Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
A securities firm managing complex operations across 15 core departments, including brokerage, investment banking, research, and compliance.
Fragmented legacy systems created severe data silos that restricted the firm's ability to match financial products with long-tail customers....
Jianghai Securities's Workflow automation is part of this use case:
Jianghai Securities Co., Ltd. is a securities brokerage company offering investment services.
Related implementations across industries and use cases
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Global compliance slowed production. Now, AI drafts multilingual content and SQL queries, saving analysts 70 hours a week.
Analysts manually reviewed mountains of data for every alert. Now, AI agents summarize and verify facts, boosting efficiency by ~20%.
Rigid workflows required custom code per bank. Now, an adaptive engine configures rules instantly, automating manual research.
Manual handoffs slowed operations. AI now automates routing and validation, boosting case closure rates by over 50%.
Complex approvals delayed digital services for 74M customers. Now, business teams use low-code tools to launch specialized AI agents.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Manual translation dragged 60-minute calls to 90+, silencing experts. Now, live AI captions let teams collaborate in native languages.
Fleet repair estimates took up to 48 hours. Autonomous agents now process them in 30 minutes, absorbing a 10x volume surge.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
A securities firm managing complex operations across 15 core departments, including brokerage, investment banking, research, and compliance.
Fragmented legacy systems created severe data silos that restricted the firm's ability to match financial products with long-tail customers....
Jianghai Securities's Workflow automation is part of this use case:
Jianghai Securities Co., Ltd. is a securities brokerage company offering investment services.
Related implementations across industries and use cases
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Global compliance slowed production. Now, AI drafts multilingual content and SQL queries, saving analysts 70 hours a week.
Analysts manually reviewed mountains of data for every alert. Now, AI agents summarize and verify facts, boosting efficiency by ~20%.
Rigid workflows required custom code per bank. Now, an adaptive engine configures rules instantly, automating manual research.
Manual handoffs slowed operations. AI now automates routing and validation, boosting case closure rates by over 50%.
Complex approvals delayed digital services for 74M customers. Now, business teams use low-code tools to launch specialized AI agents.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Manual translation dragged 60-minute calls to 90+, silencing experts. Now, live AI captions let teams collaborate in native languages.
Fleet repair estimates took up to 48 hours. Autonomous agents now process them in 30 minutes, absorbing a 10x volume surge.