GS Neotech unveiled its enterprise AI transformation (AX) strategy built on Gemini Enterprise at the Google Cloud AI Live + Labs event, outlining a roadmap focused on connecting internal data and deploying context-aware AI agents.
Unveiling at Google Cloud AI Live + Labs
In a session attended by more than 1,000 decision-makers and developers, Kim Min-hyung, an engineer in GS Neotech’s DX division, detailed the AX evolution plan centered on Gemini Enterprise. The in-person event, themed “Work Innovation through Agnostic AI,” combined presentations, live demos, and hands-on labs.
Structuring data to power AI agents
At the core of GS Neotech’s approach is turning enterprise data into knowledge graphs. The company proposes organizing disparate data into ontologies via BigQuery Graph, then linking that knowledge layer to Gemini Enterprise to deploy agents capable of multi-hop inference. The goal is to convert information silos into actionable resources for context-aware agents.
Sector-specific use cases demonstrated
GS Neotech showcased concrete examples across industries:
– Advertising: AI agents for campaign planning, research, drafting summary emails, and KPI analysis to boost team productivity.
– Online travel: A FAQ chatbot to handle first-line requests across internal channels, standardizing AI usage and reducing repetitive inquiries.
– Manufacturing: Applying Gemini Enterprise to field tasks—market research, consumer analysis, AI image generation, and monthly report analysis—to cut time spent on operational activities.
Combining cloud experience with AX capabilities
GS Neotech intends to leverage its cloud operations experience and AI capabilities to tailor AX to each business environment. Seo Jeong-in, head of GS Neotech’s IT division, summarized the ambition: “Enterprise AX is moving toward structuring scattered data and connecting it to AI agents tailored to the work context. With our experience deploying Gemini Enterprise across industries, we’ll help clients turn AX into tangible everyday outcomes.”
A pragmatic path to operationalizing AI
Rather than relying on isolated experiments, GS Neotech emphasizes building a shareable knowledge layer and integrating agents that can interact with that structured data. This positioning aims to accelerate AI adoption in business processes by encouraging the reuse of knowledge and the scalable deployment of context-aware solutions. (Note: the source text was truncated; the preceding sentence completes the original thought.)
