Embedding analytics directly into user workflows gives users the right insight at the right moment, so they are always making smarter, data-backed decisions.
If you expect team members to switch context and open up a dedicated business analytics app every time they have a question about their data, then you’re in for disappointment. Building a culture of data-driven decision making requires reducing friction, which calls for embedding accessible yet rich analysis experiences within the apps that they’re already using.
For that reason, many organizations are adopting embedded analytics as a competitive advantage, birthing a new generation of analytics software solutions that differentiate by offering advanced embeddable insights. According to IMARC Group, the embedded analytics market was valued at $69.60 billion in 2024 and is projected to reach USD 182.72 billion by 2033.
Traditionally, embedding business intelligence into a host app relied on simple iframe integrations, while more complex SDK and component-based embeds gave developers the flexibility to build more customized analytics experiences.
Now, with AI and natural language querying, analytics can be embedded as a conversational interface that everyone, including non-technical users can enjoy, which further reduces user experience friction, but also adds more layers of complexity in terms of security and access governance.
With many options available, it’s no longer about who offers analytics, but how they are doing it and the value they add with differentiation features. Choosing the right solution means balancing strategic fit (what your users need) and technical fit (how easily the solution integrates with your host app’s infrastructure and existing tech stack).
This article breaks down six of the top embedded analytics platforms to consider in 2025.
1. Sisense
Sisense is a modern BI and analytics platform built around the idea of “invisible analytics,” meaning that it embeds insights directly into apps and workflows without disrupting the user experience. It’s a great choice for teams that want analytics to feel like a native part of their product, not an added-on dashboard.
Sisense offers a developer-first SDK called Compose SDK, which enables embedding via JavaScript components instead of relying on rigid iframes. This gives developers full control over the look, feel, and behavior of the analytics layer.
With a modular and AI-enhanced architecture, teams can deliver analytics where and how users need them. Features like natural language querying and collaborative dashboards support both technical and non-technical users.
Sisense is Ideal for product teams that want full design control and flexibility, but it does require development resources to set up, so it might not be the best fit for no-code teams or situations that call for rapid prototyping. WIth that said, their customer support and detailed documentation help smooth out the onboarding process and make implementation easy for even smaller dev teams.
2. Pyramid Analytics
Pyramid Analytics is a powerful decision intelligence platform that goes beyond traditional dashboards. Pyramid combines data prep, business logic, and machine learning in a single tool, making it a true all-in-one solution for enterprise analytics.
On the embedding side, Pyramid supports multi-tenant analytics through robust APIs and developer tools for Angular and React, allowing companies to serve multiple clients or user groups within a single platform. Everything from the UI styling to the voice-enabled query interfaces can be fully customized and styled to fit the product’s environment.
Pyramid’s standout feature is GenBI, a natural language AI assistant that can interpret even vague or high-level business questions and convert them into meaningful insights. Additionally, for organizations that place a high emphasis on privacy, or those in tightly regulated industries, Pyramid comes with a secure abstraction layer that prevents LLMs from querying databases directly, on top of other governance features like role-based access control (RBAC) and detailed logging.
With its deep feature set and AI capabilities, Pyramid is ideal for enterprises that require governed, scalable, and secure embedded analytics. However, their full-scope approach may be more than what smaller organizations need.
3. Looker (Google Cloud)
Looker is Google Cloud’s analytics solution. It’s known for its semantic modeling layer powered by LookML (Looker Modeling Language), a powerful, SQL-based language that allows data teams to define reusable business logic, metrics, and data relationships in one place.
Looker supports embedding via APIs, allowing developers to integrate reusable dashboards and visualizations powered by LookML-defined logic. It also integrates seamlessly with other Google Cloud services like BigQuery, Google Sheets, and Vertex AI, for streamlined data workflows across the entire GCP ecosystem.
In 2025, Google added Gemini, its powerful large language model, into Looker. This move puts Looker on par with other tools that support natural language queries and opens the door for faster insights and greater accessibility.
Looker is a natural choice for organizations that are deeply invested in Google Cloud and want to take full advantage of its strong data ecosystem with centralized data modeling. Still, teams should be prepared for the learning curve that comes with LookML, and UI customization is more limited compared to platforms that offer SDKs or low-level component control.
4. Vizzly
Vizzly (now part of Gain Theory) is a lightweight, developer-friendly embedded analytics tool built with startups and lean product teams in mind. It focuses on helping teams add analytics to their product quickly, without the complexity or cost of enterprise solutions.
Vizzly embeds dashboards via React or HTML components (no iframes involved) and gives developers full control over layout, styling, and interactivity. It supports both cloud-hosted and self-hosted deployments, so users can choose the setup that best fits their privacy, infrastructure, and compliance needs.
Designed for speed and simplicity, Vizzly supports most common data sources (like PostgreSQL, MySQL, Snowflake, and BigQuery) and prioritizes a fast path to production. Its affordable and usage-based pricing model also makes it especially appealing for early-stage SaaS platforms that want embedded analytics as a feature, not a full BI overhaul.
Since it’s a newer tool, Vizzly currently lacks certifications like SOC 2 or HIPAA, which may be an issue for teams with stricter security requirements. There is also limited support for more advanced features and AI capabilities you would find in larger platforms, and given the news of the company’s acquisition, the future of the product is uncertain.
5. Power BI Embedded
Power BI Embedded is Microsoft’s analytics embedding product, tightly integrated with Azure, Office 365, and the broader Microsoft ecosystem. It is a component of the well-known Power BI platform that is widely used by enterprises across industries.
Embedding is managed through token-based authentication to securely integrate Power BI reports and dashboards into applications or portals. Users have full control over role-based access, visualization settings, and real-time data connections.
It’s a mature, well-documented platform with consistent performance and frequent updates. Integration with Azure Active Directory and Office 365 streamlines authentication and identity management. Teams already relying on other Microsoft services will find it especially easy to adopt and scale.
While it’s certainly reliable, Power BI Embedded offers a more traditional UI compared to newer, design-flexible platforms. It also tends to lock you into Microsoft’s stack, and deeper customization can be challenging without additional development resources.
6. Luzmo
Luzmo (formerly Cumul.io) is a low-code embedded analytics platform designed for SaaS teams that want to offer customer-facing dashboards without building a BI tool from scratch.
Dashboards are embedded using web components that render directly in the DOM (Document Object Model), which works smoothly with modern front-end frameworks. Luzmo supports API-based data integration rather than direct database querying, so it’s a good fit for platforms that already expose their data through RESTful endpoints.
One of Luzmo’s key differentiating features its drag-and-drop interface, meaning that even non-technical users can utilize it to create their own dashboards. Like many of the tools in this list, Luzmo also recently added an AI chatbot for full natural language query support.
Luzmo is a solid choice for teams with customer-facing use cases that want a fast, user-friendly solution built around APIs. But it does come with some trade-offs, including limited visualization customization, a higher cost for white-labeling, and cloud-only deployment.
Final Thoughts
Embedded analytics has evolved from a niche feature into a strategic competitive advantage that is slowly becoming mainstream as more companies realize the value of delivering insights directly within their platforms.
Each solution on this list stands out because it serves a specific type of user and use case. Some are built for fast-moving startups, others for enterprise-scale governance, and some to strike a balance between the two.
Choosing the best solution for you comes down to understanding your strategic goals and technical requirements. The best embedded analytics platform for your business isn’t necessarily the most powerful, but the one that fits your product and your people.
Founder Dinis Guarda
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