Knowledge was trapped in siloed systems. Gemini connected Jira and SharePoint, enabling staff to build custom agents for QA and coaching.
The technology division for a manufacturing conglomerate operating 30 distinct businesses across Australia, New Zealand, and the South Pacific.
Previous AI pilots failed to integrate with the organization's core data sources, leaving collective knowledge trapped in siloed systems. The team...
“Having a robust toolset for building custom agents is a key advantage. Using Vertex AI Agent Builder to quickly deploy and scale these agents ensures rapid time-to-production and accessibility for our teams. Furthermore, managing the environment as a dedicated Google Cloud project provides strong control over resources and access, giving us confidence in both management and cost governance.”
IT services and technology division for Fletcher Building Group.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
SOWs required manually merging data from four systems. Gemini agents now synthesize drafts, cutting manual work by up to 75%.
Staff chased devs for answers buried in scattered apps. AI now unifies the data, saving 20 minutes on every internal query.
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Staff chased devs for answers buried in scattered apps. AI now unifies the data, saving 20 minutes on every internal query.
Staffing lived in spreadsheets. Now, internal agents automate onboarding and match teams by skill, targeting 30% productivity gains.
Complex tables in 100-page docs bottlenecked teams. AI now parses text and images, ensuring every output is traceable and compliant.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Silos forced a 71-day wait for data. By unifying sources, 4,000 staff now access insights in hours and build models 50% faster.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Knowledge was trapped in siloed systems. Gemini connected Jira and SharePoint, enabling staff to build custom agents for QA and coaching.
The technology division for a manufacturing conglomerate operating 30 distinct businesses across Australia, New Zealand, and the South Pacific.
Previous AI pilots failed to integrate with the organization's core data sources, leaving collective knowledge trapped in siloed systems. The team...
“Having a robust toolset for building custom agents is a key advantage. Using Vertex AI Agent Builder to quickly deploy and scale these agents ensures rapid time-to-production and accessibility for our teams. Furthermore, managing the environment as a dedicated Google Cloud project provides strong control over resources and access, giving us confidence in both management and cost governance.”
IT services and technology division for Fletcher Building Group.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
SOWs required manually merging data from four systems. Gemini agents now synthesize drafts, cutting manual work by up to 75%.
Staff chased devs for answers buried in scattered apps. AI now unifies the data, saving 20 minutes on every internal query.
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Staff chased devs for answers buried in scattered apps. AI now unifies the data, saving 20 minutes on every internal query.
Staffing lived in spreadsheets. Now, internal agents automate onboarding and match teams by skill, targeting 30% productivity gains.
Complex tables in 100-page docs bottlenecked teams. AI now parses text and images, ensuring every output is traceable and compliant.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Silos forced a 71-day wait for data. By unifying sources, 4,000 staff now access insights in hours and build models 50% faster.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.