Use case
Faster retail transformation
Context

TCS partnered with Google Cloud to integrate advanced AI and generative AI capabilities into retail service offerings. They launched the Google Cloud Gemini Experience Center at their Retail Innovation Lab in Chennai, enabling retail clients to ideate, prototype, and co-develop tailored AI solutions that optimize supply chain, warehouse receiving, customer insights, and content creation. This approach automated processes using tools like Vertex AI Vision for warehouse receiving and leveraged Vertex AI with Gemini 1.5 Pro and speech-to-text to transform service centers.

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4
Use case
Faster research reports
Context

Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.

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2
Use case
Secure on-premises AI
Context

NVIDIA partnered with Google Cloud to enable on-premises agentic AI by integrating Google Gemini models with NVIDIA Blackwell platforms and Confidential Computing, ensuring data sovereignty and regulatory compliance for sensitive enterprise operations. The solution further optimizes AI inference and observability by deploying a GKE Inference Gateway alongside NVIDIA Triton Inference Server, NVIDIA NeMo Guardrails, and NVIDIA Dynamo to enhance secure routing and load balancing for enterprise workloads.

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7
Use case
Faster tax form processing
Context

Intuit integrated Google Cloud’s Document AI and Gemini models into its GenOS platform to automate the autofill of ten common U.S. tax forms, including complex 1099 and 1040 forms. The solution extracts and categorizes data from uploaded documents, drastically reducing manual data entry for TurboTax customers. This integration streamlines tax preparation workflows and improves speed and accuracy.

Models/tools
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2
Use case
Optimized CX workflows
Context

Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.

Models/tools
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3
Use case
Scalable contract detection
Context

wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.

Models/tools
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1
Use case
Fast registration & safety
Context

704 Apps implemented an AI solution using Vertex AI and Gemini 1.5 Pro to automate and accelerate driver identity verification and safety monitoring. They integrated these AI models into their existing cloud infrastructure built on Firebase and Google Kubernetes Engine, centralizing real-time data for document validation and audio sentiment analysis. The system alerts the central monitoring team when risk-related language is detected, streamlining operational decision-making and enhancing security.

Models/tools
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2
Use case
AI integration on mobile
Context

OPPO integrated Google Cloud’s Vertex AI, AutoML, and Gemini large language model into its mobile devices to automate user feedback analysis, power AI Recording Summary features, and enable AI Toolbox functionalities such as AI Writer and AI Reply. They re-engineered their hardware platform, operating system, and third-party ecosystem to embed AI agents that optimize power consumption and reduce computing latency, streamlining mobile development workflows and enhancing user experience.

Models/tools
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4
Use case
Personalized post-click landing
Context

Dataïads built an AI-powered “Post-Click Experience” system that automatically generates personalized landing pages by analyzing user context such as ad origin, product type, and behavior. The solution is implemented by integrating API access from Google Ads with Google Cloud managed services (Cloud Run and BigQuery) for automated scaling and controlled cost management, while planning to incorporate Vertex AI for further optimization. This implementation directly enhances ad campaign management and improves ecommerce conversion processes.

Models/tools
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1
Use case
Scalable, cost-efficient platform
Context

Wited revamped its learning platform by partnering with Google Cloud and Axmos Technologies to migrate from legacy systems to a robust infrastructure using Cloud SQL, Cloud Storage, Compute Engine, and Google Kubernetes Engine, ensuring reliable scalability and stability for high user demand. They then integrated generative AI by deploying Gemini and Vertex AI to power Max AI—a 24/7 virtual assistant that supports students through real-time assistance and educational guidance—thereby streamlining support processes and enabling the team to focus on innovation.

Models/tools
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2
Use case
Personalized in-car navigation
Context

Mercedes-Benz expanded its strategic partnership with Google Cloud to integrate an AI-driven conversational search capability into its MBUX Virtual Assistant. They implemented Google Cloud’s Automotive AI Agent built on Gemini on Vertex AI to access real-time navigation data from Google Maps Platform, enabling multi-turn, natural language dialogue and personalized recommendations that transform in-car navigation and user interaction.

Models/tools
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2
Use case
Data-driven embryo assessment
Context

Fairtility developed its AI-powered IVF solution, CHLOE, leveraging Google Cloud’s robust infrastructure to analyze thousands of data points daily for insights on embryo and egg viability. The system is implemented across 100 global clinics with remote deployment and near real-time updates, streamlining operational workflows and aiding embryologists with faster, data-informed treatment decisions.

Models/tools
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Use case
Efficient customer onboarding
Context

Mystifly partnered with Google Cloud to develop Mystic, an AI-powered chatbot that leverages Vertex AI Agent Builder to understand complex airline industry queries. They implemented an internal system by indexing PDFs stored in Google Cloud Storage into an unstructured datastore for quick retrieval and integrated Dialogflow CX with Cloud Functions for seamless escalation. This solution automated customer onboarding and support workflows for their SSP Manager platform by enabling travel agents to resolve configuration questions independently.

Models/tools
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2
Use case
Personalized fan engagement
Context

The Warriors overhauled their IT and data infrastructure with Google Cloud, integrating 30+ fan-facing data sources and analyzing over 100M data points to build a custom mobile app using App Engine and Firebase for a personalized digital fan experience. They implemented Gemini for Google Workspace to automate repetitive administrative tasks, streamlining internal processes and saving 41 hours per employee annually. Additionally, they are exploring Vertex AI to integrate natural language search with BigQuery, enhancing data-driven decision-making for both team performance and fan engagement.

Models/tools
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2
Use case
Rapid geospatial processing
Context

Picterra integrated Google Kubernetes Engine (GKE) and Google Earth Engine into its geospatial AI platform to efficiently process and model ultra-high resolution terrain data. They implemented scalable infrastructure on GKE to dynamically handle massive geospatial workloads, enabling rapid analysis of satellite imagery and digital terrain modelling. This streamlined climate change data analysis workflows across entire countries.

Models/tools
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2
Use case
Intuitive hotel search
Context

trivago integrated Google Cloud’s Vertex AI Search into its hotel discovery platform, enabling users to search using natural language with advanced LLMs. The AI was tailored to interpret free-text queries and integrated into existing search workflows to deliver personalized hotel recommendations. This reconfiguration improved search accuracy and user efficiency by transforming traditional, rigid search parameters into an intuitive discovery process.

Models/tools
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1
Use case
Manual advisory documentation
Context

Commerzbank partnered with Google Cloud to automate its financial advisory documentation process by integrating a multi-step generative AI pipeline. They implemented a user-friendly frontend and Java Spring backend to import and chunk client call recordings stored on GCP, which were processed using Gemini 1.5 Pro for diarized transcription, fact extraction, and summary generation, with quality assurance provided by Vertex AI Gen AI Evaluation Service. This automation streamlined the regulatory documentation workflow, enabling sales advisors to focus on high-value client engagements.

Models/tools
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3
Use case
Unified security & collaboration
Context

apree health adopted Google Workspace to centralize data access management and secure sensitive patient data by consolidating disparate security systems into a unified admin console. They implemented a zero-trust strategy with granular access controls, endpoint management, and integrated Gemini for Google Workspace to streamline document creation and collaboration across development and patient care. The migration, supported by SADA, involved transitioning over 1,200 employees and providing extensive training to facilitate a smooth change management process.

Models/tools
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1
Use case
Faster LLM deployments
Context

Moveo.AI centralized its LLM training on Vertex AI by consolidating its multi-cloud approach, leveraging A3 VMs powered by NVIDIA H100 GPUs to fine-tune large language models tailored for customer experience. The implementation integrated Dynamic Workload Scheduler for auto-scaling and optimized resource management, streamlining secure and efficient virtual agent operations.

Models/tools
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2
Use case
Faster event planning
Context

Thoughtworks implemented an AI-powered enterprise event planning solution leveraging Google's Gemini Pro multimodal capabilities. The system analyzes historical data, regional event schedules, customer shopping insights, and enterprise strategic guidance to automatically generate a personalized event calendar complete with campaign details, promotion types, image assets, and recommended schedules. Marketing teams interact with an integrated AI assistant to review, adjust, and approve event proposals, significantly streamlining their planning process.

Models/tools
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1
Use case
Quick media search
Context

Globant implemented an AI-powered video search solution that processes uploaded videos in Google Cloud by automatically generating detailed embeddings from frame analysis, transcriptions, and scene descriptions. The system then indexes these embeddings in a vector database, enabling both text and image-based queries to retrieve specific content within seconds. This solution enhances media content management processes for producers, editors, and researchers by drastically reducing manual search efforts.

Models/tools
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Use case
Unified data access
Context

Copel integrated Gemini Pro 1.5 to power a virtual agent that directly interfaces with their on-premises SAP ERP system using Google Cloud’s Cortex Framework along with Vertex AI, BigQuery, Dataplex, and Open Data QnA. The agent processes natural language queries from employees to deliver real-time insights, replacing manual data extraction and processing workflows. This integration improved data democratization and significantly accelerated decision-making across the enterprise.

Models/tools
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6
Use case
Unified digital workflows
Context

Banestes migrated its on-premise systems to Google Workspace in a multi-phase transition executed in partnership with IPNET, which included workshops, video trainings, and a custom Google Sites library to onboard over 2,600 users. They leveraged AppSheet to develop 8 internal applications that automated 6 manual processes—resulting in a 70% reduction in support calls—and integrated Gemini AI to expedite document analysis for credit and compliance, thereby streamlining email, chat, and videoconference workflows.

Models/tools
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1
Use case
Streamline communication & document creation
Context

Hydro Ottawa, a major electricity provider for Canada’s capital, implemented Google Workspace and Gemini to improve collaboration, create job posts, conduct legal and technical research, write policies, generate content, summarize documents, and organize meeting agendas across all teams.

Models/tools
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1
Use case
Efficient team collaboration
Context

Vimeo integrated Google Meet’s AI-driven note-taking and summarizing capabilities by implementing Gemini for Google Workspace across its videoconferencing and collaborative document platforms. They rolled out Google Docs, Sheets, and Slides company-wide to support simultaneous multi-user editing and integrated these tools with Google Meet to automatically generate meeting notes and action items. This implementation streamlined internal meetings and enhanced overall project collaboration across teams.

Models/tools
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1
Use case
Faster compliance processing
Context

Trace One implemented AI by integrating Google Vertex AI to automatically extract information from technical sheets and regulatory documents, map data between diverse systems, and compare texts and images for packaging compliance. The solution was developed following a successful proof-of-concept and then scaled into production using Google Cloud’s managed services, simplifying system integration and reducing operational complexity. This deployment streamlined their PLM and compliance update processes, minimizing manual intervention and optimizing accuracy.

Models/tools
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2
Use case
Modernize tech infrastructure
Context

Citi partnered with Google Cloud to migrate multiple workloads and applications to its secure, scalable infrastructure, integrating Vertex AI to enable generative AI capabilities for developer toolkits, document processing, and customer service workflows. This multi-year strategic initiative modernizes core IT systems, streamlines employee workflows, and enhances high-performance computing for Citi’s Markets business.

Models/tools
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1
Use case
Rapid secure AI access
Context

L’Oréal built GenAI as a Service by developing a comprehensive set of declarative generative AI APIs accessible via its internal L’OréalAPI portal, enabling developers to integrate advanced AI features without worrying about LLM connectivity or billing complexities. Using Google Cloud Run for scalable, serverless deployment and integrating LangChain to connect with LLMs like Gemini Pro 1.5, the solution supports prompt completion, chat with memory, and image generation. This implementation streamlines internal workflows across multiple departments while ensuring robust data security and governance.

Models/tools
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3
Use case
Faster asset mapping
Context

BMW Group, in collaboration with SORDI.ai and Monkeyway, deployed a generative AI system that scans a wide range of industrial assets and uses Vertex AI to produce detailed 3D digital twins. This automated solution replaces the slow, manual asset mapping process, enabling rapid simulation of multiple industrial scenarios to optimize planning and supply chain efficiency.

Models/tools
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1
Use case
Reducing monotonous copywriting tasks
Context

Adore Me, a direct-to-consumer lingerie brand known for its extended sizing, uses Gemini for Google Workspace to streamline copywriting and foster creativity. The team reduced over 35 hours of work creating product descriptions to just 30 minutes by leveraging a prompt library. They also use Gemini for speaker bios, enabling users to fill in key details for automated output. Internal "prompt-off" competitions teach employees how to effectively use AI tools, embedding AI into the company culture.

Models/tools
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1

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