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Introducing custom visualizations, interactive chart filtering and a host of other enhancements and bug fixes that help us provide you with the best embedded analytics solution you deserve.

Today we are excited to deliver 15 new features & product enhancements to the Reveal visualization editor, API, data sources, and docs.

Get an idea of what our plans look like, feature-wise, for 2023. Everything we add is based on customer feedback and demand. While we may add items that we believe make us competitive in the market or features that are based on the general market direction or analyst feedback, we are constantly adjusting and adapting to what you need to deliver successful software.

The fastest way to monetize your data is by embedding white-labeled dashboards directly into your product. While the opportunity is clear, the execution isn’t always easy. Building in-house drains time, money, and dev resources, and choosing the wrong partner can lead to the same bottlenecks that stall monetization efforts.

Tableau Embedded is often used to extend internal dashboards into external apps, but its architecture poses challenges for customer-facing products. iFrames limit UI control, pricing scales with usage, and customization is constrained. As expectations shift, many CTOs and SaaS leaders are prioritizing embed-first platforms with developer control, white label flexibility, and built-in AI for product environments.

The best way to deliver insights in your SaaS product is to embed them directly where users work. No switching tools. No report delays. Building analytics in-house burns time and dev resources. Reveal is purpose-built embedded analytics for SaaS platforms, with a true SDK, full white label control, and fixed pricing that scales. You get in-app self-service analytics without slowing down your roadmap.

Find out what are the pros and cons of the Sisense embedded analytics platform and how it matches Reveal’s self-service embedded analytics solution.  

White label analytics allows SaaS products to embed dashboards and insights under their own brand, fully integrated into the application. Users interact with data inside the same interface, which improves adoption and keeps workflows uninterrupted. The key difference from basic embedding lies in integration depth. iFrame-based approaches limit customization and create disconnected experiences, while SDK and API-based platforms enable deeper control, better performance, and scalability across tenants. For SaaS teams, this affects retention, monetization, and development speed, turning analytics into a core product capability rather than an external add-on.

In the embedded analytics space, however, you’ll be hard-pressed to find clear, transparent, and publicly available pricing. Most embedded analytics vendors keep their pricing a secret and charge you unpredictable costs like usage and users.

Choosing the wrong embedded analytics platform slows your roadmap, increases dev burden, and weakens the product experience. Many tools check feature boxes but fail on pricing models, embedding control, integration fit, and long-term scale.