CData Unveils ConnectAI: Bridging AI Systems with Enterprise Data Sources

CData links AI systems to more than 300 data sources - SiliconANGLE

CData Software Inc., the maker of a platform and drivers that connect data from multiple sources to applications, today announced a version of its product designed for artificial intelligence assistants, workflow builders and agent frameworks. The company said ConnectAI provides real-time, governed access to more than 300 enterprise data sources using the Model Context Protocol, a standard framework that lets AI systems securely connect to and interact with external data sources and applications. "It's a single platform that allows you to establish connections to and manage the enterprise sources that you have across your business, whether [large language model], agentic platform or workflow platform," said Will Davis, CData's chief marketing officer. "The focus is taking this connectivity that we've built and evolving it to meet the needs of where organizations are going with AI." CData, which has raised over $500 million in venture capital and private equity funding, provides real-time access to more than 300 applications, databases and web application programming interfaces with a self-service approach that resolves format variances and allows applications to read and write to multiple data sources simultaneously. The company built on its existing technology to create ConnectAI, said Chief Product Officer Manish Patel. "Enterprises need to have a centralized, governed way to manage connectivity across agents; they're not just going to use open source or a variety of connectors in the background," he said. He likened MCP to "USB-C for connectivity for AI," allowing platforms like Anthropic pbc's Claude, the open-source LangChain LLM framework and OpenAI LLC's ChatGPT to access enterprise systems without custom integrations. CData's connectors standardize communication using SQL-92, regardless of whether the underlying data source supports SQL. "You can speak one language to any one of those connectors, and we basically convert that SQL dialect into what the [application programming interface] understands," Patel said. CData made performance optimization a priority when developing ConnectAI, Patel said. "If you just give an LLM unfettered access to an API, it's going to pull a huge data set just to do an order-by," he said. "We understand how much of a query you can push down to the server side and how much we have to do client side, so we are minimizing the token consumption as much as we can." The product was tested with more than 1,600 users. The company plans to expand Connect AI's capabilities early next year by offering customization capabilities that enable customers to limit agent access to specific tools. Connect AI is available immediately.

New CData Software Provides AI Systems With Real-Time Data Access

The new CData Connect AI links AI assistants, agents and application workflows to more than 300 data sources, providing governed data with semantic-rich context. Data connectivity technology developer CData Software today debuted new software that integrates AI applications, agents and workflows with 300-plus data sources, providing AI systems with the governed, real-time business data they need to operate effectively. The company's new Connect AI offering, which builds on the company's flagship CData Connectivity Platform, links any AI application or framework that supports the Model Context Protocol (MCP) to more than 300 enterprise data sources such as databases and operational applications. CData executives, in a briefing with CRN, cited a recent "State of AI in Business 2025" report from the Massachusetts Institute of Technology that found that 95 percent of AI pilot projects are failing due to "brittle workflows, lack of contextual learning, and misalignment with day-to-day operations." [Related: The AI Data Problem: Bridging The 'AI Activation Gap'] "A lot of this, from our perspective, comes down to the ability to provide the right business data for the AI systems -- whether it's an LLM, agentic AI system or some sort of workflow platform -- to provide access to the business data for these systems and add the right business context effectively," said Will Davis, CData chief marketing officer, in an interview with CRN. CData, based in Chapel Hill, N.C., markets its unified connectivity platform for integrating structured data in real time across enterprise applications and infrastructure for business analytics and AI tasks and for operational applications such as Workday and Salesforce. The CData Connectivity Platform, which provides connectivity to on-premises and cloud data sources, uses SQL, ODBC and JDBC drivers, and a large suite of connectors to accomplish its tasks. In addition to the platform, CData offers data connectivity capabilities that can be embedded within other software products such as AI agents or operational applications. A number of leading software vendors incorporate CData's technology within their products include Salesforce and its Data Cloud and SAP with its Business Data Cloud. In May the company debuted a series CData MCP Servers to connect large language models (LLMs) via MCP support to more than 300 enterprise data sources. The new CData Connect AI is a managed MCP platform that provides data connectivity for AI agents and assistants, AI applications and AI workflows. The platform accesses data in-place in the source system -- rather than moving or replicating it -- and blends data across sources to create reusable virtual datasets. "I think the depth of connectivity is something that we believe is really powerful in the AI context and something that we're continuing to build upon," Davis said. "The barrier to ask questions of your data becomes so much lower." Putting Things In Context That means Connect AI, by inheriting existing security and authentication protocols set in the source system, provides secure, governed data access that the company says solves permission and authentication workarounds inherent in MCP. And by utilizing a data-in-place approach, the software preserves data semantics and relationships, giving AI systems complete understanding of the data context. AI systems need to comprehend what data means, not just where it resides, said Chief Product Officer Manish Patel said in the interview with CRN. "With Connect AI, companies can for the first time give AI applications governed, live access to data across hundreds of systems with the contextual intelligence that transforms AI from a productivity experiment into a trusted enterprise tool." Patel said CData Connect AI goes beyond just providing one-way access to data sources. The system, for example, allows an AI agent to act on the data, such as by creating a task for an operational application. CData is working with a number of regional systems integrators that use CData's software as part of the AI solutions and services they provide their clients, according to Davis. He said the company is in early discussions with a number of global system integrators about including CData as part of their AI strategy and services for building custom AI applications. The company is also touting the advantages for ISVs of embedding Connect AI directly within their products to provide users with self-service integration between data sources and an application's agentic capabilities. "Connect AI represents a significant milestone in CData's mission to make every enterprise 'AI-ready,' with real-time semantic intelligence," said CData CEO Amit Sharma in a statement. "We're leveraging our deep expertise in enterprise data connectivity -- built over years of connecting applications to hundreds of data sources -- and reimagining it for the AI era. This allows us to provide breakthrough access and experiences that simply weren't possible before for users of AI assistants and agentic systems."