Providing tailored agricultural advice via chatbot

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.

Notion reimagined its platform by deeply integrating OpenAI’s GPT‑4o, GPT‑4o mini, and embeddings across its core features. They prototyped an AI writing assistant during a hackathon and then built internal tools to rapidly evaluate and deploy new models, transforming workflows in search, note-taking, and knowledge management from static content to interactive, actionable insights.

Zendesk integrated OpenAI's models to create adaptive AI service agents that autonomously manage customer conversations and execute resolution tasks. They implemented a multi-agent architecture featuring task identification, conversational RAG, procedure compilation, and procedure execution agents integrated with existing support workflows through API calls and natural language procedure definitions, while providing real-time chain-of-thought visibility. This solution transitions from traditional intent-based bots to a hybrid model of scripted and generative reasoning, streamlining customer service processes.

Hebbia built Matrix, a multi-agent AI platform that orchestrates OpenAI models including o3‑mini, o1, and GPT‑4o to automate complex financial and legal research tasks. The platform decomposes intricate queries into structured analytical steps and integrates modules like OCR, hallucination validation, and artifact generation to process complete documents, creating an infinite effective context window. This solution streamlines due diligence, contract review, and market research workflows, drastically reducing manual processing time.

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.