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Boomi Acquires Lunar.dev to Expand AI Gateway Governance Capabilities

AI gateway governance

Boomi has signed a letter of intent to acquire Lunar.dev, a Tel Aviv-based startup specializing in AI gateway governance and API traffic management. The deal, announced during the BoomiWorld 2026 conference, aims to integrate Lunar.dev's control layer into the Boomi Enterprise Platform. This move addresses the growing need for organizations to manage, monitor, and secure traffic generated by autonomous agents and large language models (LLMs).

The acquisition provides Boomi with critical infrastructure to handle the complexities of the agentic enterprise. Lunar.dev offers tools that allow developers to oversee third-party API interactions, ensuring that AI deployments remain cost-efficient and secure. By incorporating these capabilities, Boomi intends to offer a unified solution for governing how autonomous agents interact with sensitive enterprise data and external services.

Strategic Impact on AI Gateway Governance

Integrating AI gateway governance into a connectivity platform is a response to the rapid proliferation of AI agents within corporate environments. As businesses move beyond simple chatbots toward autonomous systems that execute tasks, the volume of LLM-related traffic increases. Lunar.dev provides the necessary visibility to prevent cost overruns and security vulnerabilities that often accompany unmanaged API usage.

The transaction is expected to close within the next 30 to 40 days. Once finalized, the technology will become a core component of Boomi's strategy to dominate the connectivity layer for AI-driven organizations. This acquisition follows a broader industry trend where integration providers are racing to build "agentic" control planes that sit between enterprise applications and the underlying AI models.

For decision-makers, this development highlights the shift from experimental AI to operationalized, governed agent networks. Companies utilizing the Boomi Enterprise Platform will soon have access to native tools for managing Model Context Protocol (MCP) gateways and LLM traffic. This integration simplifies the technical overhead required to maintain compliance and performance standards across diverse AI implementations.

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