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Sisense Ltd.

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Sisense is an AI-powered embedded analytics platform that enables developers to embed secure, governed analytics into applications under their brand.

Overview

Sisense is an AI-powered embedded analytics platform that enables developers and product teams to embed analytics and AI capabilities directly into their applications. The company’s mission is to empower app builders by delivering analytics that are accessible within branded product experiences, helping teams deliver data-driven insights to end users without leaving the application. Sisense serves software makers and organizations building customer-facing products, offering a scalable, secure way to connect data from multiple sources, model it, and present it through embedded analytics. The platform emphasizes a developer-first approach with APIs and software development kits, governance and security in multi-tenant environments, and the ability to ship analytics that match a brand’s look and feel. Sisense positions itself as a foundation for product-led analytics, designed to accelerate innovation and turn data into a competitive edge while maintaining control over definitions, metrics, and access. By grounding analytics in governed data and providing intuitive experiences such as customizable dashboards and narrated insights, Sisense aims to make analytics a natural part of product experiences across industries and company sizes. The result is a scalable, cloud-enabled solution that reduces time to insight, supports rapid iteration, and enables decision-makers to act on data with confidence.

Mission statement

We’re building a world where analytics fuel the applications that drive business forward.

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What we offer

Sisense AI Analytics Platform

Unlock actionable insights embedded directly into applications with Sisense AI analytics platform.

Pricing not published

www.sisense.com/ai-analytics-platform/

Market segments

Market size by segment

Growth potential (CAGR)

Embedded analytics

23.4 Billion USD15.8% CAGR

Embedding interactive, branded, and role-based analytics into customer-facing applications to deliver real-time insights, AI-powered recommendations, and scalable in-product dashboards for ISVs and product teams.

Products: Sisense AI Analytics Platform

Augmented analytics

16.6 Billion USD25% CAGR

AI-driven insight generation, natural-language querying, and agent automation that surface answers and recommendations from behavioral data.

Products: Sisense AI Analytics Platform

Enterprise semantic layer

1.5 Billion USD28% CAGR

Centralized semantic definitions and reusable business logic that deliver consistent, governed metrics across BI tools, AI agents, and applications to enable metric portability and BI modernization.

Products: Sisense AI Analytics Platform

Embedded analytics and white-labeling

77.52 Billion USD27.35% CAGR

Embed real-time dashboards, KPIs, and zero-click insights into web, mobile, and products via APIs and white-labeled delivery to surface analytics inside customer workflows.

Products: Sisense AI Analytics Platform

More information about our offering

Sisense AI Analytics Platform

Sisense AI analytics platform is a cloud-enabled analytics foundation that enables developers and product teams to embed AI powered analytics into applications. It supports code-first, low-code, and no-code approaches with Compose SDK and APIs to embed, customize, and scale analytics within products. The platform emphasizes governance, security, and multi-tenant isolation, enabling end users to ask questions, receive natural language explanations, and act on insights directly inside their workflows. It offers semantic enrichment, assistant interactions, and the ability to connect to external AI tools via MCP, delivering AI powered dashboards, narratives, and forecasts while keeping definitions and access under control.

Pricing not published

  • Transform Questions Into Insights
    Empower users to interact with data naturally, elevating the analytics experience through AI-driven responses.
  • Integrate Intelligence Directly
    Seamlessly incorporate insights into applications, driving engagement through embedded analytics.
  • Ensure Data Security
    Maintain strict control over data access and governance, ensuring compliance and security in analytics.
  • Reduces Operational Burden
    Managed services ensure consistent performance and updates, allowing teams to focus on analytics rather than infrastructure.
  • Ensures Continuous Operations
    Round-the-clock support and monitoring help prevent disruptions and improve user satisfaction.
  • Protects Sensitive Data
    Robust security measures ensure data integrity and compliance, building trust with users.
  • Enhance User Engagement
    Allow users to interact with analytics using plain language, making data insights more accessible and intuitive.
  • Implement Quick Changes
    Developers can create dynamic queries, charts, and filters in real-time, adapting to changing data landscapes.
  • Ensure Stability and Scale
    Utilizes a robust platform framework to deliver consistent performance and accommodate growth.
  • Generate Actionable Insights
    Leverage advanced generative AI techniques to automate insights generation, predicting trends and patterns to enhance data-driven decision-making.
  • Connect Data Easily
    Access a diverse range of data sources seamlessly with over 200 connectors, enabling streamlined data integration and analysis.
  • Enable Real-Time Insights
    Leverage live connections to cloud data warehouses for real-time analytics without the headache of data duplication.
  • Ensure Data Safety
    Governed access and strict security protocols protect your data and maintain compliance with industry standards.
  • Integrate AI Tools Securely
    Seamlessly connect AI tools with governed data models, ensuring secure and structured insights.
  • Simplifies Data Access
    Empowers users to easily model complex data systems without requiring extensive technical skills, enhancing productivity.
  • Embed Seamless Analytics
    Easily integrate analytics into applications, ensuring a consistent brand experience and functional flexibility.
  • Enhance AI Understanding
    Provide AI with the context needed to deliver accurate insights through enriched data semantics.
  • Engage Users With AI
    Advance user experience through an interactive dialogue with AI, making analytics more accessible.
  • Facilitates Growth
    Adaptable resources allow organizations to grow without delays, ensuring performance remains optimal as demand increases.
  • Flexible and Versatile Integration
    Easily incorporate analytics across various web frameworks to suit diverse development environments.
  • Accelerate Development Time
    Automates coding processes, allowing teams to focus on higher-level tasks and innovation.
  • Enhance Analytics Capabilities
    Integrate AI technologies to turn data into actionable insights more effectively.
  • Ensure Metric Consistency
    Utilize a robust semantic layer to maintain consistent metrics and access controls, ensuring reliable analytics across all user interactions.
  • Leverage AI Within Product
    Enable users to interact with their data through natural language queries and receive AI-driven insights directly within the product environment.
  • Secure Multi-Customer Deployments
    Implement strong security measures, ensuring tenant isolation and safeguarding data across multiple customer instances.
  • Automates Data Preparation
    Leverage AI to streamline the data preparation process, allowing users to focus on analytics while reducing manual tasks.
  • Enhances Data Flexibility
    Combine and analyze data from different systems seamlessly, providing a comprehensive view for informed decision-making.
  • Align with Brand Identity
    Create cohesive look and feel by customizing visualizations to adhere to your branding guidelines.
  • Predicts Trends and Alerts
    Utilize advanced forecasting to project future trends and receive alerts for anomalies, helping users stay proactive in their decision-making.
  • Enables Conversational Queries
    Empower users to interact with analytics through natural language inquiries, simplifying the data exploration process.
  • Personalize User Experience
    Customize analytics visuals and interactions, aligning them with the product's branding for a cohesive user journey.
  • Enhances Team Efficiency
    Facilitates data sharing across departments, improving decision-making and accountability.
  • Streamline Development Process
    Enhances communication and reduces friction between teams to speed up the embedding of analytics.
  • Extend Functionality
    Develop unique functionalities that cater specifically to business needs and enhance the user experience.
  • Integrate External AI Tools
    Seamlessly connect to third-party AI tools using APIs and the Multi-Cloud Platform (MCP) while maintaining strict governance over data access and metrics.
  • Empower Users to Analyze Data
    Provide users with the tools they need to explore data and generate their own insights independently within the embedded analytics platform.
  • Customize Analytics Experience
    Brand the analytics experience to align with your product's aesthetics, utilizing customizable components and theming options.
  • Facilitates Advanced Analysis
    Perform sophisticated data analysis and transformations directly within Sisense, integrating findings seamlessly into your workflows.
  • Streamlines Workflow
    Reduce manual effort and improve efficiency by leveraging Sisense's automation capabilities in data handling.
  • Integrates AI Tools Seamlessly
    Facilitate effective collaboration by connecting your Sisense data to the AI tools your users already rely on, enhancing analytic workflows.
  • Provides Clear Explanations
    Transform complex data into understandable narratives that clearly explain the drivers of the metrics, enhancing user comprehension.
  • Customizes User Experience
    Create personalized data views while maintaining a unified data model, catering to specific user needs without duplication.
  • Customizes User Experience
    Allow users to personalize their analytics experiences, driving engagement and usability through tailored dashboard options.
  • Stay Updated
    Frequent updates help users leverage the latest features and enhancements, ensuring optimal performance.

Sources

Methodology and sourcing behind the figures and links shown above.

Embedded analytics

Primary estimate based on a published projection (cited on embeddable.com) that the embedded analytics market grows from $23.4B (2025) to $101B (2035), implying ~15.8% CAGR. Supporting sources show smaller, earlier estimates (Reveal: $0.8B in 2019 to $1.3B in 2023 at ~10–15% CAGR) and a narrower IoT-embedded-analytics report with much higher CAGR (KBV: $1.4B in 2023 to $14.4B in 2031, 35.1%), indicating growth varies by scope and vertical.

Augmented analytics

Estimates based on published market reports in the search results: ResearchAndMarkets (via GlobeNewswire) reports an estimated market value of USD 16.6 billion in 2023 and a 28.0% CAGR to 2030; Mordor Intelligence projects USD 41.87 billion in 2025 and a 23.17% CAGR to 2030. I use the 2023 reported size (16.6B) and a midpoint CAGR (~25%) between the reported 23.2% and 28.0% to express growth potential.

Enterprise semantic layer

Search results show the enterprise semantic layer is positioned as a newly critical layer for enterprise AI and analytics (AtScale blogs, AtScale 2026 State report mention, CDOTrends article, Digetiers thought leadership), indicating accelerating demand but no explicit TAM figures in the provided results. Using internal market reasoning: treat the semantic layer as a specialized enterprise-software segment (SaaS/managed) addressing large enterprises. A conservative sizing assumption: a near-term commercial base of ~10,000 mid-to-large enterprise customers adopting paid semantic-layer solutions (or modules of larger platforms) with average vendor spend of roughly $100–200k/year yields an approximate market of $1.0–2.0B (midpoint ~$1.5B). Growth potential (CAGR ~28%) reflects rapid adoption driven by generative/agentic AI needs for governed, portable metrics, strong vendor investment and partnerships (AtScale integrations with Snowflake/Databricks/etc.), and comparisons to adjacent high-growth subsegments (metadata/knowledge-graph/AI-governance tooling), which have shown multi‑decade-high growth rates as enterprises operationalize AI.

Embedded analytics and white-labeling

Estimate uses an explicit 2026 embedded-analytics market figure from an industry article (77.52 billion USD) and a high-growth CAGR from a syndicated market report on augmented/AI-driven analytics (27.35%). Augmented analytics overlaps with embedded and white-label use cases, so the Mordor CAGR is applied as representative growth potential while the Querio figure is used for the current market-size estimate.

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