Bairong Announces 2026 Interim Results: AICC Achieves Key Milestone in Cross-Industry Replication, AI Customer Service Agents Unlock New Growth Opportunities

On August 31, 2026, Bairong (06608.HK) announced its interim results for 2026. This marked the company’s first earnings release since its stock short name officially changed from “Bairong Yun-W” to “Bairong AI-W” on August 14.

The key takeaway: AICC takes center stage in the company’s strategic transformation

A notable change in the interim report is the reclassification of revenue by business type. “AICC business” is now reported separately, primarily covering intelligent customer service and marketing solutions powered by the company’s proprietary AI VoiceGPT technology for clients in new application scenarios across securities, banking, telecommunications, logistics and other industries.

AICC business: Revenue growth and expansion into new industries

During the reporting period, revenue from businesses powered by AICC technology recorded substantial year-on-year growth, with new AICC business serving clients in new application scenarios growing significantly.

Bairong has also recently demonstrated its algorithmic capabilities through strong results in leading international competitions. In July 2026, its algorithm team secured third place globally and ranked first among industry participants from China in Task 2, “Multilingual Conversational Speech Understanding,” of the INTERSPEECH 2026 MLC-SLM 2026 Challenge. Competing against more than 110 teams worldwide, the team achieved an official accuracy score of 94.84% with its proprietary “Dynamic Question-Aware Evidence Routing” framework.

More recently, BR-Voice delivered another strong performance in the SmartGlasses Challenge, held under the IEEE SLT 2026 flagship conference. Jointly launched by Northwestern Polytechnical University’s ASLP Lab, Huawei, Shanghai Jiao Tong University, Nanjing University, the University of Science and Technology of China, Nanyang Technological University, Rokid and other organizations, the competition attracted 77 teams. BR-Voice placed in the global top five across all four tasks and ranked second globally in both spoken language understanding (SLU) tasks.

The two competitions tested different capabilities: the first assessed the ability to understand complex, extended conversations; the second evaluated end-to-end performance—from accurately capturing speech to understanding it—in wearable-device scenarios involving multiple speakers and real-world conditions.

Following the reporting period, the Group was named to Internet Weekly’s “2026 Top 50 Enterprise AI Agent Applications” list for its BR-Voice full-stack speech technology suite.

Cross-industry deployment: A landmark logistics project passes a key validation milestone

During the reporting period, Bairong achieved a substantive breakthrough in replicating its AICC capabilities across industries. Its first successful expansion of AICC from financial services into logistics validated the cross-industry transferability of its “silicon-based workforce” business model. The logistics project was awarded and contracted, completed its proof-of-concept (POC) run, and began gradually scaling up in late July.

A key concern among market participants had been whether the company’s AICC capabilities were limited to financial services. The logistics deployment and the results observed at this flagship client have begun to address that concern. Since launch, daily call volumes handled by its AI customer service agents have risen from fewer than 1,000 initially to more than 15,000, with the longest calls exceeding 20 minutes. This landmark logistics deployment represents the first major validation milestone for the company’s AI Rollup strategy.

Progress in the securities sector has also been significant. As of July 2026, 13 securities firms had either signed contracts or were in the contracting process. After validating deployment results, one leading securities firm proactively expanded its AI customer service workforce from approximately 30 seats at the beginning of the year to around 210.

The company’s medium-term cross-industry expansion priorities include logistics, aviation, securities, banking, telecommunications and insurance. These industries feature a concentration of leading enterprises and substantial consumer interaction volumes, providing ample demand for large-scale deployment of AI customer service agents.

Core competitive strengths: A complete system from domain-specific foundation models to production deployment

Bairong’s competitive advantage lies in an integrated system that connects model development directly with real-world deployment.

A differentiated approach to domain-specific foundation models. While general-purpose large language models aim to address a broad range of tasks, Bairong focuses on telephone-based customer service. Traditional telephone systems operate within a highly constrained acoustic channel, sampling audio at 8,000 times per second, compared with 16,000 times per second for internet audio. General-purpose models often struggle in this environment, while Bairong uses smaller, specialized models to perform domain-specific tasks with precision. Flexible deployment options support both on-premises implementation to meet data security requirements and elastic scaling in line with business volumes.

Production-grade capabilities in telecommunications engineering and delivery. Models are only the starting point for deploying AI in telephone-based applications. Bairong has independently developed end-to-end telecommunications engineering capabilities, including softswitches, high-concurrency scheduling, business system integration and call-recording quality assurance. Many AI vendors lack these capabilities, while reliance on external integration can significantly increase project complexity and implementation costs. In narrowband speech environments, the company continues to refine noise reduction, interruption detection and conversational turn-taking to ensure stable AI performance over real telephone lines.

The company continuously identifies positive and negative user feedback from production deployments and converts those signals into training material for reinforcement learning. This has established a functioning feedback loop: business deployment generates user feedback, which supports model iteration and, in turn, improves business performance.

The FDE team: Bringing technology into the client’s day-to-day operations. Bairong has a team of forward-deployed engineers (FDEs) who work closely with clients on the ground. Their role extends well beyond delivering a model. They first assess business requirements, service-level expectations, daily inbound call volumes, transfer-to-human rates, available knowledge bases and system interfaces that need to be connected.

They then identify the business processes best suited for AI adoption and convert manual procedures into AI workflows, creating an end-to-end process spanning user interaction, task execution, system updates and final delivery. After launch, they continue to iterate based on operational results, embedding enterprise AI agents directly into clients’ business processes.

Commercialization: RaaS aligns revenue growth with clients’ business volumes

The company primarily monetizes its offerings through a RaaS (Result as a Service) model. Pricing mechanisms include charges per successfully completed ticket or qualifying call resolved without human handoff, fees based on the number of AI agents deployed, and revenue sharing linked to business volumes generated.

For logistics clients, for example, the fee per successfully handled call is lower than the corresponding human labor cost, allowing clients to measure their return on investment directly. As processing volumes rise, Bairong’s revenue grows alongside its clients’ business volumes.

Management outlook: Validate, replicate, then scale

Management stated that the company will steadily expand AICC into new application scenarios by following a “validate, replicate, then scale” approach. The next phase will focus on deepening engagement with flagship clients already using its solutions, expanding AI deployments within existing accounts, and replicating proven solutions across other clients in the same industries. Building on this foundation, the company will continue to enter additional industries.

Financial performance

During the reporting period, the company recorded revenue of RMB914 million and a net loss of RMB322 million, compared with a net profit of approximately RMB201 million in the same period last year. The decline was primarily attributable to lower revenue from certain established businesses affected by industry policies, alongside continued increases in AI research and development investment.

Although current financial performance remains under pressure, breakthroughs in new AICC business and deployments across different application scenarios are opening up new growth opportunities. According to the profit warning announcement, revenue from businesses powered by AICC technology recorded substantial year-on-year growth, while new business serving clients in new application scenarios grew significantly. The company maintains ample cash reserves and has no interest-bearing debt.

From “Bairong Yun” to “Bairong AI,” and from financial services to logistics, securities and other industries, Bairong is placing AICC at the heart of its growth strategy as it accelerates the transition from building capabilities to realizing commercial value at scale.