Google Kubernetes Engine (GKE)

6 use cases using this technology

6published use cases

6industries

3countries on record

Generative AI

top AI capability

Evidence mix: High 6 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry

Country

6 use cases

Technology & SoftwareConversational AIAgentic AI

Wonderful cuts enterprise customer service costs up to 70% with multilingual Gemini voice agents

Wonderful built enterprise-grade AI agents on Google Cloud's Gemini and Vertex AI that operate across voice, text, and email in dozens of languages and local dialects, expanding across EMEA markets including Arabic, Czech, French, Greek, Dutch, and Italian. Early deployments let contact centers handle thousands of simultaneous conversations, cutting enterprise costs by around 70% per minute of AI-handled call or chat, and one banking client built a promotional AI agent in four days versus the weeks it would have taken 50 people previously.

Wonderful· IsraelGemini · Vertex AI · Compute Engine +2

ManufacturingGenerative AI

Workerbase powers real-time shop floor AI workflows on Google Cloud

German manufacturing software company Workerbase uses Google Cloud's Vertex AI and Google Kubernetes Engine to deliver real-time, AI-generated troubleshooting instructions to shop floor operators when machines report faults, translating instructions into workers' preferred languages and supporting predictive maintenance. Manufacturers including Siemens and Porsche use the platform, which also lets supervisors build low-code workflow apps in hours instead of months and integrates with legacy systems like SAP.

Workerbase· GermanyGoogle Cloud Vertex AI · Google Kubernetes Engine (GKE) · BigQuery +1

HealthcareDocument IntelligenceGenerative AI

Giles AI delivers 95% accuracy in data extraction with Vertex AI and Gemini

London-based Giles AI built its giles research assistant on Google Cloud's Vertex AI and Gemini, using Document AI to parse medical literature, achieving 95% accuracy in data extraction, an 85% reduction in time required for clinical research tasks, and a 98% agreement rate between the AI and human researchers.

Giles AI· United KingdomVertex AI · Gemini · Gemini Pro +5

RetailPredictive Analytics

OTTO improves demand forecasting accuracy up to 30% with Google Cloud's TiDE model

OTTO, a leading German ecommerce retailer, used Google Cloud's Time-series Dense Encoder (TiDE) model trained on Vertex AI and deployed on GKE to analyze multivariate time-series data such as seasonal demand patterns, pricing changes, and promotions. TiDE improved demand forecasting accuracy by up to 30%, helping OTTO reduce inventory costs, minimize stock-outs and overstocks, and support dynamic pricing, with particularly strong responsiveness for volatile products like iPhones versus more stable items like men's jeans.

OTTO· GermanyVertex AI · BigQuery · Google Kubernetes Engine (GKE)

Media & EntertainmentSpeech & Audio AIGenerative AIConversational AI

ElevenLabs: Scaling Voice AI with GPU-Accelerated Infrastructure

ElevenLabs runs its voice AI platform for text-to-speech, voice cloning and speech-to-speech translation on Google Kubernetes Engine (GKE) with NVIDIA GPUs, using GPU optimization strategies such as Multi-Instance GPUs and GPU time sharing to improve utilization and reduce costs. The platform generates 600 hours of audio for every hour of real time, supports 29 languages (expanding to 40), and is reportedly used by 41% of Fortune 500 companies, powering products including AI Dubbing Studio, long-form audio for audiobooks and podcasts, article narration for outlets like The New York Times, and real-time conversational AI assistants.

ElevenLabsGoogle Kubernetes Engine (GKE) · NVIDIA H100 GPUs · Multi-Instance GPUs (MIG) +1

AutomotiveMachine LearningComputer Vision

Toyota shifts into overdrive: Developing an AI platform for enhanced manufacturing efficiency

Toyota's Production Digital Transformation Office built an in-house AI Platform on a Google Cloud hybrid architecture that lets factory floor employees create machine learning models without AI expertise, automating manual, labor-intensive tasks. Built by a six-person team in about 1.5 years, the platform runs at all 10 Toyota car and unit manufacturing factories; the number of models created rose from 8,000 in 2023 to 10,000 in 2024, saving over 10,000 man-hours per year, with nearly 1,200 active users and 400+ trained annually.

Toyota Motor CorporationGoogle Cloud · Google Kubernetes Engine (GKE) · GKE Enterprise +6