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CData launches Connect AI Gateway for agent governance

CData launches Connect AI Gateway for agent governance

3 Key Points

  1. What happened

    CData Software Inc. introduced Connect AI Gateway, entering early access today, letting IT teams register models, MCP servers and agents and set rules for each.

  2. Why it matters

    A single control point for agent access could help IT teams limit data exposure and model costs, and an audit trail shows which prompt, model, tool and policy drove a response.

  3. What to watch

    CData's 98.5% accuracy on 378 queries and 175-fold cost gap are company benchmarks, not independent tests, so the test is whether human review keeps shared context accurate.

WHO IT HITSEnterprise IT teams standing up AI agents for employees are the main audience, since the gateway gives them one place to register models, MCP servers and agents and to enforce each person's permissions when an agent retrieves data or acts on their behalf.

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Context & Analysis

CData's move extends its earlier Connect AI platform, which focused on giving AI tools governed access to enterprise systems, into a product meant to oversee the whole request: the initial prompt, model selection, data retrieval and any resulting action. That broader scope is what the company says would let administrators investigate an agent's behavior when an answer is wrong or an action is blocked.

The design leans on CData's existing connectors to hundreds of business applications and databases. Those connections are what let the gateway enforce a person's permissions when an agent retrieves data or acts on that person's behalf, with policies governing access to specific rows and columns. A context engine adds business definitions and less formal knowledge, held in a context graph outside individual AI models so an organization can reuse it when it changes models.

CData is careful about where the product stops. Executives said the gateway can import business definitions from analytics products but is not meant to replace a data catalog or semantic layer, and imported definitions from data catalogs are planned, not present. The open question is governance of shared knowledge: a correction useful to one employee could mislead others, so CData says human review decides what becomes shared context. How smoothly that approval process runs is likely to shape how much value customers get from the platform.

FAQ
How well does Connect AI Gateway answer enterprise queries?
In a company-run test of 378 enterprise queries, CData said Connect AI answered 98.5% correctly, compared with 65% to 75% for other MCP providers it tested. CData notes these are its own benchmarks, not independent tests.
Does the gateway replace a data catalog or semantic layer?
No. Executives said it can import business definitions from analytics tools like dbt and Power BI, but it is not intended to replace a full data catalog or semantic layer, and the initial release does not support imported definitions directly from data catalogs.
How does the gateway save on model costs?
It can set token budgets and route requests by policy, and CData plans to add automatic selection of the cheapest model. A separate test found a cost difference of up to 175-fold between models giving the same correct answer.
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