Every week: pull from Zendesk, pull from Rippling, rebuild the Sheet — and start over when the data changed. Now a dashboard does it live.
A 335-person wellness company processing hundreds of support tickets daily across multiple locations, with compensation data in Rippling and ticket performance data in Zendesk living in entirely separate systems.
Answering whether higher-paid support agents actually resolved guest issues faster required manually pulling data from Zendesk and Rippling,...
“We were pulling from Zendesk, comparing it to Rippling, cross-referencing profiles, reformatting CSVs, and doing it all over again every single week.”
Wellness spa and bathhouse offering thermal pools, saunas, and bodywork treatments.
HR, payroll, and IT management platform for global workforce operations.
Bathhouse's Pay-performance analysis is part of this use case:
Related implementations across industries and use cases
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
Three disconnected systems: one consultant could be recommended for four deals undetected. Now conflicts surface before deals close.
Managers spent days manually calling applicants. Now, AI screens and schedules instantly via text, keeping managers focused on guests.
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
A payroll burn rate view took hours to build, an hour to refresh, and broke with every reorg. One prompt now returns it instantly, live.
Millions of queries across 1,300 topics overwhelmed support. Now, an AI agent resolves them instantly, freeing staff for complex cases.
Manual dispatching bottlenecked guest requests. Now, an in-app AI instantly routes tasks to optimal staff and tracks execution.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Every week: pull from Zendesk, pull from Rippling, rebuild the Sheet — and start over when the data changed. Now a dashboard does it live.
A 335-person wellness company processing hundreds of support tickets daily across multiple locations, with compensation data in Rippling and ticket performance data in Zendesk living in entirely separate systems.
Answering whether higher-paid support agents actually resolved guest issues faster required manually pulling data from Zendesk and Rippling,...
“We were pulling from Zendesk, comparing it to Rippling, cross-referencing profiles, reformatting CSVs, and doing it all over again every single week.”
Wellness spa and bathhouse offering thermal pools, saunas, and bodywork treatments.
HR, payroll, and IT management platform for global workforce operations.
Bathhouse's Pay-performance analysis is part of this use case:
Related implementations across industries and use cases
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
Three disconnected systems: one consultant could be recommended for four deals undetected. Now conflicts surface before deals close.
Managers spent days manually calling applicants. Now, AI screens and schedules instantly via text, keeping managers focused on guests.
Comp data across five systems meant Taylor was a retrieval mechanism. One prompt built a live dashboard; four workflows run without her.
A payroll burn rate view took hours to build, an hour to refresh, and broke with every reorg. One prompt now returns it instantly, live.
Millions of queries across 1,300 topics overwhelmed support. Now, an AI agent resolves them instantly, freeing staff for complex cases.
Manual dispatching bottlenecked guest requests. Now, an in-app AI instantly routes tasks to optimal staff and tracks execution.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.