CData Software announced Connect AI, the first managed Model Context Protocol (MCP) platform that integrates AI assistants, agent orchestration platforms, AI workflow automation, and embedded AI applications with more than 300 enterprise data sources. With governed, in-place access to enterprise data, Connect AI preserves data semantics and relationships, giving AI complete understanding of the context. The solution also inherits user permissions and authentication directly from the source and can be deployed in the cloud or embedded within software products in minutes with point-and-click configuration. Connect AI takes the same enterprise-grade connectivity technology already embedded by top technology companies including Palantir, SAP, Salesforce Data Cloud, and Google Cloud into their offerings, and reimagines it specifically for AI workloads with real-time semantic integration capabilities. Connect AI solves two core challenges: First, through data-in-place access, Connect AI preserves the rich contextual relationships that AI agents need for intelligent decision-making, delivering both immediate data access and meaningful data understanding. Second, Connect AI inherits existing security and authentication protocols set in the source system ensuring AI access remains aligned with organizational controls. Data access is logged under the identity of the authenticated user or agent for comprehensive governance. Additional AI controls can be layered and managed within Connect AI. Enterprises use Connect AI with AI apps to get contextually-aware answers from business data in seconds; work that previously required days or weeks of report building. Its ability to handle complex queries across diverse systems with semantic understanding enables sales teams to use Claude for pipeline insights, marketing teams to prompt ChatGPT for campaign analysis, and finance teams to rely on Copilot for real-time budget updates and financial reports. ISVs embed Connect AI directly within their products to provide their end-users with self-service integration between their data sources and the ISV’s agentic capabilities.