Sisense Intelligence Overview

Sisense Intelligence brings together all AI-powered capabilities in the Sisense analytics platform. These tools are designed to simplify data exploration, accelerate insight generation, and support smarter, faster decision-making—regardless of user expertise.

Sisense Intelligence supports two core use cases:

  • Analytics Creation – Empowering users to build dashboards, data models, and generate insights more efficiently.

  • Data Exploration – Helping users explore, interpret, and act on data through AI-generated insights, explanations, and forecasts.

These use cases are delivered through two primary types of AI-powered experiences:

  • Conversational Interfaces – Found in tools like the AI Assistant and AI Studio, empowering you to interact with your data naturally using dialogue-driven prompts.

  • Contextual AI – Embedded experiences such as Sisense Narratives and our "Analyze It" capabilities that dynamically generate insights, explanations, and guidance directly within the analytics workflow.

Together, these capabilities support both new and experienced users—enabling faster onboarding, deeper insights, and a more approachable analytics experience.

In addition to these experiences, Sisense provides a robust developer experience through APIs and SDKs to support advanced customization:

  • REST APIs – Integrate and automate AI functionality across your analytics ecosystem.

  • Compose SDK – Build custom AI-enhanced workflows and embed intelligent capabilities directly into applications.

Below is an overview of the key AI features available in Sisense.

Generative AI - Powered by Large Language Models

  • Assistant - Interactively explore data and generate insights directly from the dashboard using a conversational interface.

  • Narrative - AI-generated textual summaries that describe widgets and highlight key insights from your data.

Analyze It - Analytical AI Features

  • Explanations - Identify the key contributors behind changes in your data to better understand underlying drivers.

  • Forecast - Predict future trends and outcomes using machine learning-based predictive modeling techniques.

  • Trend Analysis - Apply statistical trendlines to visualize and understand patterns in your data.

  • Exploration Paths - Provide users with AI-driven recommendations to explore related insights.

Natural Language Query

  • Simply Ask (NLQ) - Ask questions in natural language and receive instant data visualizations. This feature is based on traditional natural language processing models.