Partnerships

Salesforce Runs Hyperforce on Google Cloud in Expanded Partnership

mm
Add Unite.AI to your preferred sources on Google

Salesforce and Google Cloud expanded their strategic partnership on September 15, 2026, announcing at Dreamforce 2026 in San Francisco that Salesforce will run its Hyperforce infrastructure on Google Cloud and begin migrating select U.S. customers to the platform in the fourth quarter of 2026.

Under the expansion, Salesforce’s headless architecture connects with Google’s Gemini Enterprise platform so that AI agents on either platform can reason and act on the same data without custom integrations. The companies detailed new work spanning infrastructure, agent interoperability, digital commerce, and data sharing.

Hyperforce Migration and Availability

Hyperforce on Google Cloud is already successfully handling live production customer traffic, Salesforce said. The deployment is scheduled to reach general availability in North America in November 2026, followed by phased feature and regional expansion in 2027 that includes Germany.

“What changes here is the infrastructure underneath our customers, not the trust they’ve built with us,” said Meir Amiel, President and Chief Trust and Infrastructure Officer at Salesforce, in the partnership announcement. Amiel said Hyperforce running natively on Google Cloud will extend the same security, compliance, and resilience standards Salesforce holds itself to, giving enterprises Google Cloud’s flexibility without lowering the trust bar they expect from Salesforce.

Kevin Ichhpurani, President of Global Partner Ecosystem at Google Cloud, said Gemini Enterprise brings Google’s AI together with a company’s data, applications, and everyday workflows in one platform. By bringing Salesforce into Gemini Enterprise, he said, customers can build trusted agents that reason across their business context and securely take action, while Hyperforce on Google Cloud gives customers greater choice in how they deploy Salesforce on AI-optimized infrastructure.

Gemini Enterprise and Agentforce Integrations

Google Cloud is one of the first hyperscalers to implement Salesforce’s headless architecture, according to the company. The architecture makes thousands of Salesforce capabilities available to any model, agent, or interface and is built on the Model Context Protocol (MCP) open standard, which Salesforce said allows native interoperability between Gemini Enterprise and Salesforce.

Enterprises can surface Salesforce data and capabilities directly within Gemini Enterprise without custom integration, supporting use cases from pipeline health checks and account summaries to case triage across sales, service, finance, and advertising workflows. Through Tableau MCP, enterprises can also connect Gemini Enterprise to Tableau analytics, with governance, row-level security, and semantic models enforced on every agent query.

Joint customers can use Google’s Gemini models natively within Agentforce to build autonomous agents that reason and act across both platforms, and Google’s most recent models remain available to power Prompt Builder and Agentforce’s Reasoning Engine. The Agentforce Reasoning Engine with Gemini is generally available, the Salesforce Federated Connector for Gemini is in private preview with general availability planned for late October, and the Agentforce Sales Agent for Gemini Enterprise is in beta on Google Cloud Marketplace.

SharkNinja is among the joint customers already applying the integrations. Evan Gerber, VP of AI and Emerging Technology at SharkNinja, said the company is combining Gemini Live’s real-time, multimodal capabilities with Agentforce to create a new way for consumers to engage with SharkNinja throughout the life of a product, beginning with guided setup and growing into an intelligent product companion that helps people learn, troubleshoot, discover new possibilities, and connect with support when needed.

Commerce Cloud Checkout on Google Surfaces

Beginning in the fall of 2026, shoppers can discover and purchase products directly within Google Search, including AI Mode, and the Gemini app, with the experience powered by Salesforce Commerce Cloud. Merchants can send product catalog data to Google Merchant Center through a native feed integration and field-mapping interface in Business Manager, and the catalog feed integration with Google is generally available.

Checkout powered by the Universal Commerce Protocol (UCP) lets merchants enable end-to-end purchasing directly within Google surfaces while keeping payments, compliance, and order management on their existing commerce infrastructure. The UCP integration is scheduled to reach general availability in October 2026.

SharkNinja Chief Information Officer Velia Carboni said surfacing the company’s products across Google with UCP-enabled checkout on the results page shortens the path from discovery to purchase while payments and order management remain on Commerce Cloud. Carboni described the capability as a seamless experience for consumers and a meaningful new growth channel for SharkNinja.

Data 360 Expansion and Partnership Background

The new work builds on an earlier expansion the companies announced on October 16, 2025, which brought Google’s Gemini models to Salesforce’s Atlas Reasoning Engine, integrated Agentforce 360 with Google Workspace, and connected Slack’s Real-Time Search API with Gemini Enterprise. That announcement listed Zero Copy data sharing between Data 360 and BigQuery, including data query federation, data sharing, and federated authentication, as generally available at the time.

Salesforce Data 360 and Google BigQuery already support Zero Copy data sharing, and the companies are expanding data sharing to additional Salesforce and Google regions, adopting Iceberg Rest Catalog open standards, and enabling Private Connect. The Zero Copy expansion is scheduled for general availability in the fall of 2026, and Salesforce and Google Cloud said they continue to explore new capabilities such as bidirectional semantic information sharing.

Aiden Cross is an AI-generated strategist at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers.

With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value.

Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI’s editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.