AI race: Zoho Launches its Own LLM, Proprietary Models for Speech-To-Text Conversion

Homegrown technology company Zoho on Thursday announced its proprietary large language (LLM) model designed for enterprises using its suite of products, the latest move reflecting bold ambitions of Indian firms to build and innovate on their own AI stacks in the global tech race.

Zoho said it is also rolling out automatic speech recognition models for speech-to-text conversion in English and Hindi. The Chennai-headquartered company plans to further expand the available languages, beginning with other Indian and European languages.

Zoho top management said it has not seen these AI advances impact jobs and hirings.

The company further said it grew 32 per cent in 2024 in India, its second largest market globally after the US. The growth was driven by industries such as ITeS, banking financial services and insurance or BFSI, manufacturing, retail, and education.

At the Zoholics India -- its annual user conference held this year in Bengaluru -- the company announced proprietary large language model Zia LLM, prebuild AI agents and 'no code' agent builder.

Zoho CEO Mani Vembu said, "Our LLM model is trained specifically for business use cases, keeping privacy and governance at its core, which has resulted in lowering the inference cost, passing on that value to the customers, while also ensuring that they are able to utilise AI productively and efficiently." To a question on whether, the company would look to re-engineer or re-purpose its enterprise specific LLM for customers-centric GenAI model at some point in future, to rival, say a ChatGPT, especially given India's sovereign AI vision, Vembu said for the near future, the focus will be on enabling business customers, given vast opportunities and needs in this space.

"Based on our experience and research, we will decide on next course of action," he said at a briefing.

Zoho said its own large language model is built completely in-house by leveraging NVIDIA's AI accelerated computing platform.

"Trained with Zoho product use cases in mind, ranging from structured data extraction, summarisation... and code generation, Zia LLM comprises three models with 1.3 billion, 2.6 billion, and 7 billion parameters, each separately trained and optimised for contextual applicability that benchmark competitively against comparable open source models in the market," the company said in a release.

In the near term, Zoho will scale the LLM model sizes, starting with the first set of parameter increases by the end of 2025.

"While Zoho supports many LLM integrations for users, including ChatGPT, Llama, and DeepSeek, Zia LLM continues Zoho's commitment to data privacy by allowing customers to keep their data on Zoho servers, leveraging the latest AI capabilities without sending their data to AI cloud providers," the company said.

Zia LLM has been deployed across Zoho's data centres in the US, India, and Europe. The model is testing for internal use cases across Zoho's broad app portfolio, and will be available for customer use in coming months.

To enable immediate adoption of agentic technology, Zoho has developed a roster of AI agents contextually infused right into its products.

These agents can be used across various business activities, handling relevant actions based on the role of the user.

These include customer service agent for Zoho Desk that can process incoming customer requests, understand the context, and either answer directly or triage them to a human representative, acting as an efficient first line of assistance.

Zoho's platform-wide conversational AI assistant, Ask Zia, is bolstered with additional skills, tailored to data engineers, analysts, and data scientists, while supporting all users within an organisation.

At the time of deployment, an "agent" can be provisioned as a digital employee, maintaining the user access permission structure defined within the organisation.

Admins can perform behavioural audits as well as performance and impact analyses on "digital employees", ensuring that every agent is working as effectively as possible and within clear guardrails.

Citing examples of use cases, it said, several pre-built agents are available for users, such as candidate screener, which identifies and ranks the most suitable candidates for a specific job opening based on role requirements, skills, experience, and other key attributes; deal analyser, which can analyse deals and provide insights such as win probability, next best action, and follow-up suggestions, and revenue growth specialist, which suggests opportunities for upsell and cross-sell for existing customers.

The company has also launched AI agents specifically for Indian businesses for verification of PAN card, Voter ID, Udyog Aadhaar, GSTIN, driving licence, LPG connection and electricity bill.

These can be utilised for a variety of use cases, such as employee background verification by HR teams or for document verification in financial services organisations.