Boomi on Monday announced new capabilities for its Enterprise Platform aimed at helping organizations activate and manage data more effectively as they scale artificial intelligence and analytics operations.

The company said the updates focus on “data activation,” or delivering data across systems with the right context and timing to support AI, business intelligence and automation at the enterprise level.

Among the key enhancements is the addition of semantic context features designed to help AI agents operate using accurate and consistent business data.

“Last year, Boomi helped enterprises move from experimentation to execution. What we’re seeing now is clear: AI only delivers value when data is properly activated, trusted and governed first,” said Steve Lucas, chairman and chief executive officer of Boomi.

“Organizations don’t need more pilots, they need action-ready data,” he added.

The platform also introduces Meta Hub, a centralized system that aligns data standards across an organization to ensure both AI systems and users rely on consistent and trusted information.

To address regulatory requirements, Boomi launched a dedicated European platform instance, allowing customer data and system operations to remain within the region in compliance with the General Data Protection Regulation.

The company also unveiled a new SAP data connector that enables real-time data extraction without the need for custom development. This feature allows organizations to move and process data more efficiently for use in cloud and analytics platforms.

In addition, Boomi enhanced transparency in AI-driven workflows through new monitoring tools, including agent session logs and observability metrics. These features are designed to give organizations greater visibility into how AI agents operate, including performance, errors and resource usage.

The platform also introduces AI-driven recommendations to guide organizations in integrating and scaling AI agents across their systems.

Industry analysts said such developments reflect a growing shift toward more controlled and reliable AI deployment in enterprises.

“Enterprises are getting serious about accuracy as they move into production with agentic AI,” said Kevin Petrie, vice president and head of data management practice at BARC.