CDATA has implemented Connect AI, a managed model context protocol (MCP) platform designed to provide artificial intelligence applications with live managed access to over 300 enterprise systems.
Connect AI aims to bridge the gap between AI tools and enterprise data by integrating with AI assistants, agent orchestration platforms, workflow automation solutions, and embedded AI applications. The platform provides in-place data access and maintains semantics and relationships within business data. This allows AI to interpret the context rather than simply obtaining raw information.
The solution utilizes the same connectivity technologies established among major technology companies such as Palantir, SAP, Salesforce Data Cloud, and Google Cloud. The technology is reconfigured within Connect AI, specifically addressing the needs of AI workloads and is equipped with real-time semantic integration capabilities. According to the company, thousands of users have already connected hundreds of data sources to AI assistants via MCP servers, indicating the need for governed contextual enterprise data integration in AI projects.
Manish Patel, chief product officer at CDATA, highlighted the need for real-time, contextually recognized data access in AI initiatives. He said,
Companies wanting to operate their business data safely and effectively with AI requires real-time access in conjunction with semantic understanding. AI needs to understand the meaning of the data, not just where it lives. Connect AI allows businesses to deliver AI applications for the first time, providing live access to data across hundreds of systems using contextual intelligence that transforms AI from productivity experiments to trusted enterprise tools.
To address the core challenges outlined in recent MIT research, Connect AI was developed to tackle the main reasons why 95% of reported corporate AI pilots have no measurable business impact. Issues surrounding data access and governance. The platform provides direct data live access, thereby preserving the inherent contextual relationships between the data elements that AI needs to make complex decisions.
Security and governance are also essential aspects of Connect AI. Inherits user permissions and authentication from the source system, ensuring that AI access matches organizational control. Access to data is recorded under the identities of the authenticated user or agent, creating a comprehensive audit trail. Additionally, AI-specific controls can be applied to manage them within the solution.
Business Applications
Connect AI is already in use by businesses, enabling AI applications to provide contextually accurate responses from business data in seconds. This has been improved in traditional ways that require days or weeks to generate reports. The ability to manage queries across different systems while maintaining semantic understanding, benefits different teams. Sales can gather pipeline insights, marketing can analyze campaign performance, and finance can all use AI assistants to generate live budget updates.
Independent software vendors (ISVs) can connect AI to products and provide self-service integration between the user's data source and the agent service of ISVS. This white-label option allows technology companies to provide AI agents with access to the full semantic context of their customer's data, potentially increasing the effectiveness and responsiveness of their solutions.
Bhavik Paryani, growth and strategy leader at Paryani Construction, explained the impact AI has had on day-to-day operations. He said,
Connecting CDATA's AI to Acumatica completely changed the way you access your ERP data. I was able to pull out live financial data and create an interactive dashboard in the middle of a project meeting. Our team quickly jumped into the numbers and got the answers on the spot. Having instant access to this type of business data through a quick conversation with AI will change the game about how we operate, and promote our ability to deliver projects on time, budgetary and highest quality standards.
Industry perspective
Industry analysts are focusing on the ongoing challenges companies face in ensuring the quality and consistency of AI scaling and data integration. Stephen Catanzano, Senior Analyst, Data Management, Enterprise Strategy Group, Comments
Data is often unsiloed, inconsistent, poor governance, and often creates risk and inefficiency, making it difficult to expand AI. Many AI initiatives are stalling as businesses struggle to integrate multiple data sources while maintaining compliance. Tools such as CDATA's Connect AI are emerging in response to these broad market challenges, reflecting the company's vision to streamline AI-enabled data access across its enterprises.
CDATA CEO Amit Sharma stated Connect Connect, the release of AI within the broader context of the company's goals,
Connect AI represents an important milestone in CDATA's mission to make every company “AI-Ready” with real-time semantic intelligence. Over the years, we have connected applications to hundreds of data sources and leverage the deep expertise of enterprise data connectivity that we rethink in the age of AI. This allows users of AI Assistant and Agent Systems to provide groundbreaking access and experiences that were previously impossible. With thousands of customers from over 100 countries, they are uniquely positioned to capture large-scale market opportunities as businesses move from AI experiments to production deployments using intelligent contextual data access.
