7,000 weekly tickets delayed by manual notes. AI now drafts instant summaries, slashing resolution time by 47%.
An Australian technology provider serving highly regulated industries manages over 7,000 customer support tickets weekly across a hybrid service environment.
Support engineers spent significant time manually writing and reviewing detailed case notes, causing basic ticket resolutions to take up to a week....
“We wanted to minimize manual or repetitive work for our support engineers, and empower them to become thought leaders that serve customers better. Our clients are also focusing on driving costs down, so enabling new ways of working is inevitable.”
Cloud consulting and managed services provider specializing in Microsoft Azure.
ServiceNow is an enterprise software company that specializes in IT Service Management, cloud computing, and digital transformation solutions.
LAB3's Customer support is part of this use case:
Related implementations across industries and use cases
Customers waited six minutes as staff manually sorted tickets. AI now routes requests instantly, cutting waits to under a minute.
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Five-fold growth created service bottlenecks for agents. Now, an AI agent handles routine questions, freeing the team for complex problems.
Customers waited six minutes as staff manually sorted tickets. AI now routes requests instantly, cutting waits to under a minute.
Five-fold growth created service bottlenecks for agents. Now, an AI agent handles routine questions, freeing the team for complex problems.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
7,000 weekly tickets delayed by manual notes. AI now drafts instant summaries, slashing resolution time by 47%.
An Australian technology provider serving highly regulated industries manages over 7,000 customer support tickets weekly across a hybrid service environment.
Support engineers spent significant time manually writing and reviewing detailed case notes, causing basic ticket resolutions to take up to a week....
“We wanted to minimize manual or repetitive work for our support engineers, and empower them to become thought leaders that serve customers better. Our clients are also focusing on driving costs down, so enabling new ways of working is inevitable.”
Cloud consulting and managed services provider specializing in Microsoft Azure.
ServiceNow is an enterprise software company that specializes in IT Service Management, cloud computing, and digital transformation solutions.
LAB3's Customer support is part of this use case:
Related implementations across industries and use cases
Customers waited six minutes as staff manually sorted tickets. AI now routes requests instantly, cutting waits to under a minute.
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Five-fold growth created service bottlenecks for agents. Now, an AI agent handles routine questions, freeing the team for complex problems.
Customers waited six minutes as staff manually sorted tickets. AI now routes requests instantly, cutting waits to under a minute.
Five-fold growth created service bottlenecks for agents. Now, an AI agent handles routine questions, freeing the team for complex problems.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.