5 Embedded Business Intelligence Tools That'll Actually Make Your SaaS Product Shine (2025 Guide)

Look, we need to talk about embedded business intelligence tools.

If you're building a SaaS product in 2025 and not offering some form of analytics to your users, you're basically showing up to a knife fight with a pool noodle. Your competitors are embedding gorgeous dashboards, real-time insights, and AI-powered predictions right into their interfaces—and your customers are noticing.

But here's the thing: you don't need to spend six months and half your engineering budget building analytics from scratch. Embedded BI integrates powerful data visualization and reporting directly into your existing applications.

The right embedded business intelligence tool can get you from "we should probably add analytics" to "holy crap, our users love this feature" in a matter of weeks, not months.

I've spent the last few months diving deep into the embedded BI landscape, and I'm not going to bore you with a list of 15+ tools where half of them are basically the same thing. Instead, I'm giving you five solid options that actually solve real problems—including some you probably haven't heard of yet (and that's exactly why they're worth your attention).

Before we dive into the tools, let's get everyone on the same page.

Embedded Business Intelligence (BI) is the seamless integration of analytics and reporting capabilities directly into business applications, software, or websites.

Think of it like this: instead of your users having to export their data to Excel or log into some separate analytics platform, they get insights right where they're already working.

Instead of using separate BI tools, users can access insights, dashboards, and reports within the platforms they already use—eliminating the need to switch between multiple tools.

Pretty simple concept, right? But the execution? That's where things get interesting.

Traditional business intelligence is almost a privilege for data scientists and people with technical knowledge. Traditional BI software is complex to learn if you don't know data science or coding. It takes a long time to create reports.

Meanwhile, your average user just wants to answer questions like "Which customers are most likely to churn?" or "What's our revenue trend looking like?" without needing a PhD in data science.

That's the embedded BI difference. Analytics become democratized. Everyone gets insights, not just the folks who know SQL.

Before I reveal the five tools that made my list, here's what you should actually care about when evaluating embedded business intelligence solutions:

A top-tier embedded BI tool should connect easily with your data sources, applications, and third-party tools. This ensures that data flows smoothly between systems and is always up-to-date. Look for BI solutions that offer APIs, SDKs, and support for cloud platforms like AWS, Azure, or GCP, which can simplify the integration process and reduce time to deployment.

If a tool can't talk to your existing tech stack, it's basically useless. Don't compromise here.

Your brand took years to build. Why would you slap some generic-looking dashboard into your product that screams "third-party solution"?

No two businesses are alike, and your BI solution should be flexible enough to meet your specific needs. Whether it's the design of dashboards, the types of reports, or the way data is displayed, customization options allow you to tailor the solution to your organization's workflow.

If you're building for multiple clients, you need rock-solid data isolation. Period. Look for platforms that were designed for multi-tenant environments from day one—not ones that bolted it on as an afterthought.

Nobody wants yesterday's insights for today's decisions. Make sure whatever tool you choose can handle real-time (or near real-time) data processing without melting down.

Alright, let's get to the good stuff. These five tools represent different approaches to embedded analytics, and each has its own sweet spot.

Reveal is built specifically for embedded analytics. It's not a repurposed BI tool. With an SDK-first approach, it gives teams full control to integrate analytics directly into their product without the limitations of iFrames, external tools, or unpredictable pricing.

If you're the type who wants to control every pixel of your analytics experience, Reveal BI is your jam.

Native SDK Instead of iFrames: With a native SDK instead of iFrames, you get full control over how analytics are rendered and interacted with. This makes it the ideal embedded analytics solution for companies offering customer-facing analytics.

This is huge. iFrames are basically the web development equivalent of duct tape—they work, but they're clunky, have security limitations, and feel bolted-on. Reveal's SDK approach means your analytics feel like a natural part of your product.

Self-Hosted Flexibility: Reveal BI, owned by Infragistics, focuses on self-hosted embedded analytics with SDK-based customization. Their platform gives you full control over deployment and data security.

If your industry has strict compliance requirements (hello, healthcare and finance folks), this level of control is invaluable.

Learning Curve: With great power comes great responsibility (thanks, Spider-Man). The SDK-first approach means you'll need developers who are comfortable getting their hands dirty with code.

Setup Time: Requires significant technical expertise for setup and maintenance, so if you need something live tomorrow, this might not be your best bet.

Teams with strong engineering resources who want complete control over their analytics experience and can't compromise on customization or security.

Fixed pricing based on deployment requirements.

You'll need to contact their sales team for specifics.

GoodData is the AI-native analytics platform built for speed, scale, and trust.

While not as well-known as Tableau or Power BI, GoodData has been quietly building one of the most robust embedded analytics platforms out there.

Flexible Embedding Options: You can either add GoodData dashboards to your website using iframes or use GoodData.UI library - which is a Typescript framework best for building analytical web applications on top of GoodData Cloud and GoodData Platform, offering Web components, React components, and Rest API clients.

This flexibility is chef's kiss. Whether you want the quick-and-dirty iframe approach or you're ready to build something more sophisticated with their UI library, GoodData's got you covered.

Enterprise-Grade Security: Row-level security, multi-tenant support, and SOC 2 compliance, ensuring robust data governance for enterprises.

Handles Large Datasets: Reviewers like the tool's robust visualization capabilities, scalability, and its ability to efficiently handle large data sets, as well as its customizable user interface and integration capabilities with various data sources.

Steep Learning Curve: Reviewers noted that the platform can be challenging for beginners due to its numerous functions. This isn't a "set it and forget it" solution—you'll need time to learn the platform properly.

Manual Data Updates: Some users report that the platform requires manual data reloading or updating, which can be a pain if you're expecting everything to be automatic.

Mid-size to enterprise companies that need to handle large amounts of data across multiple customers and can invest time in learning a sophisticated platform.

Custom pricing based on your requirements. GoodData doesn't publish prices publicly, so you'll need to talk to their sales team.

Luzmo targets fast-moving SaaS teams with lightweight embedded analytics. It is optimized for speed and ease of use but comes with tradeoffs in scale, flexibility, and enterprise readiness.

If your mantra is "ship fast and iterate," Luzmo might be your new best friend.

JavaScript SDK Embedding: JavaScript SDK-based embedding. Dashboards and components can be embedded directly without iFrames. Developers control placement and interaction, but functionality is limited to what the SDK exposes.

User-Friendly Interface: Specifically built for intuitive embedding into software and web apps, Luzmo helps product teams deploy amazing analytics experiences in record time. Their suite of tools helps you build bespoke data products, just the way you want: whether it's with zero coding or with deep customization through code - you do it your way.

Great Support: At Luzmo, you're not alone. We offer a guided onboarding and trainings to help your team launch meaningful client-facing analytics.

Pricing Gets Expensive: Pricing becomes expensive for larger SaaS deployments, so if you're planning to scale to thousands of users, budget accordingly.

Limited Enterprise Features: Limited multi-tenant security features compared to enterprise solutions

means it might not be the best fit if you're dealing with highly sensitive data or complex permission requirements.

Performance Issues with Complex Data: Performance issues can occur with complex datasets—something to test thoroughly if your analytics involve heavy data processing.

Early-stage to mid-size SaaS companies that prioritize speed-to-market and want an intuitive platform that won't require months of engineering time.

Starting at $3,100+ for unlimited white-label embedded dashboards. This model provides extensive embedding capabilities but may require consideration of the cost relative to your needs.

Qrvey delivers a complete multi-tenant analytics solution built specifically for SaaS companies. The platform combines a native data lake, semantic layer, and embedded BI components that scale with your business.

If you're already invested in the AWS ecosystem, Qrvey deserves serious consideration.

Full-Stack Approach: Qrvey goes beyond traditional business intelligence by offering a full-stack approach. You get data management, visualization, and workflow automation in one platform.

This is huge because most embedded BI tools only handle the visualization layer. Qrvey handles everything from data ingestion to the final dashboard.

Native Data Lake: Native Data Lake: Elasticsearch-powered infrastructure handles complex datasets without performance degradation. If performance is critical (and when isn't it?), this architecture makes a real difference.

Built for Multi-Tenancy: The multi-tenant SaaS architecture ensures each customer sees only their data while maintaining enterprise-grade security.

White-Label Freedom: White-Label Analytics: Complete customization freedom with iframe-free embedding—your analytics, your brand, no compromises.

AWS Lock-In: Qrvey is purpose-built for embedded analytics in AWS environments. It provides full stack capabilities, deep customization, and fixed pricing—provided you are fully committed to AWS.

If you're on Azure, GCP, or want to keep your options open, this could be a dealbreaker.

SaaS companies running on AWS who want an end-to-end analytics solution and are comfortable committing to the AWS ecosystem.

Fixed pricing model (refreshing, right?). Contact Qrvey for specific numbers based on your usage.

Sigma caters equally to spreadsheet lovers and SQL pros, carving a niche in the business intelligence arena. Sigma empowers teams to explore data and make decisions quickly and efficiently.

If your users live in Excel but you need them to level up to real BI, Sigma is the bridge you've been looking for.

Familiar Spreadsheet Interface: The familiar spreadsheet metaphor makes data exploration intuitive for users already comfortable with Excel or Google Sheets. Snowflake integration provides powerful cloud data warehouse capabilities.

This is massive for user adoption. The number one reason BI tools fail? Users don't adopt them because the learning curve is too steep. Sigma solves this by making analytics feel like the spreadsheets people already know and love.

Embedded Analytics: A great feature of Sigma is its embedded analytics, which seamlessly integrates powerful analytics into customer-facing products. This integration enhances the product's value and provides customers with easy, self-serve access to data within the application, elevating the overall user experience.

Powerful Yet Approachable: You get SQL-level power without requiring your users to actually write SQL.

Snowflake Dependency: Sigma works best with Snowflake. If you're not on Snowflake and don't plan to be, this might limit your options.

No Native Data Management: No native data management – all data preparation handled externally, which means you'll need other tools in your stack for ETL and data prep.

Expensive for Small Teams: Base platform fee starts at $30k annually, with $1,000 annual user fees for dashboard creation and limited viewer licenses.

This pricing puts Sigma out of reach for early-stage startups.

Mid-market to enterprise companies with non-technical users who need powerful analytics without the SQL headaches, especially if you're using Snowflake.

Starting around $30K annually for the base platform, plus per-user fees. Definitely enterprise pricing.

Now that you've seen the five tools, let's talk about what features actually matter when you're making your decision.

Besides interactive embedded analytics, embedded business intelligence also lets users even create and save their own interactive reports and dashboards with simple drag and drop.

Your users should think these dashboards were built by you, not some third-party tool. Look for complete customization—colors, logos, fonts, the whole nine yards.

Software developers can use embedded business intelligence tools to quickly incorporate self-service analytics capabilities into business applications.

Let your users create their own reports and explore data without bugging your team every time they have a question.

Within a software context, embedded BI allows you to scale BI to thousands of users. Build a dashboard once, and show every user only the data they are allowed to see. Scalability is as easy as a few clicks.

This is critical for SaaS applications. Each customer should only see their data, and the system should handle this automatically.

Get notified when there are important changes or outliers in your datasets. Alerts heavily reduce the time to respond to incidents or opportunities.

Proactive insights beat reactive reporting every single time.

Embedded BI is versatile for the global business user, always on the go. Dashboards adapt to the right language, timezone, currency, and device.

If your dashboards look like garbage on mobile, you've failed. Full stop.

Even with the best tools, embedding analytics properly takes time. Don't tell your boss it'll be done in two weeks when it'll realistically take two months.

Embedded analytics tools are pivotal in the realm of data-driven decision-making. They offer organizations a seamless way to integrate data analysis directly into their existing applications and workflows. These tools empower users to access, analyze, and visualize data within the context of their daily operations—without needing to switch to an external analytics platform. As a result, businesses can harness the power of data more effectively, driving better insights and informed decisions.

The whole point of embedded BI is to make analytics easier for users. If you build something that's technically impressive but nobody uses, you've wasted your time.

The cheapest option usually isn't the cheapest in the long run. Factor in implementation time, ongoing maintenance, and the opportunity cost of shipping features late.

Your embedded BI solution needs to grow with you. What works for 50 users might completely fall apart at 5,000. Ask hard questions about performance and scalability before you commit.

Product and engineering teams are still hesitant to adopt embedded business intelligence software. Engineers often prefer to stitch their own solution together instead. Even though low-code software can save them months of time.

Look, I get it. You've got talented engineers who could build this. But should they?

The product teams who build instead of buy analytics often delay their roadmap. You need a specific skill set to build business intelligence and big data features. If your team lacks the expertise, you are draining your resources for months to come without realizing it. For this reason, product teams often postpone or halt analytics development cycles.

Unless analytics is your product, buy a solution and let your engineers focus on your actual differentiators.

Here's the truth: there's no single "best" embedded business intelligence tool.

Reveal BI is perfect if you want maximum control and have the engineering chops to handle it. GoodData scales beautifully for enterprise use cases. Luzmo gets you to market fast. Qrvey is ideal for AWS-native shops. Sigma bridges the gap for spreadsheet-loving users.

The "best" tool is the one that fits your specific situation—your tech stack, your team's skills, your budget, and your timeline.

Here's my advice: pick two or three from this list that seem like good fits, get demos, and actually test them with your real data and real use cases. Don't just watch the polished sales demo—get your hands dirty.

Embedded analytics tools have grown significantly in recent years, with industry reports reflecting their increasing adoption across various sectors. Organizations today recognize the value of embedding analytics capabilities into their software applications; it not only enhances the user experience but also improves productivity and competitiveness.

Your users expect analytics. Your competitors are already offering it. The only question is: which tool will you use to make it happen?

Choose wisely. Your product roadmap—and your customers—will thank you.