Zoho is making a bold statement in the enterprise AI space with the launch of “Zia,” the company’s proprietary large language model developed entirely in-house. This isn’t just another AI integration; it’s a comprehensive AI strategy that includes a powerful suite of AI agents, a no-code Agent Studio, and an expanded AI marketplace, all built on Zoho’s privacy-first infrastructure. I had the pleasure of sitting down with Raju Vegesna, Chief Evangelist for Zoho, to talk about Zia in advance of the launch and the highlights from our conversation are below.
Watch the full interview with Raju on our Age of AI podcast here:
The Technology Company’s Approach: Owning the Full Stack
Raju Vegesna, Zoho’s Chief Evangelist who has spent the past 25 years at the company, explains the Zoho philosophy: “How can we be an AI company if we don’t own the heart of it, which is an AI model?” This thinking reflects Zoho’s vertically integrated approach, where the company controls everything from data centers to applications.
“It’s like a car company owning how to create an engine,” Vegesna notes. “We want to own all aspects of the stack so that we can deliver good value to the customers.”
This approach allows Zoho to optimize its LLM for specific B2B business use cases rather than relying on generic models that come with performance penalties and higher costs.
Specialized AI for Business Use Cases
Unlike consumer-focused LLMs trained on open web data, Zia is designed from the ground up for enterprise scenarios. The model understands that business queries require different answers for different users based on permissions, work graphs, and individual expertise. I should also note that no customer data was used to train the Zoho model.
Vegesna shared compelling examples of Zia’s capabilities:
- Video Intelligence: Users can upload multiple videos to a hub and ask Zia to find specific answers across all content, with the AI pinpointing exact moments in specific videos where topics were discussed. When I think about this use case for even my small organization, it’s exciting. Extrapolating that out across an enterprise, and the data that will be available as a result, and it’s even more exciting.
- Audio Analysis: Customer support teams can upload all their audio files and ask about common complaints, with Zia identifying exact locations where issues were raised. This is another capability that I find tremendously exciting and which will hopefully quickly help identify common complaints and help organizations quickly solve for them.
These optimizations mean customers get specialized functionality without paying premium prices for generic AI capabilities.
Agent Studio: Democratizing AI Development
Recognizing that businesses have unique needs, Zoho also launched Zia Agent Studio, a no-code platform for building custom AI agents. While Zoho provides dozens of out-of-the-box agents, the platform enables customers, developers, and partners to create specialized agents for their specific functions, industries, or use cases.
“People are creative and they have very specific use cases,” Vegesna explains. “We cannot practically create every single agent users need.” Zia Agent Studio fills this gap with appropriate guardrails and governance built in, shortening the time to value for customer AI initiatives.
Model Context Protocol: Breaking Down Silos
Not surprisingly, Zoho is also embracing the Model Context Protocol (MCP), a new standard that allows different AI systems to communicate seamlessly. Through MCP, Zoho data can be accessed by any compliant agent, enabling customers to integrate workflows across multiple vendors without requiring developer expertise.
“The power moves to the customer,” Vegesna emphasizes. “They don’t have to be a developer to integrate two things. All you need is an agent that talks in the MCP language.”
Privacy-First AI in an Era of Data Concerns
Perhaps most importantly, Zoho’s approach addresses growing privacy concerns around AI. By controlling their entire stack, including the AI models, Zoho can guarantee where customer data is stored and processed.
“When you send information to an AI model, is there a guarantee that the AI model forgets that information?” Vegesna asks during the course of our conversation. “We can’t offer the same guarantee if we don’t control the model.”
This vertical integration becomes crucial as some customers request deployment of Zoho’s models within their own infrastructure, behind their firewalls, for maximum privacy protection.
The Future of Enterprise AI
Looking ahead, Vegesna acknowledges the transformative potential of AI across all aspects of business. “AI is going to change a lot of things,” he notes, comparing the current moment to previous technology shifts but emphasizing that AI is unique in disrupting creation time, not just distribution.
“Previous innovations changed distribution time… but this one is changing creation time because we can create software by asking AI to do it.”
Zoho’s comprehensive AI strategy—from proprietary models to agent marketplaces—positions the company as a significant player in the enterprise AI space, offering businesses a privacy-conscious, vertically integrated alternative to generic AI solutions. As AI continues to reshape business software, Zoho’s approach of owning the entire stack may prove to be a decisive competitive advantage.