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.
FletcherTech's Internal knowledge search is part of this use case:
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.
Consultants manually sifted through code. GenAI now scans 280 million lines to generate tailored implementation instructions.
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.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
Legacy HR systems delayed insights by weeks as post-offer dropouts hit 30%. Now, an ML model flags at-risk candidates daily.
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
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.
FletcherTech's Internal knowledge search is part of this use case:
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.
Consultants manually sifted through code. GenAI now scans 280 million lines to generate tailored implementation instructions.
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.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
Legacy HR systems delayed insights by weeks as post-offer dropouts hit 30%. Now, an ML model flags at-risk candidates daily.
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.