Treated as a plug-in, not a platform. Now 370+ scenarios handle 10M+ daily AI calls — and new models ship in a day, not two weeks.
A major Chinese state-owned bank generating 192 billion yuan in H1 2026 revenue, operating retail banking, corporate lending, and internal management functions at national scale.
Deploying large AI models in banking required 2-week rollout cycles per model and carried prohibitive inference costs, making enterprise-wide AI...
“区别于传统的将AI进行简单集成，人工智能大模型已从辅助工具升级为重塑行业范式的核心驱动力。”
Also reported by
Large commercial retail bank offering personal and corporate banking services in China.
Co-developed and released the "YouZhi" financial industry large model with Postal Savings Bank of China.
Postal Savings Bank of China's Enterprise banking AI is part of this use case:
Related implementations across industries and use cases
Static bots capped accuracy at 75%. Now, AI agents run live credit checks with 99% precision, tripling engagement.
Routine admin bogged down 120,000 staff. Secure custom GPTs now automate workflows, freeing bankers for strategy and risk analysis.
Staff slowed by repetitive tasks feared AI replacement. With bottom-up training, they built custom agents, speeding work by up to 50%.
Novices were too embarrassed to ask basics publicly. Private AI agents now answer instantly, cutting response times from 10s to near-zero.
23% of turns were disengaging — Cait only found out after each conversation ended. State inference now runs live and adjusts mid-turn.
Engineers capped at basic chat, complex work out of reach. Now 700 tackle cross-jurisdiction compliance reviews in hours, not weeks.
37 steps and 16 handoffs to send one email. Agents rebuilt the workflow from scratch — 3 weeks became 2 days.
Managing documentation across 65 sites bottlenecked a central team. Now, Claude synthesizes data and coaches local directors on compliance.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
Treated as a plug-in, not a platform. Now 370+ scenarios handle 10M+ daily AI calls — and new models ship in a day, not two weeks.
A major Chinese state-owned bank generating 192 billion yuan in H1 2026 revenue, operating retail banking, corporate lending, and internal management functions at national scale.
Deploying large AI models in banking required 2-week rollout cycles per model and carried prohibitive inference costs, making enterprise-wide AI...
“区别于传统的将AI进行简单集成，人工智能大模型已从辅助工具升级为重塑行业范式的核心驱动力。”
Also reported by
Large commercial retail bank offering personal and corporate banking services in China.
Co-developed and released the "YouZhi" financial industry large model with Postal Savings Bank of China.
Postal Savings Bank of China's Enterprise banking AI is part of this use case:
Related implementations across industries and use cases
Static bots capped accuracy at 75%. Now, AI agents run live credit checks with 99% precision, tripling engagement.
Routine admin bogged down 120,000 staff. Secure custom GPTs now automate workflows, freeing bankers for strategy and risk analysis.
Staff slowed by repetitive tasks feared AI replacement. With bottom-up training, they built custom agents, speeding work by up to 50%.
Novices were too embarrassed to ask basics publicly. Private AI agents now answer instantly, cutting response times from 10s to near-zero.
23% of turns were disengaging — Cait only found out after each conversation ended. State inference now runs live and adjusts mid-turn.
Engineers capped at basic chat, complex work out of reach. Now 700 tackle cross-jurisdiction compliance reviews in hours, not weeks.
37 steps and 16 handoffs to send one email. Agents rebuilt the workflow from scratch — 3 weeks became 2 days.
Managing documentation across 65 sites bottlenecked a central team. Now, Claude synthesizes data and coaches local directors on compliance.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.