Bairong's AI agents go to work at enterprises: 15,000 calls a day, paid by results

Enterprise AI agents are moving from concept demos into real production workloads. According to QbitAI, Bairong's "silicon-based employees" have been deployed at enterprise customers in batches, offering a fresh reference case for enterprise-grade agent adoption.

The most visible role among these deployed agents is AI customer service: a single deployment can handle roughly 15,000 calls per day, absorbing large volumes of repetitive, high-frequency customer interactions.

Instead of conventional per-seat or subscription pricing, Bairong operates a results-based model — the agents only get "paid" when they actually deliver business outcomes, which lowers the psychological barrier for enterprises considering AI workers.

The significance of this billing model is that it shifts the Agent business from selling software to selling outcomes, holding vendors accountable for business results rather than simply delivering a usable model API.

Bairong is an AI and data-services company focused on the financial industry, with customers concentrated in banking and insurance, sectors with demanding compliance and stability requirements. An AI customer-service agent handling tens of thousands of calls per day in such environments suggests its stability and conversational quality have reached production grade.

The sample is still limited to specific scenarios, however. While AI agents can handle 15,000 calls a day, long-tail tasks such as complex complaints, emotionally charged conversations, and cross-department coordination typically still require human involvement — where the boundary lies is exactly what customers want to know.

What to watch next: whether the pay-by-results model gains broader acceptance among enterprise buyers, and whether Bairong expands it from customer service to more job functions. The answers will decide if silicon-based employees scale beyond the showcase stage.