Democratizing Enterprise AI With Governed, Real-Time Data

IVC Venture’s product, TheNoah.ai is a full-stack zero-code AI platform that helps enterprises experiment with and adopt AI across business use cases in days rather than months. With thousands of pre-trained models, agents, insights, and automations, it enables teams to launch AI-driven workflows quickly and with minimal resources—while maintaining clear ROI visibility from day one.

To deliver these experiences inside real enterprise environments, TheNoah.ai must operate directly on customer data across business systems. By leveraging CData’s MCP functionality within Connect AI Embed, TheNoah.ai standardized access to systems such as SAP, Oracle, Microsoft ERP, Slack, and Google Workspace—accelerating AI-driven workflows while reducing integration friction.

The challenge: Scaling embedded enterprise connectivity for AI workflows

TheNoah.ai’s platform is designed to support enterprise-wide search, insights, and agentic automations that act across multiple applications and workflows. To do this, AI models and agents must continuously interact with data from customer systems in real time.

Before CData, the team built integrations in house on a case-by-case basis. While effective early on, this approach became a bottleneck as customers expected connectivity across a broader mix of enterprise and legacy systems.

At the same time, scaling AI features—such as autonomous agents, intelligent recommendations, and workflow automations—required a consistent way for models to access and act on customer data. Without a standard integration layer, expanding AI capabilities across different customer environments slowed delivery and increased custom effort.

“Without a consistent integration layer, connecting AI models and agents to customer systems meant repeated custom work. That friction limited how quickly we could deploy AI workflows across different customers.”

— Akash Sureka, Founder, TheNoah.AI

The solution: Embedding standardized, enterprise-grade connectivity

To support AI workflows that depend on accurate, up-to-date enterprise data, TheNoah.ai embedded CData’s Connect AI Embed to deliver real-time, governed access to a broad range of sources—from legacy systems to modern SaaS—right out of the box. This allowed AI agents and models to securely query, reason over, and act on enterprise data without additional integration effort from customers.

With this foundation in place, TheNoah.ai standardized how its models, agents, and automations interact with connected data through a common MCP-based interface. Implemented in less than two weeks, it drastically reduced bespoke integration work, accelerated go-to-market execution, and made it easier to scale AI capabilities across different customer environments.

"It was very easy to implement CData, and within only 2 weeks, we were up and running with real-time access and governance covered."

​— Akash Sureka, Founder, TheNoah.AI

The outcome: Faster AI delivery with lower ongoing integration overhead

With CData embedded, TheNoah.ai was able to connect AI workflows, agents, and models to customer data in less than a week. Broad connector coverage and a standardized interface improved development velocity and shortened implementation timelines across different customer environments.

Just as important, TheNoah.ai no longer carries the ongoing burden of maintaining custom, one-off integrations. By relying on CData for connector coverage and updates, the team reduced both initial build effort and the ongoing maintenance work typically required to support enterprise and legacy systems.

The platform now delivers a more complete end-to-end AI experience—pairing pre-trained models, agents, insights, and automations with real-time, governed access to enterprise data. Customers can deploy AI-driven workflows faster, reduce operational costs, improve efficiency, and see ROI sooner without extended integration projects.

"CData helped us cut data integration timelines by over 80%—from a few man-months to less than a week—while eliminating the long-term maintenance burden of home-built custom connectors, freeing our teams to scale AI capabilities faster."

— Akash Sureka, Founder, TheNoah.AI

With CData in place, scalability is no longer a constraint, and TheNoah.ai can continue to build and roll out new AI models, agents, and automations across customer environments without added integration complexity. As agentic automations, intelligent insights, and outcome-driven AI use cases expand across customer workflows, scalable and standardized access to governed enterprise data becomes increasingly foundational. TheNoah.ai expects CData’s MCP capabilities to play an increasingly central role in its long-term architecture—serving as a standard interface between the AI layer and customer systems and enabling seamless, secure connectivity as the platform scales across industries and use cases.