Q2 2026 17 Education & Technology Group Inc Earnings Call

September 9, 2026

Operator: Good evening and good morning, ladies and gentlemen, and thank you for standing by for 17 Education & Technology Q2 2026 earnings conference call. At this time, all participants are in listen-only mode. After the management's prepared remarks, there will be a question-and-answer session. As a reminder, today's conference call is being recorded. I will now turn the meeting over to your host for today's call, Ms. Lara Zhao, 17 Education & Technology's Investor Relations Manager. Please proceed, Lara.

Operator: [Break]

Speaker #2: Good evening and good morning, ladies and gentlemen, and thank you for standing by for 17 ECTEC's second quarter 2026 earnings conference call. At this time, all participants are in listen-only mode.

Speaker #2: After management's prepared remarks, there will be a question-and-answer session. As a reminder, today's conference call is being recorded. I will now turn the meeting over to your host for today's call, Ms. Lara Zhao, 17 Education & Technology Group's investor relations manager.

Speaker #2: Please proceed, Lara.

Speaker #3: Thank you, operator. Hello, everyone, and thank you for joining us today. Our earnings release was distributed earlier today and is available on our IR website.

Laura Zhao: Thank you, operator. Hello, everyone, and thank you for joining us today. Our earnings release was distributed earlier today and is available on our IR website. Joining us today are Ms. Sishi Zhou, Chief Financial Officer, and myself, Investor Relations Manager. Sishi will walk you through our latest business performance and strategic directions, and I will then discuss our financial performance in more detail. After the prepared remarks, Sishi will be available to answer your questions during the Q&A session. Before we begin, I would like to remind you that this conference call contains forward-looking statements as defined in Section 21E of the Securities Exchange Act of 1934 and the U.S. Private Securities Litigation Reform Act of 1995.

Lara Zhao: Thank you, operator. Hello, everyone, and thank you for joining us today. Our earnings release was distributed earlier today and is available on our IR website. Joining us today are Ms. Sishi Zhou, Chief Financial Officer, and myself, Investor Relations Manager. Sishi will walk you through our latest business performance and strategic directions, and I will then discuss our financial performance in more detail. After the prepared remarks, Sishi will be available to answer your questions during the Q&A session. Before we begin, I would like to remind you that this conference call contains forward-looking statements as defined in Section 21E of the Securities Exchange Act of 1934 and the U.S. Private Securities Litigation Reform Act of 1995.

Speaker #3: Joining us today are Ms. Xishu Zhou, Chief Financial Officer, and myself, Investor Relations Manager. Xishu will walk you through our latest business performance and strategic directions, and I will then discuss our financial performance in more detail.

Speaker #3: After the prepared remarks, Xishu will be available to answer your questions during the Q&A session. Before we begin, I'd like to remind you that this conference call contains forward-looking statements as defined in Section 21(e) of the Securities Exchange Act of 1934 and the U.S.

Speaker #3: Private Securities Litigation Reform Act of 1995. These forward-looking statements are based upon management's current expectations and current market and operating conditions, and relate to events that involve known and unknown risks, uncertainties, and other factors.

Laura Zhao: These forward-looking statements are based upon management's current expectations and current market and operating conditions, and they relate to events that involve known and unknown risks, uncertainties, and other factors, all of which are difficult to predict and many of which are beyond the company's control. These risks may cause the company's actual results, performance, or achievements to differ materially. Further information regarding these and other risks, uncertainties, or factors is included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events, or otherwise, except as required under applicable law. I will now turn the call over to our Chief Financial Officer to review some of our business development and strategic direction. Sishi, please go ahead.

Lara Zhao: These forward-looking statements are based upon management's current expectations and current market and operating conditions, and they relate to events that involve known and unknown risks, uncertainties, and other factors, all of which are difficult to predict and many of which are beyond the company's control. These risks may cause the company's actual results, performance, or achievements to differ materially. Further information regarding these and other risks, uncertainties, or factors is included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events, or otherwise, except as required under applicable law. I will now turn the call over to our Chief Financial Officer to review some of our business development and strategic direction. Sishi, please go ahead.

Speaker #3: All of which are difficult to predict, and many of which are beyond the company's control. These risks may cause the company's actual results, performance, or achievements to differ materially.

Speaker #3: Further information regarding these and other risks, uncertainties, or factors is included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events, or otherwise, except as required under applicable law.

Speaker #3: I will now turn the call over to our Chief Financial Officer to review some of our business development and strategic direction. Xishu, please go ahead.

Speaker #4: Thank you, Lara. Hello, everyone. Thank you all for joining us on our second quarter 2026 earnings conference call. Before we begin, I would like to note that the financial information and the non-GAAP numbers in this release are presented on a continuing operations basis and in RMB.

Sishi Zhou: Thank you, Laura. Hello, everyone. Thank you all for joining us on our Q2 2026 earnings conference call. Before we begin, I would like to note that the financial information and the non-GAAP numbers in this release are presented on a continuing operations basis and in RMB, unless otherwise stated. Let me begin with our Q2 business highlights. We are pleased to report another quarter of strong progress. Net revenues increased 254.6% year-over-year to RMB 90.1 million, bringing H1 2026 net revenues to RMB 189.5 million, up 302.6% from the same period last year. Gross margin expanded to 69.2%, representing a year-over-year improvement of 11.7 percentage points, which is driven by the growing contribution of our AI-powered application services and ongoing optimization of our revenue mix.

Sishi Zhou: Thank you, Lara. Hello, everyone. Thank you all for joining us on our Q2 2026 earnings conference call. Before we begin, I would like to note that the financial information and the non-GAAP numbers in this release are presented on a continuing operations basis and in RMB, unless otherwise stated. Let me begin with our Q2 business highlights. We are pleased to report another quarter of strong progress. Net revenues increased 254.6% year-over-year to RMB 90.1 million, bringing H1 2026 net revenues to RMB 189.5 million, up 302.6% from the same period last year. Gross margin expanded to 69.2%, representing a year-over-year improvement of 11.7 percentage points, which is driven by the growing contribution of our AI-powered application services and ongoing optimization of our revenue mix.

Speaker #4: Unless otherwise stated, let me begin with our second quarter business highlights. We are pleased to report another quarter of strong progress. Net revenues increased 254.6% year over year to RMB 90.1 million.

Speaker #4: Bringing first half 2026 net revenues to RMB 189.5 million, up 302.6% from the same period last year. Gross margin expanded to 69.2%, representing a year-over-year improvement of 11.7 percentage points, which is driven by the growing contribution of our AI-powered application services and an ongoing optimization of our revenue mix.

Speaker #4: During the quarter, we achieved our first quarterly GAAP and non-GAAP profitability, with GAAP net income of RMB 1.1 million and adjusted net income of RMB 4.7 million.

Sishi Zhou: During the quarter, we achieved our first quarterly GAAP and non-GAAP profitability with GAAP net income of RMB 1.1 million and adjusted net income of RMB 4.7 million. We believe these results provide further validation of our strategic transformation into an AI-powered application service provider and demonstrate the improving economics and scalability of our evolving business model. Importantly, this progress was achieved while we continued to invest in AI capabilities, product innovation, and the expansion of our application ecosystem. Beyond our financial performance, we also made important progress in advancing our AI application service strategy. Over the past several years, we have built extensive experience serving education scenarios across districts, schools, teachers, and students. With the advancement of AI technologies, we are evolving from traditional digital solutions towards more deeply integrated agentic services.

Speaker #4: We believe these results provide further validation of our strategic transformation into an AI-powered application service provider and demonstrate the improving economics and scalability of our evolving business model.

Speaker #4: Importantly, this progress was achieved while we continued to invest in AI capabilities, product innovation, and the expansion of our application ecosystem. Beyond our financial performance, we also made important progress in advancing our AI application service strategy.

Speaker #4: Over the past several years, we have built extensive experience serving education scenarios across districts, schools, teachers, and students. With the advancement of AI technologies, we are evolving from traditional digital solutions toward more deeply integrated agentic services.

Speaker #4: A key milestone during the quarter was the further expansion of our collaboration with Shanghai Minhang District. Building on our long-standing partnership and existing digital teaching infrastructure, the latest phase of our collaboration has evolved from SaaS-based services toward agentic services.

Sishi Zhou: A key milestone during the quarter was the further expansion of our collaboration with the Shanghai Minhang District. Building on our long-standing partnership and existing digital teaching infrastructure, the latest phase of our collaboration has evolved from SaaS-based services towards agentic services, providing more personalized AI capabilities to teachers and embedding AI more deeply into daily teaching workflows. An important aspect of this evolution is that the procurement model is also evolving. The Minhang project adopts a service-oriented approach, combining initial system development with ongoing service components linked to actual AI usage. We believe this model provides a potential framework for scaling AI applications in education beyond the traditional one-time software deployments. Meanwhile, this represents an important validation of our strategy, moving AI from a supporting tool towards an intelligent service layer that can actively assist education professionals in real-world scenarios.

Speaker #4: We are providing more personalized AI capabilities to teachers and embedding AI more deeply into daily teaching workflows. An important aspect of this evolution is that the procurement model is also evolving.

Speaker #4: The Minhang project adopts a service-oriented approach, combining initial system development with ongoing service components linked to actual AI usage. We believe this model provides a potential framework for scaling AI applications in education, beyond traditional one-time software deployments.

Speaker #4: Meanwhile, this represents an important validation of our strategy—moving AI from a supporting tool toward an intelligent service layer that can actively assist education professionals in real-world scenarios.

Speaker #4: Another important milestone during the quarter was the introduction of our personalized AI agent for individual teachers. These teacher-facing AI agents are designed to support key teaching workflows, including assessment, content generation, and learning analytics.

Sishi Zhou: Another important milestone during the quarter was the introduction of our personalized AI agent for individual teachers. This teacher-facing AI agent is designed to support key teaching workflows, including assessment, content generation, and learning analytics. Specifically, it helps teacher automate tasks such as essay grading and class analysis, generate personalized assessments, and translate learning data into differentiated teaching recommendations. Our vision is not to replace teachers, but to empower educators by combining AI's capabilities with teachers' own experience in the classroom context. We are also expanding access to teacher-facing AI applications to broaden adoption and gather real-world feedback as we continue to validate product market fit.

Speaker #4: Specifically, it helps teachers automate tasks such as essay grading and class analysis, generate personalized assessments, and translate learning data into differentiated teaching recommendations. Our vision is not to replace teachers, but to empower educators by combining AI capabilities with teachers' own experience and classroom context.

Speaker #4: We are also expanding access to teacher-facing AI applications to broaden adoption and gather real-world feedback as we continue to validate product-market fit. Together with our student-facing personalized learning services and regional AI applications, these expand our AI application capabilities across three core scenarios.

Sishi Zhou: Together with our student-facing personalized learning services and regional AI applications, this expands our AI application capabilities across three core scenarios: educational administration, teaching, and personalized learning, marking the establishment of an agentic ecosystem spanning the full workflow of teaching, learning, administration, assessment, and research. Strategically, this three-layer AI agentic system also aligns with the logic of our G, B, C, and synergistic growth flywheel. To further elaborate the integrated ecosystem, our G-end business allows us to validate AI applications at regional scale and establish benchmark use cases in complex education environments. For example, in Minhang District, our digital teaching systems have already been deployed across more than 3,000 classes with teacher and student coverage of 97.8%. Based on this foundation, we are continuing to upgrade regional AI capabilities from traditional digital tools toward more proactive agentic services.

Speaker #4: Education administration, teaching, and personalized learning. Marking the establishment of an agentic ecosystem spanning the full workflow of teaching, learning, administration, assessment, and research. Strategically, this three-layer AI agentic system also aligns with the logic of our GBC and the synergistic growth flywheel.

Speaker #4: To further elaborate the integrated ecosystem, our G&A business allows us to validate AI applications at a regional scale and establish benchmark use cases in complex education environments.

Speaker #4: For example, in Minhang District, our digital teaching systems have already been deployed across more than 3,000 classes, with teacher and student coverage of 97.8%.

Speaker #4: Based on this foundation, we are continuing to upgrade regional AI capabilities from traditional digital tools toward more proactive agentic services. Our B2B business enables us to replicate these capabilities across schools and embed AI into daily teaching workflows.

Sishi Zhou: Our B-end business enables us to replicate these capabilities across schools and embed AI into daily teaching workflows, creating scalable pathways for broader adoption. We are also seeing increasing interest from school-based customers in adopting more integrated AI services, which provides additional opportunities to expand beyond our existing regional deployments. Our C-end business, led by Yiqi Aixue, continues to serve as important commercialization engine, delivering personalized AI learning services directly to students and families. Together, these three areas reinforces each one another. G validates, B replicates, and C monetizes and scales. The trust, distribution, capabilities, and education insights accumulated across these scenarios continuously strengthen our ability to develop and commercialize AI application services. Turning to our financial position, the improving business performance has also strengthened our financial flexibility. As of the quarter end, we maintained a strong cash position of RMB 456.9 million.

Speaker #4: Creating scalable pathways for broader adoption. We are also seeing increasing interest from school-based customers in adopting more integrated AI services, which provides additional opportunities to expand beyond our existing regional deployments.

Speaker #4: Our C-end business, led by Ichi Aishie, continues to serve as an important commercialization engine, delivering personalized AI learning services directly to students and families.

Speaker #4: Together, these three areas reinforce each other. G validates, B replicates, and C monetizes and scales. The trust, distribution, capabilities, and educational insights accumulated across these scenarios continuously strengthen our ability to develop and commercialize AI application services.

Speaker #4: Turning to our financial position, the improving business performance has also strengthened our financial flexibility. As of the quarter end, we maintained a strong cash position of RMB 456.9 million.

Speaker #4: Providing sufficient resources to support continued investment in AI capabilities, product innovation, and long-term growth opportunities. On September 3rd, our board of directors authorized a share repurchase program of up to $10 million worth of its ordinary shares.

Sishi Zhou: Providing sufficient resources to support continued investment in AI capabilities, product innovation, and long-term growth opportunities. on 3 September, our board of directors has authorized a share repurchase program of up to $10 million US worth of its ordinary shares, including in the form of American depository shares, during a 12-month period starting from 3 September 2026, funded from our existing cash balance. The program reflects our confidence in our long-term strategy and our commitment to disciplined capital allocation and long-term shareholder value creation. Looking ahead, we believe the next stage of growth will come from expanding AI application services across more education scenarios. In G-end, we will continue to develop benchmark projects that demonstrate the value of AI in large-scale education environments. In B-end, we will continue to productize and replicate proven capabilities across school-based scenarios.

Speaker #4: Including in the form of American Depository Shares. During a 12-month period, starting from September 3, 2026, funded from our existing cash balance. The program reflects our confidence in our long-term strategy and our commitment to disciplined capital allocation and long-term shareholder value creation.

Speaker #4: Looking ahead, we believe the next stage of growth will come from expanding AI application services across more education scenarios. In Q2, we will continue to develop benchmark projects in large-scale education environments.

Speaker #4: In B end, we will continue to productize and replicate proven capabilities across school-based scenarios. In C end, we will continue to enhance personalized AI learning services while exploring additional individual user applications.

Sishi Zhou: In C-end, we will continue to enhance personalized AI learning services while exploring additional individual user applications. Through this integrated approach, we aim to create a reinforcing cycle where real education scenarios improve our AI capabilities, and improved AI capabilities create greater value for users. We believe our accumulated education insights, AI capabilities, and growing application ecosystem provide a strong foundation for continued innovation and long-term value creation. This concludes our business update. I will now turn the call over to Laura to walk you through our financial performance in detail. Thank you.

Sishi Zhou: In C-end, we will continue to enhance personalized AI learning services while exploring additional individual user applications. Through this integrated approach, we aim to create a reinforcing cycle where real education scenarios improve our AI capabilities, and improved AI capabilities create greater value for users. We believe our accumulated education insights, AI capabilities, and growing application ecosystem provide a strong foundation for continued innovation and long-term value creation. This concludes our business update. I will now turn the call over to Lara to walk you through our financial performance in detail. Thank you.

Speaker #4: Through this integrated approach, we aim to create a reinforcing cycle where real education scenarios improve our AI capabilities, and improved AI capabilities create greater value for users.

Speaker #4: We believe our accumulated education insights, AI capabilities, and growing application ecosystem provide a strong foundation for continued innovation and long-term value creation. This concludes our business update.

Speaker #4: I will now turn the call over to Lara to walk you through our financial performance in detail. Thank you.

Speaker #3: Thank you. I will now walk you through our financial and operating results for the second quarter of 2026. Please note that all financial figures are presented in RMB terms unless otherwise stated.

Laura Zhao: Thank you, Sishi. I will now walk you through our financial and operating results for Q2 2026. Please note that all financial figures are presented in RMB terms unless otherwise stated. We are pleased to report strong financial results for Q2 2026, highlighted by the company's first quarterly net profit on GAAP and non-GAAP basis since its strategic transformation. Let me take you through the details. Net revenues. Net revenues for Q2 2026 were RMB 90.1 million, $13.3 million US, representing a year-over-year increase of 254.6% from RMB 25.4 million in Q2 2025, and bringing the H1 2026 net revenues to RMB 189.5 million, compared with RMB 47.1 million in H1 2025.

Lara Zhao: Thank you, Sishi. I will now walk you through our financial and operating results for Q2 2026. Please note that all financial figures are presented in RMB terms unless otherwise stated. We are pleased to report strong financial results for Q2 2026, highlighted by the company's first quarterly net profit on GAAP and non-GAAP basis since its strategic transformation. Let me take you through the details. Net revenues. Net revenues for Q2 2026 were RMB 90.1 million, $13.3 million US, representing a year-over-year increase of 254.6% from RMB 25.4 million in Q2 2025, and bringing the H1 2026 net revenues to RMB 189.5 million, compared with RMB 47.1 million in H1 2025.

Speaker #3: We are pleased to report strong financial results for the second quarter of 2026, highlighted by the company's first quarterly net profit on both GAAP and non-GAAP bases since its strategic transformation. Let me take you through the details.

Speaker #3: Net revenues. Net revenues for the second quarter of 2026 were 90.1 million RMB, US 13.3 million US dollars, representing an year-over-year increase of 254.6% from 25.4 million RMB in the second quarter of 2025.

Speaker #3: And bringing the first half of 2026 net revenues to RMB 189.5 million, compared with RMB 47.1 million in the first half of 2025. The substantial growth was primarily driven by the continued expansion of EGI Share, our consumer-facing AI-powered membership product, complemented by the ongoing contributions from district-level and school-based subscription projects.

Laura Zhao: The substantial growth was primarily driven by the continued expansion of Yiqi Aixue, our consumer-facing AI-powered membership product, complemented by the ongoing contributions from district-level and school-based subscription projects. Cost of revenues for the second quarter of 2026 were RMB 27.8 million, representing a year-over-year increase of 157.2% from RMB 10.8 million in the second quarter of 2025, which was mainly due to the continued growth of Yiqi Aixue and the related service delivery costs. Gross profit for the second quarter of 2026 was RMB 62.3 million, compared with RMB 14.6 million in the second quarter of 2025. Gross margin for the second quarter of 2026 was 69.2%, compared with 57.5% in the second quarter of 2025, representing an improvement of 11.7 percentage points, and up from 61.9% in the first quarter of 2026.

Lara Zhao: The substantial growth was primarily driven by the continued expansion of Yiqi Aixue, our consumer-facing AI-powered membership product, complemented by the ongoing contributions from district-level and school-based subscription projects. Cost of revenues for the second quarter of 2026 were RMB 27.8 million, representing a year-over-year increase of 157.2% from RMB 10.8 million in the second quarter of 2025, which was mainly due to the continued growth of Yiqi Aixue and the related service delivery costs. Gross profit for the second quarter of 2026 was RMB 62.3 million, compared with RMB 14.6 million in the second quarter of 2025. Gross margin for the second quarter of 2026 was 69.2%, compared with 57.5% in the second quarter of 2025, representing an improvement of 11.7 percentage points, and up from 61.9% in the first quarter of 2026.

Speaker #3: Cost of revenues. Cost of revenues for the second quarter of 2026 were RMB 27.8 million, representing a year-over-year increase of 157.2% from RMB 10.8 million in the second quarter of 2025, which was mainly due to the continued growth of EGI share and related service delivery costs.

Speaker #3: Gross profit for the second quarter of 2026 was RMB 62.3 million, compared with RMB 14.6 million in the second quarter of 2025. Gross margin for the second quarter of 2026 was 69.2%, compared with 57.5% in the second quarter of 2025.

Speaker #3: Representing an improvement of 11.7 percentage points, and up from 61.9% in the first quarter of 2026. The increase in gross margin was primarily attributable to the growing contribution of the company's consumer-facing AI-powered application services and the continued optimization of the company's revenue mix.

Laura Zhao: The increase in gross margin was primarily attributable to the growing contribution of the company's consumer-facing AI-powered application services and the continued optimization of the company's revenue mix. Total operating expenses for the second quarter of 2026 were RMB 63.0 million, including share-based compensation expenses of RMB 3.6 million, representing a year-over-year increase of 46.2% from RMB 43.1 million in the second quarter of 2025, significantly slower than the revenue growth, reflecting the growing operating leverage of our business model. Sales and marketing expenses for the second quarter of 2026 were RMB 26.9 million, including share-based compensation expenses of RMB 1.1 million, representing a year-over-year increase of 92.2% from RMB 14.0 million in the second quarter of 2025. The increase was primarily attributable to the increased sales and marketing investment activities in support of the continued expansion of Yiqi Aixue.

Lara Zhao: The increase in gross margin was primarily attributable to the growing contribution of the company's consumer-facing AI-powered application services and the continued optimization of the company's revenue mix. Total operating expenses for the second quarter of 2026 were RMB 63.0 million, including share-based compensation expenses of RMB 3.6 million, representing a year-over-year increase of 46.2% from RMB 43.1 million in the second quarter of 2025, significantly slower than the revenue growth, reflecting the growing operating leverage of our business model. Sales and marketing expenses for the second quarter of 2026 were RMB 26.9 million, including share-based compensation expenses of RMB 1.1 million, representing a year-over-year increase of 92.2% from RMB 14.0 million in the second quarter of 2025. The increase was primarily attributable to the increased sales and marketing investment activities in support of the continued expansion of Yiqi Aixue.

Speaker #3: Total operating expenses for the second quarter of 2026 were RMB 63.0 million, including share-based compensation expenses of RMB 3.6 million, representing a year-over-year increase of 46.2% from RMB 43.1 million in the second quarter of 2025.

Speaker #3: Significantly slower than the revenue growth, reflecting the growing operating leverage of our business model. Sales and marketing expenses for the second quarter of 2026 were RMB 26.9 million, including share-based compensation expenses of RMB 1.1 million, representing a year-over-year increase of 92.2% from RMB 14.0 million in the second quarter of 2025.

Speaker #3: The increase was primarily attributable to the increased sales and marketing investment activities in support of the continued expansion of ETI's share. Research and development expenses for the second quarter of 2026 were RMB 20.0 million, including share-based compensation expenses of RMB 0.9 million, representing a year-over-year increase of 66.8% from RMB 12.0 million in the second quarter of 2025.

Laura Zhao: Research and development expenses for the second quarter of 2026 were RMB 20.0 million, including share-based compensation expenses of RMB 0.9 million, representing a year-over-year increase of 66.8% from RMB 12 million in the second quarter of 2025. The increase in research and development expenses was primarily attributable to the higher personnel-related costs associated with research and development activities to support a broader range of AI application scenarios. General and administrative expenses for the second quarter of 2026 were RMB 16.0 million, including share-based compensation expenses of RMB 1.5 million, representing a year-over-year decrease of 6.1% from RMB 17.1 million in the second quarter of 2025. The decrease was primarily attributable to lower share-based compensation expenses and disciplined cost management. Loss from operations for the second quarter of 2026 were RMB 0.6 million compared with RMB 28.5 million in the second quarter of 2025, approaching operating break-even.

Lara Zhao: Research and development expenses for the second quarter of 2026 were RMB 20.0 million, including share-based compensation expenses of RMB 0.9 million, representing a year-over-year increase of 66.8% from RMB 12 million in the second quarter of 2025. The increase in research and development expenses was primarily attributable to the higher personnel-related costs associated with research and development activities to support a broader range of AI application scenarios. General and administrative expenses for the second quarter of 2026 were RMB 16.0 million, including share-based compensation expenses of RMB 1.5 million, representing a year-over-year decrease of 6.1% from RMB 17.1 million in the second quarter of 2025. The decrease was primarily attributable to lower share-based compensation expenses and disciplined cost management. Loss from operations for the second quarter of 2026 were RMB 0.6 million compared with RMB 28.5 million in the second quarter of 2025, approaching operating break-even.

Speaker #3: The increase in research and development expenses was primarily attributable to higher personnel-related costs associated with research and development activities to support a broader range of AI application scenarios.

Speaker #3: General and administrative expenses for the second quarter of 2026 were RMB 16.0 million, including share-based compensation expenses of RMB 1.5 million, representing a year-over-year decrease of 6.1% from RMB 17.1 million in the second quarter of 2025.

Speaker #3: The decrease was primarily attributable to lower share-based compensation expenses and disciplined cost management. Loss from operations for the second quarter of 2026 was RMB 0.6 million, compared with RMB 28.5 million in the second quarter of 2025.

Speaker #3: Approaching operating break-even. As a percentage of net revenues, loss from operations improved to negative 0.7%, compared with negative 112.0% in the second quarter of 2025.

Laura Zhao: As a percentage of net revenues, loss from operations improved to -0.7% compared with -112.0% in the second quarter of 2025. Net income for the second quarter of 2026 was RMB 1.1 million compared with net loss of RMB 26.0 million in the second quarter of 2025, marking the company's first quarterly GAAP net profit since its strategic transformation. Net income as a percentage of net revenues was 1.2% in the second quarter of 2026, compared with -102.1% in the second quarter of 2025. Adjusted net income for the second quarter of 2026, which included share-based compensation expenses of RMB 3.6 million, was RMB 4.7 million compared with adjusted net loss non-GAAP of RMB 18.9 million in the second quarter of 2025.

Lara Zhao: As a percentage of net revenues, loss from operations improved to -0.7% compared with -112.0% in the second quarter of 2025. Net income for the second quarter of 2026 was RMB 1.1 million compared with net loss of RMB 26.0 million in the second quarter of 2025, marking the company's first quarterly GAAP net profit since its strategic transformation. Net income as a percentage of net revenues was 1.2% in the second quarter of 2026, compared with -102.1% in the second quarter of 2025. Adjusted net income for the second quarter of 2026, which included share-based compensation expenses of RMB 3.6 million, was RMB 4.7 million compared with adjusted net loss non-GAAP of RMB 18.9 million in the second quarter of 2025.

Speaker #3: Net income for the second quarter of 2026 was RMB 1.1 million, compared with a net loss of RMB 26.0 million in the second quarter of 2025, marking the company's first quarterly GAAP net profit since its strategic transformation.

Speaker #3: Net income as a percentage of net revenues was 1.2% in the second quarter of 2026, compared with negative 102.1% in the second quarter of 2025.

Speaker #3: Adjusted net income for the second quarter of 2026, which included share-based compensation expenses of RMB 3.6 million, was RMB 4.7 million, compared with an adjusted net loss (non-GAAP) of RMB 16.9 million in the second quarter of 2025.

Speaker #3: Adjusted net income non-GAAP as a percentage of net revenues was 5.2% in the second quarter of 2026, compared with negative 74.3% in the second quarter of 2025.

Laura Zhao: Adjusted net income non-GAAP as a percentage of net revenues was 5.2% in Q2 2026 compared with negative 74.3% in Q2 2025. Please refer to the table captioned "Reconciliations of non-GAAP measures to the most comparable GAAP measures" at the end of this press release for the reconciliation of net income or loss under US GAAP to the adjusted net income or loss non-GAAP. Cash and cash equivalents, restricted cash, and term deposits were RMB 456.9 million as of 30 June 2026, compared with RMB 407.0 million as of 31 December 2025. The substantial increase in cash was driven by both our return to profitability and improved cash generation from operations. We maintain a robust cash position that provides financial flexibility to support continued investment in product innovation, improved AI capabilities, and other strategic growth opportunities ahead.

Lara Zhao: Adjusted net income non-GAAP as a percentage of net revenues was 5.2% in Q2 2026 compared with negative 74.3% in Q2 2025. Please refer to the table captioned "Reconciliations of non-GAAP measures to the most comparable GAAP measures" at the end of this press release for the reconciliation of net income or loss under US GAAP to the adjusted net income or loss non-GAAP. Cash and cash equivalents, restricted cash, and term deposits were RMB 456.9 million as of 30 June 2026, compared with RMB 407.0 million as of 31 December 2025. The substantial increase in cash was driven by both our return to profitability and improved cash generation from operations. We maintain a robust cash position that provides financial flexibility to support continued investment in product innovation, improved AI capabilities, and other strategic growth opportunities ahead.

Speaker #3: Please refer to the table captioned "Reconciliations of Non-GAAP Measures" to the most comparable GAAP measures at the end of this press release for the reconciliation of net income or loss under US GAAP to the adjusted net income or loss non-GAAP.

Speaker #3: Cash and cash equivalents, restricted cash, and term deposits were RMB 456.9 million as of June 30, 2026, compared with RMB 407.0 million as of December 31, 2025.

Speaker #3: The substantial increase in cash was driven by our return to profitability and improved cash generation from operations. We maintain a robust cash position that provides financial flexibility to support continued investment in product innovation, improved AI capabilities, and other strategic growth opportunities ahead.

Speaker #3: Going forward, we remain steadfast in our role as an AI application service provider, driving AI to fully empower large-scale, personalized education for all. With that, we conclude our prepared remarks.

Laura Zhao: Going forward, we remain steadfast in our role as an AI application service provider, driving AI to fully empower large-scale personalized education for all. With that, we conclude our prepared remarks. Thank you. Operator, we are now ready to begin the Q&A session.

Lara Zhao: Going forward, we remain steadfast in our role as an AI application service provider, driving AI to fully empower large-scale personalized education for all. With that, we conclude our prepared remarks. Thank you. Operator, we are now ready to begin the Q&A session.

Speaker #3: Thank you. Operator, we are now ready to begin the Q&A session.

Speaker #1: Thank you. To ask a question now, 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.

Operator: Thank you. To ask a question now, please press *11 on your telephone and wait for your name to be announced. To withdraw your question, please press *11 again. There may be a short pause as we compile the Q&A roster. Again, that's *11 for questions. One moment while this question. This question comes from the line of William Gregovski from Greenridge Global. Please ask your question. William, your line is open.

Speaker #1: There may be a short pause as we compile the Q&A roster. Again, that's star one-one for questions. One moment while we queue this question. Now, this question comes from the line of William Gregorzewski from Green Ridge Global.

Speaker #1: Please ask your question, William. Your line is open.

William Gregovski: Hi, fantastic quarter. We're closing in on a year since you guys announced the C-end product. How has that performed relative to your initial expectations, and what kind of growth do you see going forward for that?

William Gregozeski: Hi, fantastic quarter. We're closing in on a year since you guys announced the C-end product. How has that performed relative to your initial expectations, and what kind of growth do you see going forward for that?

Speaker #2: Hi. Fantastic quarter. We're closing in on a year since you guys announced the CEND product. How has that performed relative to your initial expectations, and what kind of growth do you see going forward for that?

Speaker #4: Oh, okay. William, thanks for the question. We are very encouraged by the progress of our consumer business since the introduction of ETI Share in late 2025.

Laura Zhao: Okay, William, thanks for the question. We are very encouraged by the progress of our consumer business since the introduction of Yiqi Aixue in late 2025, actually. The business has developed into an important growth engine for the company faster than we initially anticipated. More importantly, we believe the progress to date has validated our core thesis that combining our educational insights, personalized learning capabilities in AI into an integrated consumer-facing service that can create meaningful value for students and families.

Sishi Zhou: Okay, William, thanks for the question. We are very encouraged by the progress of our consumer business since the introduction of Yiqi Aixue in late 2025, actually. The business has developed into an important growth engine for the company faster than we initially anticipated. More importantly, we believe the progress to date has validated our core thesis that combining our educational insights, personalized learning capabilities in AI into an integrated consumer-facing service that can create meaningful value for students and families.

Speaker #4: Actually, the business has developed into an important growth engine for the company, faster than we initially anticipated. More importantly, we believe the progress to date has validated our core thesis: that combining our educational insights, personalized learning capabilities, and AI into an integrated consumer-facing service can create meaningful value for students and families.

Speaker #4: The financial results provide tangible evidence of that progress. As noted in the earnings call, we are not only seeing strong top-line growth, but also increasingly encouraging economics as the business scales.

Sishi Zhou: The financial results provide tangible evidence for that progress, as noted in the earning call. We are not only seeing strong top-line growth, but also increasingly encouraging economics as the business scales. Looking forward, we remain optimistic about the long-term opportunity, but I would not extrapolate any single quarter into a specific growth trajectory. There may be seasonality and quarterly fluctuations as we continue to scale. What gives us confidence is that the foundation for growth is becoming broader. In addition to each issue itself, our district and school-based presence continues to strengthen our data, distribution, and trust advantages. We are also extending our consumer-facing AI applications from students and families to individual teachers through our new teacher agent, as noted.

Speaker #4: And looking forward, we remain optimistic about the long-term opportunity. I would not extrapolate any single quarter into a specific growth trajectory; there may be seasonality and quarterly fluctuations as we continue to scale.

Speaker #4: And what gives us confidence is that the foundation for growth is becoming broader. In addition to each issue itself, our district and school-based presence continues to strengthen our data, distribution, and trust advantages.

Speaker #4: We are also extending our consumer-facing AI applications from students and families to individual teachers through our new Teacher Agent, as noted. So over time, we see an opportunity to serve a broader base of individual users with personalized AI application services, while leveraging the ecosystem we have built across different education scenarios.

Sishi Zhou: Over time, we see an opportunity to serve a broader base of individual users with personalized AI application services while leveraging the ecosystem we have built across different education scenarios. Thank you.

Speaker #4: Thank you.

William Gregovski: Great. Can you just talk generally about the shape of the B-end and G-end pipeline?

William Gregozeski: Great. Can you just talk generally about the shape of the B-end and G-end pipeline?

Speaker #2: Great. And then can you just talk generally about the shape of the B-end and G-end pipeline?

Speaker #4: Okay, sure. We continue to see opportunities across both district and school-based scenarios. But I think the more important development is not only the simple size of the pipeline.

Sishi Zhou: Okay, sure. We continue to see opportunities across both district and school-based scenarios. I think the more important development is not only the simple size of the pipeline, it is how the nature of customer demand is evolving. A good example is Minhang district. In the latest phase of our collaboration, engagement has evolved from the purchase of SaaS-based services toward agentic services, providing personalized AI agents to teachers across the district. We view this as an important validation of our strategy, actually. It demonstrates that customers are beginning to move beyond purchasing digital tools toward adopting AI services that are more deeply embedded into everyday education workflows. Equally important, we are beginning to see these capabilities replicated beyond district-level projects. Some of our core school-based customers are also showing interest of upgrading from existing offerings to agentic services.

Speaker #4: It is how the nature of customer demand is evolving. A good example is Ninghang District. In the latest phase of our collaboration, engagement has evolved from the purchase of SaaS-based services toward agentic services.

Speaker #4: Providing personalized AI agents to teachers across the district—and we view this as an important validation of our strategy, actually. It demonstrates that customers are beginning to move beyond purchasing digital tools toward adopting AI services that are more deeply embedded into everyday education workflows.

Speaker #4: And equally important, we are beginning to see these capabilities replicated beyond the district-level projects. Some of our core school-based customers are also showing interest in upgrading from existing offerings to agentic services.

Speaker #4: This gives us early evidence that capabilities validated in a large-scale regional environment can be productized and extended into broader school-based scenarios. So, strategically, I always think that G and B end somewhat differently from traditional project businesses.

Sishi Zhou: This gives us early evidence that capabilities validated in a larger scale regional environment can be productized and extended into broader school-based scenarios. Strategically, we think that G and B end somewhat differently from traditional project businesses, which is that G-end allows us to validate and establish benchmark AI applications at scale. B-end allows us to replicate those capabilities across schools and embed them into daily teaching workflows. Together, G and B provide important distribution, trust, and user touch points that can support the continued growth of our C-end business. We will continue to remain selective on new G-end and B-end opportunities, focusing on projects that are strategically aligned, replicable, and commercially sound. Yeah. Thank you.

Speaker #4: Which is like that G end allows us to validate and establish benchmark AI applications at scale. B end allows us to replicate those capabilities across schools and embed them into daily teaching workflows.

Speaker #4: And together, G and B provide important distribution, trust, and user touchpoints that can support the continued growth of our C-end business. We will continue to remain selective on new G-end and B-end opportunities.

Speaker #4: Focusing on projects that are strategically aligned, replicable, and commercially sound. Yeah. Thank you.

Speaker #2: Great. Thank you.

William Gregovski: Great. Thank you.

William Gregozeski: Great. Thank you.

Speaker #1: Thank you. Once again, if you wish to ask a question now, please press star one one on your telephone keypad. It's star one one for questions.

Operator: Thank you. Once again, if you wish to ask a question now, please press star 1 1 on your telephone keypad. It is star 1 1 for questions. Thank you. I am showing no further questions. I will now turn the conference back to Ms. Laura Zhao for closing comments.

Speaker #1: Thank you. I'm showing no further questions. I'll now turn the conference back to Ms. Laura Cho for closing comments.

Speaker #5: Thank you, operator. In closing, on behalf of the 17 Education & Technology Group management team, we'd like to thank you for your participation in today's call. If you require any further information, please feel free to contact us directly.

Laura Zhao: Thank you, operator. In closing, on behalf of 17EdTech's management team, we would like to thank you for your participation in today's call. If you require any further information, please feel free to contact us directly. We appreciate your continued interest and support. Thank you for joining us today. This concludes the call.

Lara Zhao: Thank you, operator. In closing, on behalf of 17 Education & Technology's management team, we would like to thank you for your participation in today's call. If you require any further information, please feel free to contact us directly. We appreciate your continued interest and support. Thank you for joining us today. This concludes the call.

Speaker #5: We appreciate your continued interest and support. Thank you for joining us today. This concludes the call.

Operator: Thank you for your participation in today's conference. This does conclude the program. You may now disconnect your lines.