Top 10 Embedded Analytics Tools in 2025

What is Embedded Analytic?

Embedded analytics is the integration of analytical capabilities directly into other software applications, platforms, or web portals, allowing users to access, analyze, and act upon data within the same environment they are already using. Rather than requiring users to switch to a separate business intelligence (BI) or analytics tool, embedded analytics brings data insights, visualizations, and interactive dashboards right into the workflow of the host application.

This integration is typically seamless and customizable, often white-labelled to match the look and feel of the host software, creating a unified user experience. Users can explore data through interactive charts, filters, and reports without leaving the core application, enabling real-time, informed decision-making. For example, a sales team can see pipeline analytics within their customer relationship management (CRM) system, or a finance team can access cash flow forecasts inside their enterprise resource planning (ERP) software.

Useful: Explore the components, benefits, use cases, and how to implement embedded analytics

Top Embedded Analytics Tools You Should Consider

1. Embeddable

Embeddable is a developer-first embedded analytics platform designed to help teams build fast, interactive, and fully customizable customer-facing analytics dashboards directly into their applications. It combines the flexibility of custom-built software with the ease of traditional BI tools, allowing users to create bespoke analytics experiences that match their platform's look and feel without using iframes, ensuring a native and seamless user experience. The platform supports easy embedding, real-time analytics, and high performance, enabling product and engineering teams to create analytics with minimal effort and fast deployment.

2. Sisense

Sisense Embedded Analytics is a feature-rich platform that allows organizations to embed real-time data insights, interactive dashboards, and AI-powered analytics directly within their own applications or products. It enables users to access analytic insights without switching platforms, improving user experience, decision-making speed, and engagement.

Sisense’s embedded analytics solution focuses on providing seamless workflows and real-time insights directly where users spend their time, such as business applications, enhancing productivity and data-driven decision-making.

3. ThoughtSpot

ThoughtSpot Embedded Analytics is an AI-powered analytics platform that enables businesses to integrate intuitive, search-driven data insights and interactive dashboards directly into their applications, portals, or products. It provides a Google-like natural language search interface that allows users to ask complex data questions and receive instant visualizations without SQL knowledge. The platform supports flexible embedding options such as JavaScript SDKs, REST APIs, and iframes, with extensive customization and white-labelling capabilities to match a company’s brand. Key features include AI-driven insights through SpotIQ, conversational analytics with Spotter, real-time data exploration, strong enterprise security, and developer tools for seamless prototyping and deployment. ThoughtSpot Embedded is designed to make data analytics accessible to non-technical users while providing powerful automation and integration capabilities for developers.

4. Qrvey

Qrvey is an all-in-one embedded analytics platform designed to help SaaS companies quickly integrate and deliver customizable, interactive analytics, reporting, and automated workflows into their applications. It supports data ingestion from various sources, including SQL, NoSQL, APIs, and unstructured data, and offers a powerful data engine for data transformation and management. The platform features self-service, drag-and-drop dashboard building, pixel-perfect report generation, role-based access controls, and a no-iframe JavaScript widget architecture for seamless embedding. Qrvey emphasizes ease of use for both developers and end users, providing a scalable, cloud-native, multi-tenant data lake built on Elasticsearch with robust security and automation capabilities. It aims to save development time by reducing the need to build complex analytics layers in-house, offering flexible deployment, and enabling companies to provide AI-driven insights and personalized analytics experiences efficiently.

5. Reveal BI

Reveal BI is an embedded analytics and business intelligence platform designed specifically for seamless integration into applications. It offers a true embedded SDK enabling developers to embed customizable, interactive, and branded dashboards and reports directly within software applications without using iframes, providing a native and cohesive user experience. Reveal supports a wide range of tech stacks including .NET Core, Java, React, Angular, VueJS, and more, and can be deployed on-premises, in the cloud, or hybrid environments. Key features include intuitive drag-and-drop dashboard creation, detailed drill-downs, advanced filtering, predictive analytics, and robust API support for customization.

6. Luzmo

Luzmo is an embedded analytics platform designed primarily for SaaS companies. It provides powerful, customizable, and intuitive data visualization and dashboard capabilities that can be seamlessly integrated into SaaS products, web platforms, or applications. This allows product teams to add impactful, user-friendly analytics and insights for their users quickly. Luzmo supports a variety of data sources and offers features like drag-and-drop dashboard creation, AI-powered insights, white-labelled dashboards, and client-specific personalized datasets. It aims to help businesses deliver meaningful data intelligence and actionable insights directly within their platforms without requiring extensive engineering or data science expertise.

7. Metabase

Metabase Embedded Analytics allows businesses to integrate interactive, customizable dashboards and charts directly into their own applications or websites, providing users with seamless access to data insights without leaving the app. It supports both simple iframe-based static embedding for public sharing and secure embedding with signed tokens for controlled, user-specific data access. Additionally, Metabase offers an Embedded Analytics SDK for React, enabling developers to embed individual components like charts or query builders with fine-grained customization and interactivity.

8. Yellowfin

Yellowfin Embedded Analytics is a flexible and scalable platform that seamlessly integrates interactive, white-labelled dashboards and reports directly into applications, providing users with an intuitive, data-driven experience within their existing workflows. It offers robust self-service BI, natural language querying, AI-powered automated insights, data storytelling, and extensive customization options to match branding requirements. The platform supports secure, multi-tenant deployments on-premises or in the cloud, with comprehensive APIs and SDKs enabling deep integration and control. Yellowfin focuses on enhancing user engagement through interactive reporting, real-time data access, and collaboration features, making it suitable for diverse industries aiming to embed advanced analytics while reducing development time and infrastructure costs.

9. Microsoft Power BI

Power BI Embedded Analytics is a Microsoft solution that allows developers to integrate fully interactive Power BI reports, dashboards, and tiles directly into web applications or websites, enabling users to visualize and analyze data without leaving their primary workflow. It supports two main embedding scenarios: embedding for customers (external users who don’t need Power BI licenses or sign-ins) and embedding for organizational users (internal users who authenticate with Power BI credentials). The platform offers rich customization options such as white-labelling, real-time data access, AI-driven insights, row-level security, and cross-device compatibility. Power BI Embedded aims to deliver seamless, secure, and engaging data experiences that empower users to make data-driven decisions efficiently within familiar applications, supported by extensive developer tools, SDKs, and APIs for streamlined integration and management.

10. Tableau

Tableau Embedded Analytics enables businesses to integrate highly interactive, customizable dashboards and visualizations directly into their applications or websites, offering users real-time data insights within their usual workflows. It features robust tools like a JavaScript API and REST API for deep customization and automation, and supports advanced analytics, predictive insights, and natural language queries. Tableau emphasizes security through role-based access control, single sign-on, and data encryption, making it suitable for multi-user environments with strict data governance. Though powerful and scalable, embedding Tableau in multi-tenant SaaS products can be complex and costly due to its architecture not being originally designed for multi-tenancy, often requiring workarounds for customer-specific data isolation.

Conclusion

The tools highlighted in this article - whether focused on seamless integration, real-time insights, or customizable visualizations - represent the forefront of innovation in 2025. They empower organizations to move beyond static dashboards and deliver contextual intelligence directly within the workflows where decisions are made.

Choosing the right embedded analytics solution isn't just about features - it's about alignment. Businesses must consider scalability, user experience, data governance, and how well the tool fits into their existing tech ecosystem. Whether you're a SaaS provider looking to enrich your product with native analytics or an enterprise seeking to democratize data access across departments, the right tool can transform how your users interact with information.

Ultimately, embedded analytics is not just a technology trend - it's a philosophy of making data invisible yet omnipresent. The best tools in 2025 will be those that make insights feel intuitive, actionable, and indispensable. As you evaluate your options, prioritize tools that not only meet your current needs but also anticipate the future of how your users will consume and act on data.

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