Back office ops · Production
GCash uses Glean to save employees 2-3 hours a week and reach 90%+ adoption
The problem
Without a centralized intranet, GCash employees had to manually search across disconnected applications to find information, constantly interrupting their own and colleagues' workflows and harming organizational productivity.
Workflow diagram · grounded in source
1
Employee needs information
trigger
“workers regularly had to interrupt their workflows and those of others to ask about the information they needed”
2
Unified knowledge indexing
ai_action
“Glean delivered GCash a comprehensive, unified view of all its knowledge, stitching together information and perspectives from its many data sources”
3
Instant search and retrieval
output
“workers can search and instantly find what they need, staying better informed and focused throughout the day”
4
Compliance standards indexing
integration
“compliance department, which can now index and always stay up-to-date with the sensitive compliance standards set by the many regulatory bodies they work with”
5
Citizen-developer agent building
ai_action
“empowering employees to build their own applications through Glean Agent Builder. Now capable of developing personalized business agents through just natural language”
Reported outcome
Glean saves GCash employees 2-3 hours per week, has achieved over 90% adoption in some departments, and enabled citizen developers to build personalized AI agents through Glean Agent Builder.
Reported metrics
Hours saved per employee per week2-3 hours a week
Adoption rate in some departmentsover 90%
Reported stack
GleanGlean Agent Builder
Frequently asked questions
What did this team achieve with this AI workflow?
Glean saves GCash employees 2-3 hours per week, has achieved over 90% adoption in some departments, and enabled citizen developers to build personalized AI agents through Glean Agent Builder.
What tools did this team use?
Glean, Glean Agent Builder.
What results were reported?
Hours saved per employee per week: 2-3 hours a week; Adoption rate in some departments: over 90% (source-reported, not independently verified).
How is this back office ops AI workflow structured?
Employee needs information → Unified knowledge indexing → Instant search and retrieval → Compliance standards indexing → Citizen-developer agent building.