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Atoti Intelligence introduces two in‑built AI tools, Auto‑Explain and Visualize This. They are designed to work directly within Atoti UI. Users can interact with their data using natural language, generate insights instantly, and understand what is driving changes in their metrics.

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What is Auto-Explain?

Auto‑Explain is a feature that automatically analyzes variations in data and identifies the root causes behind them. When a metric changes between two points (across dates, categories, products, or any other dimension) Auto‑Explain breaks down the shift to show which underlying factors contributed most. It operates directly in Atoti UI, allowing users to launch explanations as soon as they notice an unusual movement in a chart, KPI, or table. This supports fast, in‑context exploration without interrupting the analysis flow.

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Why use Auto-Explain?

Auto‑Explain helps users understand their data faster by:
  • Reduces the time spent investigating unexpected metric changes
  • Identifies the dimensions that drive variations are automatically
  • Provides clear, easy‑to‑interpret explanations
  • Works seamlessly with the existing Atoti data model
It is especially valuable for analysts who need quick clarity on performance drivers in complex, multidimensional datasets.

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What is Visualize This?

Visualize This is an AI‑assisted visualization feature that lets users generate charts, dashboards, and insights through natural language. By interacting with an integrated AI assistant inside the Atoti UI, users can ask for visualizations conversationally, without having to configure chart settings manually. The AI assistant is supported by Atoti‑specific tools that understand the platform’s data structures. This means it generates visualizations that are accurate, meaningful, and aligned with the dataset.

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Why use Visualize This?

Visualize This is powered by a large language model with access to Atoti-specific tools. This combination makes it useful in three ways:
  • Data visualization: Create charts, dashboards, and multi-widget pages from natural language requests, without manually configuring widgets. The assistant selects appropriate visualization types and maps your data to them.
  • Cube knowledge: Ask questions about your cube structure — available measures, hierarchies, dimensions — and get answers drawn from the Atoti context provided to the assistant.
  • General-purpose assistance: Because the assistant is backed by an LLM, it can also handle any question you would ask a conversational AI, from explaining a concept to writing a cookie recipe.