Agora (API) Q1 2026 Earnings Call Transcript

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DATE

Tuesday, May 26, 2026 at 9 p.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — Bin Zhao
• Chief Financial Officer — Jingbo Wang

TAKEAWAYS

• Total Revenue -- $37.7 million, representing 13.5% year-over-year growth and above the $36 million-$37 million guidance range.
• GAAP Net Income -- $1.1 million, more than double the net income reported in the same period last year, with a net income margin of 2.9%.
• Gross Profit -- $23.9 million, a 5.7% year-over-year increase, with gross margin at 63.4%, compared to 68% in the same period last year due to product mix shifts, especially subscale conversational AI products.
• Operating Expenses -- R&D expenses totaled $14.4 million, up 2.9% year over year and making up 38.1% of revenue; sales and marketing expenses were $5.9 million, down 4.8% year over year, accounting for 15.6% of revenue; G&A expenses were $6 million, down 3.4% year over year, at 15.9% of revenue.
• GAAP Profitability -- Achieved a sixth consecutive quarter of GAAP profitability, attributed to operating leverage improvements and disciplined expense management.
• Dollar-Based Net Expansion Rate (DBNER) -- 99%, an increase from 95% in the first quarter of 2025, reflecting methodology refinement to better track same-customer growth.
• Cash Flow and Balance Sheet -- Operating cash flow (including interest) was $5.7 million, with a net cash outflow primarily due to $13.1 million share repurchase of approximately 3.6% of outstanding shares; total cash, equivalents, and financial products stood at $166 million as of March 31, 2026.
• Share Repurchase Program -- Cumulative repurchases reached 78.1% of the current $200 million program, representing 43.7 million ADS and $156.2 million spent.
• Q2 2026 Guidance -- Revenue expected between $39 million and $40 million, implying 13.7%-16.6% year-over-year growth with further sequential acceleration versus Q1 performance.
• Conversational AI Usage Growth -- CEO Bin Zhao noted “usage has demonstrated remarkable momentum. With over 150% sequential growth every single quarter” since the launch of the conversational AI engine product.
• Product Launches -- Unveiled the Agent Series, a low-code visual environment to rapidly build and deploy AI agents, and the Intelligent Meeting Engine, targeting enterprise collaboration with AI-enhanced transcription, summary, and data security features.
• Strategic Partnerships -- Announced integration of Google Gemini Live and XAI models, with Agora featured as a recommended Google partner for real-time conversational AI; established a new partnership with NetEase Smart Enterprise to expand offerings in content moderation and AI-driven engagement.
• Market Segment Performance -- Both China and US/international businesses grew rapidly, with US growth outpacing China; main demand in China from social, entertainment, education, and new IoT-driven verticals, and in the US from live shopping, healthcare, and financial services.
• Conversational AI Revenue Outlook -- Management expects conversational AI products could contribute approximately 5% of total revenue by year-end, up from a relatively low current base.

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RISKS

• Gross Margin Pressure -- CFO Jingbo Wang stated gross margin dropped to 63.4% from 68%, "mostly due to the initial negative gross margin of the conversational AI business," which remains at a subscale and high-experimentation stage.
• Competitive Intensity -- CEO Bin Zhao highlighted, there is a lot of competition. For conversational AI in Silicon Valley and US market. Market is still at early stage. And there are different players trying to attack it. From quite diverse angles. Because it is still a growth market. So every company has a chance to win from different angles and still making progresses.
• Conversational AI Profitability Drag -- Wang noted that in first quarter, 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 has generated no revenue but a lot of cost.

SUMMARY

Agora (NASDAQ:API) reported accelerating revenue and continued GAAP profitability, driven by growth in real-time engagement and early momentum in conversational AI. Management specified that both China and US/international segments are expanding, but US market growth is stronger, supported by use cases in live shopping and healthcare. Product launches in AI agent and meeting technologies, as well as new ecosystem partnerships with Google and NetEase, were positioned as strategic advances enabling broader enterprise adoption and new market penetration. The company is maintaining significant investment in conversational AI and expects its contribution to total revenue to grow rapidly, while acknowledging that short-term gross margin is constrained by subscale AI operations and elevated experimentation costs.

• The revised DBNER calculation was introduced to more accurately reflect year-over-year customer spend dynamics, and aligns this metric with quarterly revenue growth rates.
• Management anticipates operating income and net income to grow sequentially each quarter through year-end, targeting notably higher GAAP net profit for 2026 and a return to GAAP operating profit in the second half.
• Share repurchase activity reduced outstanding share count by approximately 3.6% during the quarter, with the cumulative buyback program reaching over three-quarters of its authorized $200 million size.
• Underlying gross margin for core real-time engagement products remained relatively stable, as pressure was isolated to the conversational AI segment during its initial rollout and customer proof-of-concept phase.
• Management does not expect the conversational AI investment drag to impact the goal of achieving positive operating profit margin by Q4 2026.

INDUSTRY GLOSSARY

• Dollar-Based Net Expansion Rate (DBNER): A metric that compares revenue in a given quarter to revenue from the same group of customers in the prior year, measuring growth from existing clients after accounting for upsells, downsells, and churn.
• POC (Proof of Concept): An initial deployment stage where products or services are tested in real customer environments to validate viability and performance before scaling, often generating costs without immediate revenue.
• RTE (Real-Time Engagement): Technologies and platforms that allow synchronous, interactive communications such as live video, audio, and chat within applications.

Full Conference Call Transcript

Bin Zhao: Hi, Tony. Thank you, operator. And welcome everyone to our earnings call. I will start with a review of our, operating results for the quarter. I am pleased to report our 6th consecutive quarter of GAAP profitability. Alongside another quarter of strong top line growth. Total revenue for the first quarter of 2 thousand 26 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 an 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 abilities with our real time engagement infrastructure and expanding our ecosystem partnerships. In March, we officially launched an agent series. A visual low code environment that enables developers and enterprise to rapidly build past and deploy with 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-1. At the same time, many enterprises still struggle to deploy voice AI in production environments. The challenge is not simply AI model itself, but the complexity of integrating multiple technology layers. While maintaining low latency reliability, and the natural conversational experience at scale. In addition, effective enterprise deployment require domain specific expertise. 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 a debt collection agent need very different conversational styles.

Content scenarios, and customer engagement approaches. Our solution is designed to eliminate this complexity through a fully integrated stack that combines 3 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 laundry model, and TTS capabilities with intelligent inter interruption handling. Noise suppression, marketing role 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. We are already seeing strong early validation. From real world deployments. In Q1, 1 customer implemented a story and pulling 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 this capability. 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 employment options, including on premises and private cloud and a full data isolation to help ensure that customer meeting content remains entirely within their controlled influence infrastructure.

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 the contents date, server net server netting, and intelligent workflow automation and has been well received in industries, including finance, government, and health care. Turning to ecosystem partnerships. We continue to integrate the native AI models such as Google's Gemini Live, and XAI's 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 into a strategic partnership with NetEase Enterprise Service Division. NetEase Smart Enterprise. Today, together, we will provide integrated solutions spanning real time video content moderation, and AI agent This partnership combines NetEase's expertise in AI and content moderation with our leadership in real time engagement infrastructure. We believe this partnership is meaningful validation of our technology from 1 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 that Agora and Shengwang teams for their continued dedication and execution. And thank our shareholders for their ongoing trust and support.

Globally, Constitutional 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 150% sequential growth every single quarter. And as I see it today, I am 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. With that, let me turn things over to Jingbo.

Jingbo Wang: who will review our financial results. 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.

Operator: 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 Shunghwa.

Jingbo Wang: We have 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. This change aligns DBNER more closely with our quarterly revenue growth rate making it easier for investors to compare the 2. Total revenue for the first quarter reached $37.7 million representing 13.5% year over year growth. Those results exceeded the high end of our guidance range of $36 million to $37 million and reflected continued expansion of usage growth of our real time engagement services in sectors such as US live shopping, social and entertainment, and financial services.

DBNER for the first quarter was 99% compared with 95% in the first quarter of 2025. Gross profit for the first quarter 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 Sales and marketing expenses were $5.9 million in Q1. Down 4.8% year over year.

Sales and 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 Down 3.4% year over year. was $6 million in Q1. 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. Turning to the bottom line. We delivered a GAAP net income of $1.1 million in Q1, more than double the GAAP net income in the first quarter last year.

Representing a 2.9% net income margin This marks our 6th consecutive quarter of GAAP profitability and reflects continued improvement in our operating leverage. Now turning to cash flow. Operating cash flow. Including interest received was $5.7 million in Q1, was negative $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 $166 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. During the quarter, we repurchased approximately 12.5 million Class B 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 March 31, 2026. We have repurchased 174.7 million Class A ordinary shares. Or 43.7 million ADS. For approximately $156.2 million under our share repurchase program. Which represented 78.1% of a $200 million share repurchase program The current program will expire in February 2020. Now turning to guidance. Based on currently available information, we expect total revenues for the second quarter of 2026 to be between $39 million and $40 million compared to 34.3 million in the second quarter of 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 the first quarter. 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. 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 an increasingly important driver of long-term growth. Thank you all for joining today's call. Let's open it up for questions. Thank you.

Operator: 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. First question comes from the line of Harry Zhao from Bank of America Securities. Please go ahead.

Analyst (Harry Zhao): Hi. Management, for taking my questions, and congratulations on the strong first quarter and solid Q2 guidance. I have 3 questions here. The first 1, says the company, did not disclose the revenue breakdowns by region, so we would like to know the growth trend in overseas and China market. And what verticals are driving the growth behind. And secondly, in terms of the conversational AI, I would like to know the primary application scenarios at current stage and what revenue scale could the company achieve by the end of this year? And thirdly, it is about the appropriate guidance. What is the operating profit target for 2026 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. In terms of growth rate, the US business is still is still a little bit faster. and they are both approaching very healthy rates. So in terms of the demand, in both markets, I will talk about the demand in the RT market first. Tony will talk about demand in the AI market. So for RTE, in China, demand for the traditional vertical social entertainment education, most of those verticals' demand continue to recover. And in The US international markets, demand for live shopping financial services, and healthcare were among the strongest.

And we have a pipeline of new customers in these verticals as well. So overall, RT demand looks quite healthy.

Bin Zhao: About the demand on AI side, from the beginning of this year, we are closely watching the progress on our front. We were the first to introduce AI into the whole RT technology stack and offer the first generation of products empowered by those capabilities. Since then, we have 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 life. And those claims are not fake, but many of those claims are overstatements that far ahead of what is happening on the ground. Most of it oversimplifies the practical challenges and actual adoption process.

Since early last year, we have been seeing demand from call center education, digital, I think we talked about that last year. This is happening over the past few quarters in different regions. In each of those areas, we actually had certain partners and customers and worked with them to go into real production. With them, made progress in the overall experience, capital token economy, and customer use case adoption. At this moment, we see fairly large demand from the call center side. 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 for Zuzu, Similar demand is expanding. Fuzuzu's growth itself is also very promising. It can get enough monthly subscription revenue from the most sticky user group every month. So it is not just 1 time sale of the hardware toy. Seeing a similar trend in other use cases of conversational AI.

Jingbo Wang: So Tony just talk about the demand for conversational AI. So that is in So I will also answer partly the second question. So for revenue contribution this year, I would believe call center and IoT will be the biggest contributors And I think Tony has talked about that in his opening remarks that since we released our commercial AI, engine product, in March last year. Its usage has been growing at more than 150% sequential growth rate every single quarter. So also the revenue contribution at moment is still relatively low. We expect to see revenue to quickly ramp up and possibly in towards somewhere around 5% revenue contribution by year-end.

So 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. And in terms of the GAAP net profit, we expect the GAAP net income will be significantly higher than last year. And our goal is to achieve GAAP operating profit. In the second half of this year. Thanks, Benjamin.

Analyst (Harry Zhao): Very clear. Thank you. Thank you.

Operator: Just a moment for our next question, please. Next, we have rate Rachel Han from CICC. Please go ahead.

Rachel Hahn: Thanks. Hi. This is Ri Han, Rachel from CICC. Thanks for taking my questions, and congrats on another solid 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 event. So could you give us an update on how this vertical has been developing since then? And how should we think about the potential revenue contribution from overseas e commerce for the rest of 2026? My second question is domestic China business. I know we share some color on the growth drivers for the domestic business this year.

But I noticed we announced net Ease smart enterprise partnership this quarter. So how should we think about its potential impact on our Sheng Wang's growth in 2026. Thank you.

Jingbo Wang: Sure. First question, commerce use case. So I wanna say that in The US market and in probably all developed markets in general, video based live shopping is still a very nascent. We mentioned Whatnot last quarter. So after that event, very successful event, actually, the it did not turn off their user acquisition and customer user stickiness So we continue to see growing demand from that customer. In addition, we recently won another fast-growing video based e commerce customer. In US market from a competitor. And on top of that, we in the last quarter, it was a masterclass for the industry. So now everybody in the industry is watching.

And several other players are trying to host similar events in the future. We are discussing with a few of them. Already. So we do expect this vertical to have long-run growth. And we are making solid progress. On that front. So in terms of the business in China, as I said, earlier, demand from these main internet-based use cases, social entertainment, education, we see steady demand recovery. Also, still at a moderate rate. And also, from verticals such as IoT, cameras, doorbells, cars, and some other wearable devices. The demand for our technology is growing very fast. It has been very fast in the past 2-3 years. And also digital transformation customers with additional AI features.

We also see renewed demand growth from digital transformation. Traditional enterprise customers, In terms of the partnership, I think it is certainly very helpful in and of itself, but also it reflects the reflects a further consolidation of the RT market in China. Right? So recently, To just give some more examples, 1 of these recently? a cloud competitor in this market? Repurchased all of its venture capital investors and started to force more profitability rather than scale. Right? And that used to be a competitor, is now our largest partner And we also see another large private cloud vendor has. As further reduced its staff on the RTE business.

So we do believe this kind of easing competition, this trend of consolidation will gradually help our revenue growth. As well. Okay. Thanks, that is very helpful, and hope all the best. Thank you.

Rachel Hahn: Thanks.

Operator: Thank you. Just a moment with our next question, please. Last question comes from Yu from China Securities. Please go ahead.

Analyst (Yu Xing): Hi, management. Good. Thanks for taking my question, and congrats on the strong And just 2 quick ones. First, are we seeing an improvement in domestic competitive landscape? And how should that translate into pricing power and revenue growth? Also, excluding the initial gross margin drag from conversational AI, What is what is the underlying gross margin trend for our core business? Second question, as the conversational AI business's cost is part hardware. it is unique economic spending. if AI progress comes in below expectation, how should we think about our target of turning operating profit margin positive? By Q4 of 2 thousand 26.

Jingbo Wang: Sure. So first question, I am competition and the margins. So I will talk about RT and Tony will talk about So I think I just talked about let me think about the competition in the China market. We see that the market is moving toward further consolidation. That was more players who no longer come after scale. Right? So we do believe that will help with revenue growth as well as margin improvement in the coming quarters. So as you can see, overall, the gross margin in this quarter was lower compared to the same quarter last year. But that is mostly due to the initial negative gross margin of the conversational AI business. Is excluding conversational AI.

Gross margin, of the core RTE business has remained actually relatively stable in the first quarter.

Bin Zhao: And on the AI side, there is a lot of competition. For conversational AI in Silicon Valley and US market. Market is still at early stage. And there are different players trying to attack it. From quite diverse angles. Because it is still a growth market. So every company has a chance to win from different angles and still making progresses. 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 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. As you can see, most of the AI companies can only make a fraction of revenue in China market compared to their peers. The market is quite hard to get into at this moment. However, there is similar demand on conversational AI side. And the technology and product progress are also similar. Okay. So yeah.

Jingbo Wang: So in terms of the unit economics of the conversational AI product, I think it is still too early to talk about for example, in first quarter, 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 has generated no revenue but 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 goal certainly in turn positive and also be at a healthy level.

In the longer term, we actually expect the conversational AI business to generate similar, if not higher gross margin than the current RT products. because of, 1, higher pricing, and 2, the more technical differentiation and value creation for customers. Oh, as to the question about if the AI progress is expectation. But we actually, we have considered all the investments we need to make on that front. And it will not affect our goal of achieving profitability in the second half of the of this year.

Analyst (Yu Xing): Thank you.

Operator: Thank you. As a reminder, to ask a question, please press 11 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 earning release will be available on the company's website at investor.agora.io And if there is any further questions, please feel free to email the company. Thank you. Thank you. Bye-bye.

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