Inside Connect AI Gateway

CData introduces Connect AI Gateway, an enterprise AI connectivity and governance platform designed to link AI models and agents with business systems through schema-aware connectors, semantic context, access controls, and centralized auditing. The company argues that conventional AI gateways often manage model traffic or tool calls without sufficient understanding of source-system data, definitions, permissions, or business rules, which can reduce accuracy and increase token costs. The gateway resolves user prompts against a context graph, selects and scopes the necessary tools and data sources, routes tasks to suitable models, applies policies at the model, tool, and data levels, and records actions in an audit trail. CData says its approach can reduce unnecessary context and tool calls by performing operations such as joins outside the model, while allowing organizations to use hundreds of MCP servers, third-party servers, and multiple model providers without locking context into a single platform. CData Labs benchmarks cited in the announcement report higher accuracy and substantially lower token use than raw data-access approaches, although the product is currently offered through an early-access program.

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