Rapid, culturally-aware support

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.

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.

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.

Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.

Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.

Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.

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.

LY Corporation leveraged OpenAI’s API to integrate advanced generative AI into its flagship services, including a GPT‑4o-powered LINE AI Assistant and GPT‑4 enhancements in Yahoo! JAPAN Search for summarizing reviews and generating travel plans. They also deployed SeekAI, an in-house productivity tool using RAG to rapidly retrieve information from internal documentation, streamlining employee inquiries and operations.

Physics Wallah developed 'Gyan Guru', a hyperpersonalized conversational study companion to address the unique academic and support needs of its 2 million daily users. The system was implemented by indexing over one million Q&As and ten million solved doubts in a vector database, then leveraging a Retrieval-Augmented Generation (RAG) approach integrated with Azure OpenAI to deliver individualized, context-aware responses. This integration streamlined various student interactions including academic queries, product-related issues, and general support, reducing reliance on human subject matter experts.