CData Software today launched CData Connect AI Gateway, the next evolution of the Connect AI platform designed to give organizations a single control point for the models, tools, data and actions used by AI agents and the individuals who work with them. The Gateway connects agents and individuals to enterprise systems through governed tools, applies company context at every step, enforces permissions down to the record and routes each request to the most efficient model for the task, helping enterprises move AI from answering questions to taking action.
Built on CData’s data layer, which already powers Palantir, Google, hundreds of enterprise products and thousands of customers worldwide, Connect AI Gateway understands the schemas, objects, relationships and operations of connected systems from day one. It imports the knowledge a company already holds, including metric definitions, business terminology and existing semantic models, and keeps what resolves each request, so context accumulates inside the customer’s environment and under its control. Schema-aware tools also send models only the information a request needs, cutting AI cost while keeping AI accurate across systems.
Bringing Enterprise Context to AI Agents and Individuals
Connect AI Gateway is built on CData’s portfolio of hundreds of schema-aware connectors. The connectors give AI access to the structure, relationships and semantics of the systems they reach, including applications, databases, data warehouses, on-premises systems and legacy environments. Its design makes five things possible:
- Enterprise MCP built in, useful on day one. Hundreds of CData-built connectors exposed as governed tools over live systems the moment an agent connects: SAP, NetSuite, Salesforce, the warehouses and databases, on-premises and legacy included. One managed platform replaces the server-per-system sprawl, and MCP servers a customer already runs are governed under the same policy.
- Context that compounds, under your control. The Gateway starts from the schemas and relationships the connectors carry, adds the metric definitions, terminology and semantic models a company already has, so Finance’s “revenue” and Sales’ “enterprise segment” resolve the same way every time, and turns approved corrections into reusable context, available to every authorized agent and user inside the environment.
- Security and governance at every step of the request. Agents act with exactly the access their users have, and policy applies to the model, the tool and the data. Every request carries the identity behind it, person or agent, with entitlements enforced at the source down to the record. Changes are validated against the system’s own business rules before they commit, and one audit trail traces any figure in an answer back to the prompt, model, tool and policy behind it.
- Reduced cost at every layer where tokens accrue. Schema-aware tools filter, join, and aggregate at the source, so only the answer set enters the context window, and routing sends each request to the most efficient model that can serve it. Spend is attributed and budgeted by team, agent, model, and tool.
- No stack to steer AI toward. No warehouse to fill, no model to favor, no platform to route deeper into. Context lives in a portable graph outside any model or data platform, so frontier, open-weight and locally hosted models all inherit the same definitions and know-how—switch models, and the context arrives with it. If a model provider fails, requests can fail over to another with the context intact.
In CData Labs research, prompts run through CData’s connectors returned correct results 98.5 percent of the time across CRM, project management, data warehouse and ERP systems, against 65 to 75 percent for competing MCP approaches. A second study ran 22 models, from economy to frontier tier, against live enterprise systems. Through governed tools every model returned the same correct answer, and the least expensive did it at 178 times lower cost than the most expensive. Governed tools also kept models to the records they were authorized to change, something no model managed on raw access.
One Governed Path for Every Agent Interaction
As enterprises move beyond AI assistants and toward agents that execute business processes, organizations need visibility and control over more than the model generating a response. They need to know which systems an agent accessed, what data it used, which policies governed the interaction, and what actions it ultimately took.
Connect AI Gateway answers those questions from one place. Every agent interaction travels one governed path between the agent and the systems where work gets done: grounded in company context, checked against policy at the model, the tool, and the data, and logged from the prompt to the record it touched. Because that path is built on CData’s own connectors, organizations get this control without building and managing separate infrastructure for every system an agent reaches.
That’s what lets enterprises put agents into business-critical workflows—taking action, with data, context, security, and cost under control.
Availability
CData Connect AI Gateway is available through an early access program beginning September 29, 2026.
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This entry was posted on September 29, 2026 at 8:23 am and is filed under Commentary with tags CData. You can follow any responses to this entry through the RSS 2.0 feed.
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CData Launches Connect AI Gateway, One Control Point Between AI and the Systems That Run the Business
CData Software today launched CData Connect AI Gateway, the next evolution of the Connect AI platform designed to give organizations a single control point for the models, tools, data and actions used by AI agents and the individuals who work with them. The Gateway connects agents and individuals to enterprise systems through governed tools, applies company context at every step, enforces permissions down to the record and routes each request to the most efficient model for the task, helping enterprises move AI from answering questions to taking action.
Built on CData’s data layer, which already powers Palantir, Google, hundreds of enterprise products and thousands of customers worldwide, Connect AI Gateway understands the schemas, objects, relationships and operations of connected systems from day one. It imports the knowledge a company already holds, including metric definitions, business terminology and existing semantic models, and keeps what resolves each request, so context accumulates inside the customer’s environment and under its control. Schema-aware tools also send models only the information a request needs, cutting AI cost while keeping AI accurate across systems.
Bringing Enterprise Context to AI Agents and Individuals
Connect AI Gateway is built on CData’s portfolio of hundreds of schema-aware connectors. The connectors give AI access to the structure, relationships and semantics of the systems they reach, including applications, databases, data warehouses, on-premises systems and legacy environments. Its design makes five things possible:
In CData Labs research, prompts run through CData’s connectors returned correct results 98.5 percent of the time across CRM, project management, data warehouse and ERP systems, against 65 to 75 percent for competing MCP approaches. A second study ran 22 models, from economy to frontier tier, against live enterprise systems. Through governed tools every model returned the same correct answer, and the least expensive did it at 178 times lower cost than the most expensive. Governed tools also kept models to the records they were authorized to change, something no model managed on raw access.
One Governed Path for Every Agent Interaction
As enterprises move beyond AI assistants and toward agents that execute business processes, organizations need visibility and control over more than the model generating a response. They need to know which systems an agent accessed, what data it used, which policies governed the interaction, and what actions it ultimately took.
Connect AI Gateway answers those questions from one place. Every agent interaction travels one governed path between the agent and the systems where work gets done: grounded in company context, checked against policy at the model, the tool, and the data, and logged from the prompt to the record it touched. Because that path is built on CData’s own connectors, organizations get this control without building and managing separate infrastructure for every system an agent reaches.
That’s what lets enterprises put agents into business-critical workflows—taking action, with data, context, security, and cost under control.
Availability
CData Connect AI Gateway is available through an early access program beginning September 29, 2026.
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This entry was posted on September 29, 2026 at 8:23 am and is filed under Commentary with tags CData. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.