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Bairong's AICC Revenue Grows 52% in H1 2026 as Overall Revenue Drops

Bairong Intelligent reported a 43% fall in H1 2026 revenue but a 52% rise in AICC revenue, with new-scenario income up 195%, as it expands outcome-based AI agents beyond finance.

AI News Feed · 2026-09-02 14:39

AICC embeds AI agents into contact centers to handle inquiries, marketing, service and operations. Bairong said its AICC and enterprise-agent capabilities, honed in finance, are now being replicated into logistics, securities, airlines and other service-intensive industries. Revenue from new non-credit AICC scenarios jumped 195% to 11.26 million yuan. In logistics, a project's daily call volume rose from below 1,000 at launch to more than 15,000 by late August. For one leading securities firm, deployment expanded from about 30 seats at the start of the year to about 210 seats by July.

The overall drop was due to regulatory rules on internet-assisted lending introduced in 2025 and enforced from October of that year, plus additional measures in the first half of 2026, which led some financial institutions to suspend certain products. Bairong's AI decision-making business generated 372 million yuan, down 26%, while other businesses fell 62% to 377 million yuan, mainly because of contraction in intelligent marketing and operations for credit products. The AI decision segment retained 96% of its core-institution customers, with 141 core institutions and core revenue from banks and internet platforms up 1%.

R&D spending increased 31% to 394 million yuan, or 43% of revenue, and 901 of 1,477 employees were in R&D. CEO Zhang Shaofeng called the restructuring a strategic upgrade on an earnings call, prioritizing AICC new scenarios for resources and cross-industry replication. AICC accounted for 18.1% of total revenue in the first half, up from about 6.8% a year earlier.

The company develops its own vertical foundation models, including voice, proactive dialogue and document understanding. Zhang said phone-scenario models are mostly between 0.4B and 30B parameters, aiming to balance accuracy, stability, latency and inference cost. Unlike overseas firms such as Sierra and Decagon that build on third-party foundation models, Bairong controls pre-training, post-training and inference optimization itself. The company also relies on a data flywheel fed by real interactions and a field deployment engineering team to embed agents into client workflows. At Interspeech 2026's MLC-SLM Challenge, Bairong reported 94.84% accuracy in multilingual conversational speech understanding, ranking third globally and first among Chinese industrial competitors.

Bairong uses a Results-as-a-Service model, charging for processed call volumes and completed tasks. Contact center work has clear boundaries and documented workflows, making it a practical entry point for enterprise AI, the company said. It said customer-service and marketing AI agents have been developed since 2017. Bairong also outlined a "tech-reconstruction AI Roll-up" approach, using investment and cooperation to gain more real business entry points and scale validated agent capabilities.