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The news On July 17, 2025 Zoho launched Zia LLM and deepened its AI portfolio with agents, an agent builder, MCP support and an agent marketplace. Key announcements from the press release include: In-House LLM : Zoho has developed its own large language model, Zia LLM, which comes in three sizes (1.3B, 2.6B, and 7B parameters) to optimize for different business use cases. This allows customers to leverage AI while keeping their data within Zoho's ecosystem, ensuring privacy. The three models allow Zoho to always optimize the right model for the right user context, striking the proper balance between power and resource management. This focus on right-sizing the model is an ongoing development strategy for Zoho. Speech-to-Text Models : The company also unveiled two proprietary Automatic Speech Recognition (ASR) models for English and Hindi, with plans to support more languages in the future. Prebuilt AI Agents : To facilitate immediate adoption, Zoho has introduced a range of AI age...

The analyst’s day is full of research. Now, this is the age of AI and AI is here to help, isn’t it? As everyone is talking about copilots and AI agents, why not using the tools at hand to do a little research on research. NB., no one really has a good definition of an AI agent, so this might become an additional topic for research. But I digress. Imagine the following project at hand, which is not only interesting for analysts, btw, but also for a variety of roles in the corporate world. Let’s call it vendor (competitor) monitoring. The job is the following: Research reputable sites for news about a number of vendors, relating to a set of keywords. Reputable sites are high quality news sites, high quality tech publications, high quality analyst sites and, of course the news pages of the vendors in question. Limit the time frame of the search matching to the cadence of my information requirement, e.g., “yesterday” for a daily update or “last week” for a weekly update. Provide a summary ...

During ZohoDay24, Zoho amongst other topics, gave some insight into how the company looks at AI. Raju Vegesna presented Zoho’s AI vision and progress. Additionally, I had the opportunity for a one on one with Zoho’s director of AI research, Ramprakash (Ram) Ramamoorthy . If you want to listen and watch the interview, you can do this here . Both represented a vision that is refreshingly differentiated from the current hype with everyone and their dog talking like large language models, LLMs, are the everything one needs. Well, let me tell you: They aren’t. But let me come to this point later. In addition to not every language model being created equal, and typical for a hype, there is still too much talk about the technology itself, whereas in the words of Raju and Ram the best AI implementation is “ when the customer doesn’t know they are using AI but finds value in the output ”. This resonates very well with me, as one of my beliefs is that the customer shouldn’t care about the techn...

Now, that we are in the middle of – or hopefully closer to the end of – a general hype that was caused by Open AI’s ChatGPT, it is time to reemphasize on what is possible and what is not, what should be done and what not. It is time to look at business use cases that are beyond the hype and that can be tied to actual business outcomes and business value. This, especially, in the light of the probably most expensive demo ever, after Google Bard gave a factually wrong answer in its release demo. A factual error wiped more than $100bn US off Google’s valuation. I say this without any gloating. Still, this incident shows how high the stakes are when it comes to large language models, LLM. It also shows that businesses need to have a good and hard look at what problems they can meaningfully solve with their help. This includes quick wins as well as strategic solutions. From a business perspective, there are at least two dimensions to look at when assessing the usefulness of solutions that...