Previously, agents manually handled all simple info requests—30% of contacts. Now, an AI agent resolves these queries automatically.
The financial services division of Europe's largest manufacturing company operates a global support function serving diverse clients, from sole traders to large enterprises.
Support agents managed customer data across disjointed email inboxes and spreadsheets, lacking centralized visibility. Additionally, routine data and...
“When you provide financial products, your customers recognize value and consistency, service and trust are paramount — so it’s really about how you differentiate your customer service.”
Industrial automation, smart infrastructure, and energy technology provider.
AI-powered customer service and employee experience software platform.
Siemens's Customer support is part of this use case:
Related implementations across industries and use cases
Teams searched 32,000 scattered docs to fix devices. AI now mines that data to resolve 50% of cases autonomously.
Rigid "press 1" phone trees bottlenecked global support. Now, localized AI agents guide complex step-by-step blind installations.
A regulatory surge overwhelmed a support team using 5 fragmented tools. Now, AI fields 100k monthly questions, freeing agents for complex cases.
Reactive support for 15M broadband upgrades drove high call volumes. Now, AI agents proactively text and call to schedule installations.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
Complex multi-tab spreadsheets limited early bots. Now, an extraction pipeline structures this data for AI to reliably resolve queries.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Previously, agents manually handled all simple info requests—30% of contacts. Now, an AI agent resolves these queries automatically.
The financial services division of Europe's largest manufacturing company operates a global support function serving diverse clients, from sole traders to large enterprises.
Support agents managed customer data across disjointed email inboxes and spreadsheets, lacking centralized visibility. Additionally, routine data and...
“When you provide financial products, your customers recognize value and consistency, service and trust are paramount — so it’s really about how you differentiate your customer service.”
Industrial automation, smart infrastructure, and energy technology provider.
AI-powered customer service and employee experience software platform.
Siemens's Customer support is part of this use case:
Related implementations across industries and use cases
Teams searched 32,000 scattered docs to fix devices. AI now mines that data to resolve 50% of cases autonomously.
Rigid "press 1" phone trees bottlenecked global support. Now, localized AI agents guide complex step-by-step blind installations.
A regulatory surge overwhelmed a support team using 5 fragmented tools. Now, AI fields 100k monthly questions, freeing agents for complex cases.
Reactive support for 15M broadband upgrades drove high call volumes. Now, AI agents proactively text and call to schedule installations.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
Complex multi-tab spreadsheets limited early bots. Now, an extraction pipeline structures this data for AI to reliably resolve queries.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.