The gateway that makes AI more accurate, for less
Company and system context travels with every request, so answers are accurate, within your access rules, from the lowest-cost model that fits the task.
Ensure AI knows your business, grounded in your systems and context
Built on CData's enterprise MCP platform, Connect AI brings together the agents, models, and context with direct access to your systems.
Learn more about the enterprise MCP gateway
More accurate answers, lower costs, and full control
A gateway can only control the context and governance it can access. CData starts with the source connection, so every request carries full business context and is governed end-to-end.
Spend fewer tokens—and less on every token.
The gateway sends each request only the context it needs and processes data in the platform, so the model burns fewer tokens — then routes to cheaper models that can deliver the same quality answers.
- Cut retries and extra turns with company and system context
- Run joins, filters, and calculations in CData before data reaches the model
- Send the model only the results the task needs, so it reads fewer tokens
- Keep toolsets lean so agents pick the right tool
Policy at the model, the tool, and the record.
Govern every step of AI interaction from the model call down to the record retrieval from one control plane.
- Set agent guardrails with runtime controls
- Create and manage policy with natural language or code
- Authenticate every identity at runtime down to the source
- Give agents controlled access to precise tools and toolkits
Ground every agent in your business context.
An agent can only be as accurate as what it knows about your business. The gateway applies your context to every request so answers are grounded, not guessed.
- Keep company and system context in one place, shared across every model and agent
- Import or create semantic definitions
- Capture the working knowledge that never made it into a schema
- Create data models and virtualizations to shape connected data
- Give AI a deep understanding of every source system
Works with what you use today and tomorrow
Apply your context across the AI tools your teams work in, the models you approve, and the systems where work happens — all through one gateway.
+ any agent you build
+ local deployments
See the full model catalog
+ hundreds more of CData-owned, custom, or third-party MCP servers
See the full MCP Server catalogProven in production
CData runs critical data workflows for internal teams—and ships as embedded connectivity inside customer-facing products.
CIO, Anaqua
One control plane
for connectivity, governance, and context across every AI model and system
6–8 weeks
from evaluation to company-wide rollout
Director of Product Management, Google Cloud
Hundreds
of data sources now accessible within Google Cloud—SaaS, NoSQL, legacy systems, and more
Zero
custom integration code required to connect Google Cloud to enterprise data sources
Head of Engineering, Palantir Technologies
One
unified metadata layer harmonizing data access across all source systems inside Foundry
Faster
time to AI-ready data for Foundry users, with CData handling all connectivity complexity
VP of Product, Salesforce Data Cloud
The context layer decides
Two CData Labs studies, one conclusion: accuracy, safety, and cost are determined by the layer that connects AI to your systems—not by the model.
98.5%
correct through Connect AI
Connect AI answered 98.5% of queries correctly; other MCP providers scored 65–75% on the same set. The difference: Connect AI grounds every request in your schema and business context before it reaches the model. Based on internal testing by CData Software (Q4 2025). No independent third-party verification. Actual accuracy gaps varied among platforms and MCP approaches, testing conducted using sandbox accounts containing known data sets that mirror production account structures. Results may not be representative of performance in live production environments, and results may vary. Organizations should conduct their own independent testing before making purchasing or implementation decisions. 75% range of average accuracy across platforms, results differ by MCP approach.
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178×
cost spread for the same correct answer
Connect AI delivered the same correct answer across models at up to a 178× difference in cost. The difference: Connect AI controls for accuracy and safety, so model choice becomes a cost decision. Based on internal testing by CData Software (Q3 2026). No independent third-party verification. Actual cost gaps varied among models, testing conducted using sandbox accounts containing known data sets that mirror production account structures. Results may not be representative of performance in live production environments, and results may vary. Organizations should conduct their own independent testing before making purchasing or implementation decisions.
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Put the gateway to work
One platform, two teams: IT teams that run AI safely, and business teams that get more productive with AI.
Connect AI to your business. Control every interaction.
Early access is open. Bring your systems, your models, and your policies.