CData Software Released Connect AI Gateway

The new enterprise platform aims to improve AI model accuracy and reduce data exposure.

Updated on Sept. 29, 2026 in Artificial Intelligence

CData Software Released Connect AI Gateway

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CData Software Inc. has introduced its Connect AI Gateway, a platform designed to help IT teams register models and agents while enforcing strict user permissions. The tool has entered early access for enterprise users looking to better secure their data workflows.

Why it matters

The platform is designed to improve agent accuracy and limit data exposure by applying policies that restrict access to specific records. It also aims to control costs by managing token budgets and selecting the most appropriate models for specific tasks.

The system features a context engine that reuses business definitions from tools like dbt and Power BI to filter and aggregate data. It also enables model routing, with performance tests showing a 175-fold cost difference between different models.

The players

CData Software Inc.

CData Software Inc. is a data connectivity solutions provider that develops tools for integrating applications and databases.

The details

The Connect AI Gateway provides audit trails for prompts and policies while allowing IT teams to register MCP servers and agents. By capturing knowledge from documents and conversations, the platform minimizes context window data to optimize AI performance.

CData Software Inc. introduced the Connect AI Gateway and launched early access on September 29, 2026.

The Tech Race

The introduction of the Connect AI Gateway marks a formal attempt to standardize security protocols for Model Context Protocol (MCP) servers in enterprise environments. This development follows a broader industry trend of moving away from raw, insecure AI integration toward managed, policy-driven interfaces.

Enterprise IT users can expect improved control over AI agents, including the ability to enforce permissions and audit data usage. These features help teams reduce the security risks associated with connecting internal business data to large language models.

The takeaway

Organizations looking to deploy AI agents must prioritize systems that provide governance and auditability over raw connectivity. Implementing a gateway architecture helps ensure that business definitions remain consistent while controlling the costs of model usage.