CloudFuze has launched an AI migration service designed to help organizations move AI assistants, conversation histories, and custom agents between platforms without rebuilding everything from scratch. The offering covers migration involving Microsoft Copilot, Google Gemini, and Claude, with an initial agent migration path from Microsoft Copilot Studio to Google Gemini Enterprise. CloudFuze says the service can transfer conversation context and artifacts, recreate agents using Google’s Agent Development Kit (ADK), and preserve selected agent settings and permissions. The launch addresses an emerging enterprise challenge: retaining accumulated AI knowledge when organizations change platforms.
CloudFuze Launches AI Migration for Assistants and Agents
As enterprises invest in AI assistants and custom agents, their dependence on these systems increasingly extends beyond the underlying models. Conversation histories, uploaded files, instructions, connected data sources, and workflow configurations can all become part of how employees perform their jobs. Moving to another AI platform can therefore mean more than switching software: it can require rebuilding accumulated business context.
CloudFuze has introduced a dedicated AI migration category designed to transfer AI applications, conversation history, and custom agents between platforms. The company says its service supports migration involving Microsoft Copilot, Google Gemini, and Claude, with its initial agent migration offering focused on moving Microsoft Copilot Studio agents to Google Gemini Enterprise.
The launch targets organizations that want to change AI platforms while retaining useful knowledge and reducing the work involved in recreating existing AI workflows.
Moving conversations and context between AI platforms
CloudFuze’s AI migration service is designed to transfer conversation histories, contextual information, and associated artifacts from supported AI assistants. The company says users can then ask questions in the destination assistant about previous conversations and receive answers with source references.
That capability addresses a practical limitation of changing AI tools: a new assistant may not automatically have access to the interaction history and files accumulated in another platform. Without a transfer process, employees may need to locate old information manually, repeat instructions, or recreate established workflows.
Preserving conversation history could make transitions less disruptive, particularly for teams that use AI to support research, document preparation, analysis, and recurring business tasks. However, the usefulness of migrated context will depend on whether the destination platform can interpret the transferred material correctly and whether source references remain accessible.
CloudFuze identifies Microsoft Copilot, Google Gemini, and Claude within the scope of its assistant migration offering. The announcement does not specify that every feature or data type is supported across every possible source-and-destination combination.
Recreating Copilot Studio agents in Gemini Enterprise
The initial agent migration path targets Microsoft Copilot Studio to Google Gemini Enterprise. Rather than simply moving conversation records, CloudFuze says it can recreate agents using Google’s Agent Development Kit (ADK).
The migration covers agent instructions, topics, child agents, knowledge sources, connector tools, Model Context Protocol (MCP) integrations, flows, and Dataverse tables. CloudFuze also says it can preserve selected attributes, including display names, descriptions, permissions, and sharing settings.
Connectors may need to change when an agent moves between ecosystems. CloudFuze describes mapping Microsoft services to Google Workspace equivalents, such as Microsoft Teams to Google Chat, and replacing web-browsing integrations with Google Search.
These translations are important because agents often depend on external tools and data sources to complete tasks. Recreating an agent’s instructions without accounting for its integrations could leave it unable to perform the same functions after migration.
Still, moving an agent between platforms is not necessarily a one-to-one conversion. Differences in available tools, APIs, permissions, data models, and runtime behavior can require adjustments. The announcement does not provide independent test results demonstrating functional parity across all migrated agents.
Dry runs and enterprise migration planning
CloudFuze says organizations can run a dry migration to identify potential issues before starting the actual transfer. Once migration is complete, the company says agents can be used on the destination platform.
A preliminary run can help IT teams identify missing dependencies, incompatible configurations, or data that requires additional preparation. This is particularly relevant when agents connect to enterprise records, collaboration systems, and internal workflows.
Organizations should also assess access controls, data retention, audit requirements, and the handling of sensitive information before migrating AI histories and agent configurations. Preserving permissions is useful, but administrators still need to verify that access rights remain appropriate in the destination environment.
CloudFuze founder and CEO Ravi Poli said the company developed the offering after customers repeatedly asked how to preserve AI conversations, files, and agents during platform migrations.
AI portability becomes an enterprise concern
The launch comes as businesses evaluate AI platforms alongside their existing cloud, productivity, and enterprise software environments. Microsoft has reported that more than 230,000 organizations have used Copilot Studio to build agents, according to the figure cited in CloudFuze’s announcement.
As organizations build more customized agents, the effort required to move between platforms may become a factor in technology decisions. Migration tools could help reduce the cost of switching, although compatibility, governance, and destination-platform capabilities remain important considerations.
CloudFuze’s offering positions AI migration as a way to retain more of the knowledge and configuration built around enterprise AI systems. Its practical value will depend on the breadth of supported migrations and how reliably conversations, permissions, integrations, and agent behavior survive the transition.
Market Landscape
AI migration is emerging as a distinct enterprise requirement as organizations build custom assistants and agents across productivity and cloud ecosystems. Unlike conventional file migration, AI migration can involve conversation histories, agent instructions, knowledge sources, tools, and workflow logic.
CloudFuze is targeting this challenge with assistant migration and an initial Copilot Studio-to-Gemini Enterprise agent migration path. The opportunity is to reduce disruption when organizations change platforms. Key evaluation criteria will include migration completeness, integration compatibility, security controls, and whether recreated agents behave as expected.
Top Insights
- New migration category: CloudFuze is targeting AI assistants, conversation histories, artifacts, and custom agents.
- Initial agent migration path: The company is offering migration from Microsoft Copilot Studio to Google Gemini Enterprise.
- Agent configuration transfer: Supported components include instructions, knowledge sources, connectors, MCP integrations, flows, and Dataverse tables.
- Cross-platform connector mapping: CloudFuze describes replacing selected Microsoft integrations with Google Workspace equivalents.
- Validation is essential: Organizations should test permissions, dependencies, data integrity, and agent behavior before relying on migrated systems in production.
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