New AI agents from Zoho handle customer service, sales analysis, and recruitment screening, providing ready-made solutions for common business functions.
Global software company Zoho Corporation has launched a comprehensive artificial intelligence portfolio, including its own large language model and AI agent marketplace, positioning itself as an alternative to major cloud providers for small and medium enterprises seeking AI capabilities without data privacy compromises.
The announcement, made from Adelaide, comes from the Austin, Texas-headquartered company with international operations based in Chennai, India. The launch includes Zia LLM, a proprietary large language model built entirely in-house using NVIDIA’s AI platform, alongside 25+ ready-to-deploy AI agents and a no-code agent builder called Zia Agent Studio.
Homegrown AI models target business
Zoho’s Zia LLM comprises three models with 1.3 billion, 2.6 billion, and 7 billion parameters, each optimized for different business contexts including structured data extraction, summarization, and code generation. The company claims these models benchmark competitively against comparable open-source alternatives while maintaining data privacy by keeping customer information on Zoho’s own servers.
“Today’s announcement emphasises Zoho’s longstanding aim to build foundational technology focused on protection of customer data, breadth and depth of capabilities, and value,” said Mani Vembu, CEO at Zoho. “Because Zoho’s AI initiatives are developed internally, we are able to provide customers with cutting-edge tool sets without compromising data privacy and organisational flexibility, democratising the latest technology on a global scale.”
The company has also developed two Automatic Speech Recognition models for English and Hindi that Zoho claims perform up to 75% better than comparable models across standard tests while maintaining low computational requirements.
Ready-made agents for business functions
For immediate deployment, Zoho offers pre-built AI agents designed for specific business roles. The Customer Service Agent can process incoming requests, understand context, and either respond directly or route to human representatives. A Revenue Growth Specialist identifies upselling opportunities, while a Deal Analyser provides win probability assessments and follow-up suggestions.
The updated Ask Zia assistant now includes specialized capabilities for data engineers, analysts, and data scientists, handling tasks from building data pipelines to creating machine learning models through conversational interfaces.
SME-focused approach differs from giants
Unlike major cloud providers that typically charge per API call or token usage, Zoho’s approach targets smaller businesses that may find enterprise AI pricing prohibitive. The company’s 55+ integrated applications allow businesses to build custom agents using the same tools as Zoho’s internal developers, potentially reducing the need for multiple vendor relationships.
The Agent Marketplace will eventually allow ecosystem partners and developers to create and distribute agents, similar to traditional app stores but focused on AI-powered business functions.
Zoho has adopted the model context protocol (MCP), enabling third-party AI systems to access Zoho’s action library while respecting existing permission structures. This interoperability could benefit SMEs using multiple software platforms.
Gradual rollout planned
The offerings are currently in early access phases, with general availability expected by late 2025. Zia LLM will be deployed across Zoho’s data centers in the US, India, and Europe, with pricing structures to be announced at general availability.
Future developments include expanding language support, implementing Agent2Agent protocols for collaborative AI systems, and adding specialized skills for finance and customer support teams.
For SMEs struggling with expensive AI solutions that require sending sensitive data to external providers, Zoho’s approach offers a compelling alternative: keep control of your data, avoid per-usage pricing structures, and access enterprise-grade AI capabilities without the enterprise complexity. In an era where data privacy breaches make headlines and AI costs can quickly spiral, that combination of control, affordability, and capability could prove decisive for businesses seeking to compete in an AI-driven economy.
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