CData Software unveiled major additions to its Connect AI platform, broadening its scope for enterprise, grade AI deployment support. The new features, presented at the Gartner Data & Analytics Summit, include advanced agent tooling, enhanced governance controls, and wider connectivity options to aid companies in shifting their AI experiments into fully operational systems. The new edition enhances the platform’s managed Model Context Protocol (MCP) technology by developing three fundamental aspects connectivity context, and control, necessary for the successful operation of AI. With these advancements, the company intends to tackle the ongoing data infrastructure issues that are most of the time the cause of generative AI projects not achieving the expected business results.
Addressing the Data Infrastructure Gap in AI Deployments
Although the pace at which enterprises invest in artificial intelligence is growing exponentially, the projects face the challenge of being deployed into production environments. Analysts predict that the world will spend $2.5 trillion on AI projects by the year 2026; however, the outcome of these projects is not as impressive as predicted. The main problem is not the capability of the artificial intelligence, but the complexity that arises when integrating the data with the enterprise infrastructure.
Research carried out in the industry has revealed that only a few organizations are satisfied with the current state of the artificial intelligence data infrastructure. In addition, many development teams have to build custom integrations that lack scalability. Furthermore, the AI development teams end up spending a significant portion of the implementation period connecting the data rather than focusing on the intelligent application development.
“AI agents are only as effective as the tools they can access and the data behind them, and only as safe as the controls governing both,” said Amit Sharma, CEO and Founder of CData. “This release gives teams the ability to build use-case-specific agent tools with the right business context, deploy them securely, and enforce granular controls over which data agents can access, which actions they can take, and under what identity. That’s what’s been missing, not better models, but the connectivity, context, and control that make agents trustworthy enough to run in the enterprise.”
Expanded Connectivity Across Enterprise Systems
The improved Connect AI platform establishes live, read, write access to over 350 enterprise data sources, thus allowing organizations to embed AI agents straight into their business systems without having to duplicate or physically move their data. One of the most significant new features is the Connect Gateway that authorizes AI workloads to securely connect with data sources behind corporate firewalls. Additionally, the gateway is compatible with major platforms like SAP, Microsoft SQL Server, and PostgreSQL, thus enabling AI, powered applications to function on live enterprise data no matter its storage location. The main benefit of this is the removal of complex data pipelines and the guarantee of up, to, date AI agent operations based on information directly extracted from working systems.
Also Read: Precisely Introduces AI Agents to Strengthen Data Integrity Suite for Enterprise AI Initiatives
Introducing New Tools for Context-Aware AI Agents
In order to enhance the way in which AI agents are able to interpret and interact with enterprise data, CData has developed an expanded range of agent tools that are intended to ensure structured access to enterprise business operations, thereby ensuring that the AI agents are exposed to the required level of context while avoiding unnecessary exposure to data or inefficient tool usage.
The new framework includes three categories of tools:
- Universal Tools, which provide a standardized interface for working across hundreds of connected systems.
- Source Tools, which allow tightly controlled interactions with specific enterprise platforms.
- Custom Tools, which enable organizations to create specialized operations tailored to internal workflows.
In addition, the platform introduces Workspaces and Toolkits, enabling organizations to define clear boundaries around what data and actions an AI agent can access. Each combination can be deployed as a dedicated MCP server, ensuring that agents operate only within approved operational scopes while maintaining strong governance and compliance.
Enterprise-Level Security and Identity Governance
Security and governance issues continue to be at the heart of the latest changes to the platform. The new and enhanced platform includes SCIM 2.0 integration with automated identity management and Custom OAuth Applications, which enable organizations to authenticate and manage AI interaction using their own identity management systems.
These new features ensure that every query generated by the AI is authenticated, authorized, and recorded, which means that organizations can have complete control over how the AI interacts with the business systems.
This is particularly important to organizations that operate in heavily regulated industries and need to tightly control access to data and related systems.
Benchmarking AI Data Accuracy
In order to gauge the capabilities of various MCP providers, CData carried out benchmarking exercises with five providers and a total of 378 real, life enterprise prompts from CRM ERP project management, and data warehouse systems. The findings indicated that CData Connect AI reached a 98. 5% accuracy level and drastically beat the other providers, whose scores varied from 65% to 75%. Besides, the test deciphered the usual breakdown points for other platforms, mostly when dealing with sophisticated requests related to date calculations, multi, condition filtering, and domain, specific business logic. Such accuracy is a major issue as more and more organizations are creating AI agents that can work autonomously and can handle multi, step workflows across different enterprise systems.
“AnySoft is an agentic coding tool that builds software that fits your business by ingesting, enriching, and unifying an organization’s live business data giving AI the context it needs to power everything from CRM to marketing automation,” said AnySoft CEO Alex Noe. “That means connectivity to every system our customers run on isn’t a nice-to-have, it’s foundational. CData Connect AI Embed gives them production-grade access to 350+ data sources with the control and compliance built into the data layer.”
“Connect AI has been a game changer for how we retrieve information from our enterprise systems using AI and the reason it works so well is how it manages context,” said Paul Kantorovich, Manager of FP&A and AI Strategy, Foodtastic.
Enabling the Next Phase of Enterprise AI
Right now, as companies are starting to use large language models interacting with live business data, the infrastructure that links these AI models to enterprise systems is becoming an essential pillar for digital transformation. With a stronger focus on connectivity, context, aware intelligence, and leading, class governance, CData is set to level up its Connect AI platform. It is their goal to support entities in moving quickly from their AI experiment phase to fully scalable AI production deployments.
