Zoho expands Analytics for agentic AI, opens new integration and embedded AI opportunities for partners

The upgraded platform adds a multi-agent architecture, MCP connectivity, and white-labelled AI agents, letting businesses move from analysing enterprise data to triggering workflows.

Zoho has expanded its Analytics platform with agentic AI capabilities, opening up new possibilities for systems integrators, software developers and technology partners to build data-driven solutions that connect enterprise information with automated workflows.

The upgrade introduces native semantic and ontology layers, a multi-agent architecture for its Ask Zia conversational BI system, and tools that allow developers to extend Zoho Analytics beyond its own platform through Model Context Protocol (MCP).

The changes will help businesses move beyond traditional reporting and dashboards towards AI systems that can interpret business data, understand organisational context and trigger actions. Zoho is also enabling organisations to embed and white-label AI agents within their own applications, portals and products.

For partners, the embedded AI and headless BI capabilities are particularly relevant. They provide ways to build integrations and incorporate analytics agents into customer-facing applications.

"The business intelligence industry is undergoing a fundamental transition from traditional human-driven analysis to intelligent orchestration," said Clarence Rozario, director of Product Management, Zoho BI and Analytics Platform.

He said AI agents need to understand an enterprise's metrics, hierarchies, boundaries and business vocabulary before organisations can trust them with operational decisions. Zoho's new semantic and ontology layers provide that context within Analytics.

The ontology layer maps an organisation's structure, while the semantic layer defines its business metrics and terminology. Together, they help AI agents interpret data according to the way a business operates. Organisations can create and edit multiple semantic models without writing code.

Zoho said these native capabilities also eliminate the need for a separate cloud data warehouse to build and manage semantic models.

MCP and embedded AI extend partner possibilities

The upgraded Ask Zia uses a multi-agent architecture that orchestrates six specialised agents covering data analysis, modelling, visualisation, data preparation, coding and SQL generation.

Users can handle complex requests through a single prompt, while businesses can build custom agents using the same knowledge base.

These agents can connect to internal and external systems through MCP and trigger automated workflows. Zoho has also added a workflow builder to Analytics, allowing businesses to design processes that connect insights with actions.

The platform's headless BI model gives developers and external agents access to Zoho Analytics through its MCP server, available in remote and local options. The server provides tools for data analysis, preparation and visualisation.

Zoho has also introduced a command-line interface and a Claude plug-in that allows users to work with Analytics from within Claude.

The embedded AI system allows organisations to deploy agents inside their own applications, portals and products with white-labelling support. Zoho said permissions and governance controls remain in place when these agents operate outside its platform.

These capabilities could be relevant to SIs and ISVs that build enterprise applications, data integrations and customer-specific solutions. They also give partners additional ways to connect Zoho Analytics with other business applications and AI tools.

Zoho is also adding 30 data connectors to over 500 options already available in Analytics. The new integrations include Zoho ERP, Zoho Spend, Zoho FSM, Zoho Shifts and Zoho Voice, alongside third-party services such as SAP, PayPal, Adobe Commerce, Twilio, Notion, Intercom, Supabase, Amazon DocumentDB and AlloyDB.

The platform will also support Apache Ossie, an open-source standard that allows organisations to define metrics and dimensions once and share those definitions across different BI tools and AI agents. Zoho said this makes business logic portable and helps prevent organisations from being locked into a single analytics ecosystem.

Governance and pricing remain key considerations

As businesses give AI agents access to enterprise information and workflows, Zoho is adding controls to monitor their activity and manage data access, usage and costs.

Its Data Catalog brings together data, metrics, analytics assets and models, with capabilities for data lineage, impact analysis, search and access-policy management. AI observability allows administrators to track which agents ran, who used them, what information they accessed and how they responded to queries.

Administrators can also monitor AI usage and costs across teams and manage Ask Zia. Organisations can choose between Zoho's own large language model and their preferred frontier model.

The platform also includes sandbox and deployment management. Teams can develop and test analytics assets and agents before publishing them to production, with the option to roll back to earlier versions.

Beyond agentic AI, the upgrade includes more than 50 additional capabilities, including new visualisations, custom visuals, pixel-perfect reports, scenario analysis, correlation matrices, VARX forecasting and a data science studio with Jupyter notebooks.

Zoho Analytics is used by over 100,000 businesses worldwide and is available through Zoho Cloud, on-premises deployments and public cloud infrastructure including AWS, Microsoft Azure and Google Cloud.

Zoho said pricing remains unchanged despite the updates, and each plan now includes Zoho LLM credits.

Cloud pricing starts at ₹960 per month, billed annually, for the Basic plan, which includes two users and 0.5 million rows. Additional users cost ₹200 per user per month, billed annually.

The latest cloud version is available now. Preview versions of pixel-perfect reporting, ontology and the semantic model will roll out globally over the next four to eight weeks. Updates to the on-premises version are expected in the first quarter of 2027.