Zoho Evolves Analytics Platform to Enable AI Agents to Turn Data into Action
Zoho has evolved its business intelligence and reporting platform, Zoho Analytics, into an Agentic Analytics platform designed to help AI agents understand business data and translate insights into action.
Moving beyond traditional reporting and dashboards, the updated platform provides an intelligence layer that gives AI agents the business context they need to interpret information, generate relevant insights and support operational decisions.
As enterprises accelerate AI adoption, a key challenge is the lack of business context. AI models often struggle to interpret organisation-specific terminology, departmental relationships and internal governance requirements. Zoho addresses this through a native architecture that embeds business context into the analytics platform, reducing the need for complex, disconnected external data warehouses. The new capabilities are available across Zoho’s UAE and KSA data centres.
“We are at the beginning of the next leap forward in data analytics, where a strong data foundation is the starting point for all agentic activity in business operations,” says Hyther Nizam, CEO at Zoho, Middle East and Africa (MEA). “Agents, however, cannot function only with data, but require a robust intelligence layer. Today’s updates to Zoho Analytics provide that and more: one open and extensible trusted intelligence layer that gives every AI tool in your business the context, metrics, and governance to deliver answers users can rely on.”
Embedding business context into analytics
Zoho Analytics builds its data intelligence around an organisation’s data structure through two key components: a semantic layer and an ontology layer.
The semantic layer acts as a business glossary for AI, defining key terms, metrics and their meanings. This helps AI interpret information in the context of an organisation’s operations. The ontology layer maps business entities, their relationships and how they connect across the organisation, enabling AI to generate insights and recommendations that reflect actual business requirements.
Governance and oversight are also built into the platform, giving businesses greater control over data access and costs, helping reduce errors and ensuring that information is used appropriately by AI agents. These controls are particularly relevant as organisations navigate an evolving AI regulatory landscape.
Ask Zia brings multi-agent intelligence to business users
The intelligence layer is designed to deliver consistent and repeatable insights, enabling agentic AI to ask questions, understand information, make decisions and take action based on business-specific data.
At the centre of this experience is Ask Zia, Zoho Analytics’ conversational super-agent for business intelligence. It uses a multi-agent architecture spanning data analysis, modelling, visualisation, preparation, coding and actions.
A central agent plans and orchestrates tasks among specialised sub-agents, all of which work with the same semantic layer, ontology and conversational context. This allows users to move between tasks without losing context. For example, a user can begin with a data analysis and then create a data pipeline to prepare information for further use within the same conversation.
Businesses can also build custom agents for specific functions. These agents use the same underlying data, semantic models and knowledge base as Ask Zia. Support for the Model Context Protocol (MCP) enables them to connect with external tools and systems, alongside the built-in tools available within Zoho Analytics.
By bringing data analysis, business context, AI-powered insights and agent-driven workflows together, the platform aims to help organisations move from information to decisions and action with greater confidence.
Open architecture and developer capabilities
Zoho says its semantic and ontology layers are native to Zoho Analytics, rather than requiring a separate data platform or cloud data warehouse. Businesses can create multiple semantic models for different operational contexts, allowing departments such as finance and operations to work with definitions relevant to their respective requirements.
Compatibility with Apache Ossie also allows organisations to make their business definitions portable rather than locking them into the Zoho platform. Semantic models can be created and edited without coding.
For developers, the platform adds headless business intelligence capabilities, local and remote MCP servers, and a command-line interface. These tools enable analytics and intelligent agents to be embedded directly into external applications and developer workflows. The update also includes a dedicated Claude plug-in.
