7 million, with a GAAP net margin of 7.8%. We expect our revenue and net profit to continue growing on a quarter-over-quarter basis in Q4. As you can see, our core real-time engagement path business is rebounding strongly and is on track to deliver its first full-year revenue growth since the pandemic, providing a stable, profitable foundation for us. At the same time, we are significantly increasing our investment in conversational AI. Voice-based human-machine interaction is not new, yet most conversational AI solutions today still disappoint users. Why?

Because building voice agents that can converse naturally with a human is just hard. Just a few months ago, Greylock Partners, a leading venture capital firm, published a blog post titled, "Voice Agents: Easy to Use, Hard to Build." They nailed the core challenge. Behind the simplicity users expect lies immense complexity: system obstruction, real-time audio processing, latency management, and compliance requirements. Consider the issue of background noise and multiple speakers. Just two of the many technical challenges. In a real-world setting, like a busy home, office, or car, clean audio is the exception, not the norm. A voice agent must accurately isolate a user's voice from overlapping speech and ambient sounds. Without this, transcription becomes unreliable. Intent is misunderstood, and the agent's reasoning falters, undermining the whole interaction. Furthermore, as Andrew Tapassi has pointed out, there is often a significant gap between a working demo and a production-ready product.

Conversational AI is no exception. For instance, in our discussion with customers and prospects, many have expressed frustration with the reliability and scalability of current solutions, especially when users are distributed across geographies or when concurrent usage is high. Our investment in conversational AI is specifically aimed at addressing these challenges. Recently, we launched our conversational AI Engine 2.0. It integrates over a decade of advanced audio research and development, including AI-powered noise suppression, acoustic echo cancellation, a proprietary audio codec, and adaptation across thousands of device types to ensure that AI hears and speaks with consistent clarity. In addition, the engine also tackles core interaction challenges: selective attention, turn-taking, interruption handling, emotion detection, and natural conversational flow. In short, we're not just providing the transmission pipeline for voice and video. We're building the behavioral intelligence that powers truly responsive, human-like conversational AI agents.

To help developers build voice agents more easily, we announced our conversational AI Studio at our recent Convo AI and RTE Conference in late October, which allows developers to create, configure, and deploy voice agents through a zero-code interface. Complementing this, our conversational AI Benchmark and Orchestration Platform allows developers to evaluate, mix and match, and optimize both our proprietary and third-party modules so they can identify the best-performing combination for their specific use case. Our Open-Source TEN Framework designed for building voice agents continues to gain traction in the developers' community. Recognized for its high concurrency architecture and deep cross-platform integration, it has been adopted by multiple cloud providers and major enterprises for their agent orchestration platforms. All these products are backed by our global distributed real-time inference cloud.

Over the past several months, we've expanded this infrastructure to cover key regions across North America, South America, Europe, and Asia, ensuring consistent latency, reliability, and performance even under high concurrency and varying network conditions. Early adoptions from customers around the world have been encouraging, and our pipeline of use cases and prospects continues to grow as we head into next quarter. Our recent Convo AI and RTE Conference attracted more than 3,000 on-site attendees, a record for us, and made it the largest gathering focused on conversational AI technology globally. Our customers and developers are deploying our conversational AI solutions to build voice agents for outbound marketing, inbound customer service, tutoring, and many other applications. Power manufacturers are also integrating our technology into smart toys, enabling voice-powered companionship and learning experiences.

In conclusion, the convergence of advanced AI models and robust real-time infrastructure is unlocking a new era of possibilities. Backed by proven scalability, deep technology expertise, and a forward-looking product suite, we're well-positioned to empower this next chapter, enabling truly human-like, reliable, and scalable voice agents. With that, let me turn things over to Jingbo, who will reveal our financial results.

Jingbo Wang (CFO)

Thank you, Tony. Hello, everyone. Let me start by first reviewing financial results for the third quarter of 2025, and then I will discuss outlook for the fourth quarter. Total revenues for the third quarter reached $35.4 million, up 12% year-over-year, representing a third consecutive quarter of double-digit organic growth. If we look at the two business divisions, Agora revenues reached $18.2 million in Q3, representing 15.9% year-over-year growth and flat quarter-over-quarter. The strong year-over-year growth reflects our successful market penetration and growing adoption in verticals such as live shopping. Shenghua revenues reached RMB 122.4 million in Q3, up 8.4% year-over-year and 6% sequentially, driven by continued business expansion and adoption in key verticals such as social, entertainment, and IoT. Dollar-based net retention rate is 108% for Agora and 90% for Shenghua, marking the fourth consecutive quarter of improvement for both businesses.

Gross margin for the third quarter was 66%, slightly decreased 0.7% year-over-year and 0.8% sequentially. Moving on to expenses, R&D expenses were $13.8 million in Q3, decreased 52.8% year-over-year. R&D expenses represented 39.1% of total revenues in the quarter, compared to 92.7% in Q3 last year. Sales and marketing expenses were $6.5 million in Q3, decreased 5.6% year-over-year. Sales and marketing expenses represented 18.3% of total revenues in the quarter, compared to 21.7% in Q3 last year. G&A expenses were $5 million in Q3, decreased 48.4% year-over-year. G&A expenses represented 14.1% of total revenues in the quarter, compared to 30.8% in Q3 last year. Moving on to the bottom line, we delivered net income of $2.7 million in Q3, representing a 7.8% net income margin. This result represents a significant improvement from last year and marks our fourth consecutive quarter of GAAP profitability.

Based on our current business momentum and visibility into the fourth quarter, we expect net income to grow sequentially compared to Q3. Now turning to cash flow, operating cash flow was $0.7 million in Q3, compared to negative $4.6 million last year. Moving on to balance sheet, we ended Q3 with $374.3 million in cash, cash equivalents, bank deposits, and financial products issued by banks. Net cash outflow in the quarter was mainly due to share repurchase of $4.8 million. In the third quarter, we repurchased 5.2 million ordinary shares or 1.3 million ADS, representing 1.4% of our outstanding shares at the beginning of the quarter. Since our board approved the share repurchase program in February 2022, we have repurchased $132.1 million worth of shares through September 30, 2025.

The share repurchase program demonstrates our dedication to returning value to our shareholders, balanced with our ability to continue investing in strategic growth opportunities. Now turning to guidance for the fourth quarter of 2025, we currently expect total revenues to be between $37 million and $38 million, compared to $34.5 million in the fourth quarter last year, representing year-over-year growth rate of 7.2% -10.1%. This outlook reflects our current and preliminary views on the market and operational conditions, which are subject to change. In closing, I would like to express my gratitude to our outstanding teams in Agora and Shenghua. Our sustained double-digit revenue growth and profit expansion are a direct reflection of your hard work and strategic focus. To our shareholders, thank you for your continued trust. We remain focused on executing our roadmap to build a durable, market-leading company at the forefront of AI innovation.

Thank you all for joining today's call. Let's open it up for questions.

Operator (participant)

Thank you very much. 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 Zhao from Bank of America Securities. Please go ahead.

Harry Zhao (Analyst)

Thanks, Management, for taking my question. Congratulations on another quarter of double-digit growth and solid guidance for the fourth quarter this year. I have three questions. First is regarding the demand outlook. Could Management share about the key trends in both domestic and international markets for the coming quarters and what are the key downstream sectors that are driving the demand growth? The second question is regarding the AI application. Could Management share the latest update on the development of AI and also what are the key scenarios that could drive meaningful revenue contribution in the near term? Thirdly is on the profitability outlook. Could Management share the profitability outlook for both fourth quarter this year and also for 2026 on the operating profit level and also the net profit level? Thanks.

Tony Zhao (Founder, Chairman, and CEO)

All right. I'll take the first two questions, and Jingbo will take the last one. For the demand in China, the overall demand recovery trend continues. With stabilized regulatory environment and demand from social entertainment and education customers refunded and gradually goes up, demand from IoT and digital transformation customers are experiencing rapid growth. In US and international markets, live commerce demand continued its rapid growth, and other verticals generally show growth as well. The overall growth rate is slightly faster than in China. As to the AI demand and the trend, before I answer the question, I want to first clarify the difference between voice AI and conversational AI. We are actually focused on conversational AI, which is very related to our real-time engagement business, and it means the real-time human-AI voice interaction. On the other hand, voice AI is a much broader concept.

It includes both real-time conversation and non-real-time functionalities such as audio recognition and generation. The non-real-time use case is actually much more broad, and non-real-time audio recognition generation is also much easier to achieve usability and to find practical use cases. In the past two years, audio generation or text-to-speech has been widely used in non-real-time content production. For example, most of the short video clips people watch today are using AI-generated voiceover. Those have been growing in the last two years in the social media and a lot of other markets. However, when we move to real-time conversation, the complexity of the technology makes the whole experience much more challenging, as I stated in the opening remark, and takes longer to mature and gain adoption.

In conversational AI applications, currently, there are three use cases that have progressed to a more advanced stage, namely call center, education, and companionship toys. For these use cases, we already see some customers have moved from proof-of-concept phase to real-world production. Given the vast scale and the potential usage of these verticals, we expect the success of these customers will drive broader adoption. We already have customers in production today, but usage is still ramping up. We expect to see some sizable conversational AI revenue in the first half of next year, and hopefully, conversational AI will become a meaningful revenue contributor towards the end of next year.

Jingbo Wang (CFO)

Okay. Third question. For Q4 this year, given that Q4 is normally a strong season for us, we expect to achieve GAAP operating profit per case in Q4, and therefore, the GAAP net profit will further grow on top of the Q3 level. For next year, our target is to achieve GAAP operating profit for the full year of 2026. GAAP net profit, that's, first of all, a big improvement over 2025 already. In terms of the GAAP net profit, that will have some level of uncertainty due to the potential interest rate cut. Under the current forecast, we expect year-over-year net income improvement over 2025 as well.

Operator (participant)

Thank you. Just a moment for our next question, please. Next question comes from Rachel Wang from CICC. Please go ahead.

Rachel Wang (Investment Banking VP)

Thank you for taking my questions. Can you hear me?

Jingbo Wang (CFO)

Yes.

Rachel Wang (Investment Banking VP)

Hi, this is Rayhan from CICC. First of all, congrats on the solid growth this quarter, and especially the continued improvement in profitability. I have two questions. First, I noticed that our third quarter revenue came in slightly above the midpoint of the guidance range. Could you give us more color on what drove this solid performance? My second question is, on the AI side, which downstream applications are showing the strongest momentum so far? In particular, how is the adoption trend for AI companionship toys, and when should we expect these use cases to start contributing to your financial results? Thank you.

Jingbo Wang (CFO)

Okay. I'll take the first question. As Tony mentioned in the earlier question, for Q3, actually, we see pretty strong demand from the U.S. and international market as well as the China market. In the U.S and international market, live commerce continued to grow very strongly, especially in more developed markets. The other verticals, such as social and fintech, are also growing pretty well in Q3. In China, first of all, we had the summer vacation in Q3, which is generally the strong season for social apps and also for education apps. In addition, the IoT sector, so smart cameras, smart wearable devices like watches, and also the smart toys, are all experiencing very rapid growth.

Tony Zhao (Founder, Chairman, and CEO)

Yeah. For the AI sort of use cases side, there are quite strong pipelines of customers and prospects for call centers, including outbound marketing and inbound customer services. For AI companionship toys, we see strong momentum from our customer, RoboPong. Their sales and usage numbers are quite impressive, and they also started to charge end-user monthly subscription fees, which we believe is a more healthy and sustainable business model and also a breakthrough in similar kind of toys. A couple of other toys manufacturers are also in the process of integrating our solutions, and we expect to see them coming to market in the next few months.

Operator (participant)

Thank you.

Rachel Wang (Investment Banking VP)

Okay. Thank you for your detailed answers. I wish our company continued growth and success. Thank you.

Tony Zhao (Founder, Chairman, and CEO)

Thank you.

Jingbo Wang (CFO)

Thank you.

Operator (participant)

Our next question comes from Yuxing from China Securities. Please go ahead.

Hi, Management. Thanks for taking my question, and congrats on the strong execution quarters. My first question relates on AI usage. Could you share the sequential growth trend for AI-related usage? Looking at our current customer pipeline, when can we see signs of meaningful scale for these AI applications? My second question relates on maybe strategy expansion. We could see some CDN vendors expanding into edge GPU inference and security. Given our R&D infrastructure, could we see a similar path to maybe offer Oracle or just a cross-sell edge-side inference or security features?

Tony Zhao (Founder, Chairman, and CEO)

Yeah. Conversational AI usage increased by more than 150% on a quarter-over-quarter basis. It is quite fast. Although, as I mentioned, the voice AI has matured for years already, conversational AI is still at the early stage. We do see a strong pipeline of customers and prospects. We believe we are not far from more broader adoption and proliferation of voice agents. For the second question, we are not a CDN company, but we do have a global distributed network and a large number of data centers distributed across every major region. It is a good question. In fact, we have opportunities that are similar but from a different perspective. Specifically, we are targeting real-time inference services for conversational AI. This is what we build for our own product.

This inference service needs to connect with multiple distributed ASR, TTS, large language model service, as well as our self-developed and deployed modules in different locations. This kind of capability is a must to support the call process in a way that it has to be very low latency so that the real-time nature of the interaction could be enabled. Such an infrastructure service is of great value to any agent that requires ultra-low latency or real-time inference. This is also an opportunity we could expand in the future.

Okay. Thank you. That's very helpful.

Operator (participant)

Thank you. Just a reminder to ask the question, please press star one one on your telephone keypad. Thank you. There are no further questions. That concludes today's Q&A session. Thank you, everybody, 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 are any other questions, please feel free to email the company. Thank you.