InMorphis
Internal operations automation
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
- 100% IT and HR SLA compliance
- 73% code generation accuracy
- 2.5x sales team productivity
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 Co., Ltd. is a securities brokerage company offering investment services.
Jianghai Securities's Workflow automation is part of this use case:
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.
Routine reviews delayed member support. Now, non-technical employees securely build custom AI agents to resolve complex cases in minutes.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
37 steps and 16 handoffs to send one email. Agents rebuilt the workflow from scratch — 3 weeks became 2 days.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Managing documentation across 65 sites bottlenecked a central team. Now, Claude synthesizes data and coaches local directors on compliance.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.
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 Co., Ltd. is a securities brokerage company offering investment services.
Jianghai Securities's Workflow automation is part of this use case:
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.
Routine reviews delayed member support. Now, non-technical employees securely build custom AI agents to resolve complex cases in minutes.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
37 steps and 16 handoffs to send one email. Agents rebuilt the workflow from scratch — 3 weeks became 2 days.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Managing documentation across 65 sites bottlenecked a central team. Now, Claude synthesizes data and coaches local directors on compliance.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.