Reveal Embedded Analytics Review: Pricing, Features, Pros and Cons

Reveal is not trying to compete with Tableau or Power BI for the attention of your marketing team. It is an embedded analytics SDK built for development teams who want to ship dashboards, reporting, and AI-powered insights as native features inside their own software products. Built by Infragistics, a developer tools company with over three decades of history and more than two million developers using its products, Reveal occupies a focused niche in the analytics market and fills it convincingly.

The platform’s strongest selling point is its flat-rate annual pricing for embedded analytics, which means adding 10 users or 10,000 users does not change your bill. That pricing model, combined with SDK-first architecture and flexible deployment options (including fully self-hosted and air-gapped environments), makes it a compelling choice for SaaS companies and enterprise software builders. But the lack of publicly listed embedded pricing, some gaps in advanced analytics, and a cost structure that can be prohibitive for smaller organizations mean it is not right for every team.

What Is Reveal?

Reveal is an embedded analytics platform developed by Infragistics, a privately held software company headquartered in Cranbury Township, New Jersey. Infragistics was founded in 1989 and built its reputation on developer-focused UI toolkits and components. The company maintains global offices across the US, Europe, Japan, Southeast Asia, Australia/New Zealand, and India. Reveal launched in 2019 as Infragistics’ purpose-built entry into the embedded analytics market.

The core philosophy behind Reveal is “embed-first analytics.” Rather than taking a standalone BI tool and retrofitting it for embedding (the approach many competitors take), Reveal was designed from the ground up to be integrated into other software applications via native SDKs. There are no iFrames, no redirects to external dashboards, and no separate tool for end users to learn. Analytics render directly inside the host application’s DOM as a native part of the experience. Reveal also offers a standalone BI option with per-user pricing for individual use, but the embedded analytics SDK is the product’s primary focus and what we are reviewing here.

Reveal Key Features

SDK-Based Embedded Analytics

Reveal’s primary differentiator is its SDK-first architecture. On the server side, the platform supports .NET Core, Java, and Node.js. On the front end, there are SDKs for React, Angular, Blazor, Vue (as Web Components), jQuery, MVC, and Java Frameworks. For Windows desktop applications, WPF and WinForms SDKs are also available. The platform runs on all major cloud providers (AWS, Azure, GCP) and all server operating systems (Windows, Linux, macOS).

This is not an iFrame wrapper around an external dashboard. The SDK renders analytics directly within your application’s UI, giving developers pixel-level control over the look, behavior, and interaction model. Most competing embedded analytics products either rely on iFrame embedding (which limits customization and introduces security complications) or require significant custom development to achieve native-feeling integration. Reveal’s approach eliminates both problems. NuGet packages are actively maintained, with version 1.8.3 released in January 2026.

AI-Native Analytics

Reveal has moved aggressively into AI-powered analytics. The platform includes natural language Q&A (allowing end users to ask questions about their data in plain English), automatic KPI summaries, anomaly detection, and recommended actions. Conversational analytics let users interact with dashboards through dialogue rather than clicks and filters alone.

What sets this apart from competitors adding AI as an afterthought is the deployment model: Reveal’s AI features run inside your infrastructure using customer-controlled models. Reveal does not host, train on, or store your data. For organizations in regulated industries (healthcare, finance, government), this is a meaningful advantage over cloud-only AI analytics solutions. The AI features are disabled by default and enabled through configuration, giving development teams full control over the rollout.

Self-Service Dashboard Creation

End users get a drag-and-drop dashboard builder with ready-made templates, instant chart filters, dashboard linking, and one-click data blending. The interface supports 30+ chart types and visualization options. Calculated fields, statistical functions, and drill-down capabilities are available without writing code.

The self-service tools are designed so that non-technical users can create and modify dashboards without developer assistance. One notable finding is that organizations integrating Reveal have reported significant increases in time-on-app after deployment, with analytics becoming a stickiness driver rather than just a reporting feature. That said, the initial setup and configuration of the self-service environment still requires professional developers.

White-Label Capabilities

Full white-labeling is included in Reveal’s base subscription at no extra cost. This covers colors, fonts, logos, layout, custom menus, tooltips, and filters. Prebuilt themes are available for faster deployment, and the pixel-level UX control means the analytics can be styled to match any host application’s design system.

For SaaS companies, this is critical. Your customers should never know they are looking at a third-party analytics tool. Many competing embedded analytics platforms either charge extra for white-labeling or limit the degree of customization available. Reveal’s inclusion of full branding control in the base price is a genuine differentiator.

Multi-Tenant Security

Reveal takes a secure-by-default approach. The SDK lives within your application’s security context, so you do not need to modify your existing security model to accommodate it. Row-level security is implemented through custom queries. Role-based access is managed via APIs with JWT-based authentication. Audit logging and per-tenant usage caps are built in for SaaS applications serving multiple customer organizations.

Data source authentication supports username/password, tokens, and OAuth. Connection data is obfuscated and encoded. Reveal does not store your data or credentials, which is an important distinction from cloud-hosted analytics platforms that require data to flow through their servers.

Flexible Deployment Options

Reveal can be deployed in the cloud (any provider), in a private cloud, or fully self-hosted on your own infrastructure. The self-hosted option supports air-gapped environments with no external connections required, which is essential for defense, healthcare, and financial services organizations with strict data sovereignty requirements.

There is no dedicated server dependency. The platform runs wherever your application runs. This flexibility is rare among embedded analytics tools, many of which are cloud-only or require a dedicated analytics server that adds complexity and cost to the deployment.

Data Connectivity

Reveal supports 25+ native data connectors covering major databases (SQL Server, PostgreSQL, MySQL, Oracle), cloud data warehouses (Snowflake, BigQuery, Redshift), business applications (Salesforce, HubSpot, QuickBooks, Microsoft Dynamics CRM), cloud storage (Google Drive, OneDrive, Dropbox, SharePoint), web analytics (Google Analytics), and REST APIs for custom integrations.

Data blending from multiple sources is supported natively within the dashboard builder. One limitation worth noting: there is no current support for modern lakehouse formats like Apache Iceberg or Delta Lake tables. Organizations using these newer data architectures will need to access their data through other means or wait for future connector updates.

Predictive Analytics and Forecasting

The platform includes built-in machine learning models, statistical functions, and time-series forecasting accessible directly from the dashboard builder. Users can add predictive overlays to visualizations with a few clicks rather than writing code or integrating a separate ML toolkit.

However, these capabilities are oriented toward business-level forecasting and trend analysis rather than advanced data science workloads. Organizations needing sophisticated statistical modeling, custom algorithm development, or deep predictive analytics will find Reveal’s built-in tools insufficient compared to dedicated BI platforms like Tableau or specialized data science environments.

Reveal Pricing and Plans

Reveal uses a dual pricing model depending on how you plan to use the product. The embedded analytics offering and the standalone individual BI product are priced entirely differently.

For the embedded analytics offering (the focus of this review), Reveal does not publish pricing on its website. You must fill out a form and speak with sales. Third-party sources confirm that pricing varies widely depending on the scope of the project. The vendor’s own blog emphasizes that the model is a “single, all-you-can-eat price” with no user tiers, no token spikes, and no unpredictable invoices.

The flat-rate model is Reveal’s strongest pricing advantage. Competing products like Power BI Embedded use capacity-based pricing (starting around $735/month for A1 capacity), while platforms like ThoughtSpot charge per-user ($50/user/month), and enterprise solutions like Sisense and Looker often require custom quotes in the mid-six figures. Reveal’s model means your cost stays the same whether your application serves 100 users or 100,000, which is extremely attractive for high-growth SaaS products.

The downside is transparency. Without public pricing, it is impossible to evaluate whether Reveal fits your budget before engaging with sales. Feedback on cost is mixed: some organizations report that Reveal replaced multiple tools and cut their analytics spending in half, while others (particularly smaller companies and early-stage startups) describe the embedded pricing as prohibitively expensive. The standalone individual product offers a free trial with no credit card required, which is useful for evaluating the dashboard builder and visualization capabilities before committing to the embedded SDK.

Integrations

Reveal’s integration model is SDK-centric rather than app-marketplace-centric. Because the product lives inside your application’s codebase, integration primarily happens through the server and client SDKs rather than through a traditional connector marketplace.

Native data connectors cover the major categories: relational databases (SQL Server, PostgreSQL, MySQL, Oracle), cloud warehouses (Snowflake, BigQuery, Redshift), CRM and business apps (Salesforce, HubSpot, QuickBooks, Microsoft Dynamics CRM), cloud storage and productivity (Google Drive, OneDrive, Dropbox, SharePoint, Google Analytics), and reporting systems (SSRS, Microsoft Dynamics AX). REST API support enables connections to any system with an API.

There is no traditional app marketplace or Zapier/Make integration, which is expected given Reveal’s developer-oriented nature. Developers integrate data sources programmatically through the SDK, which provides more control but also means every new data connection requires development work. For teams accustomed to plug-and-play connector marketplaces found in standalone BI tools, this is a tradeoff worth understanding upfront.

The platform supports cross-platform deployment with SDKs that work across web, Windows, iOS, and Android, making it possible to embed analytics consistently across different application surfaces. However, some niche data source integrations are absent, and support for modern lakehouse formats (Iceberg, Delta Lake) is not yet available.

Customer Support

Reveal’s support is provided through Infragistics’ Priority Support infrastructure. The published support terms include 24/5 worldwide availability with a guaranteed one-business-day response time. Support channels include phone, live chat, email, and community forums. A developer Discord channel provides an informal support and community interaction option.

Help documentation is hosted at help.revealbi.io, covering SDK integration guides, API references, and dashboard configuration. The documentation is maintained and kept current, though it is primarily available in English only, which is a notable gap for a product that supports 13+ end-user languages.

Support quality is one of Reveal’s most consistently praised attributes. The implementation assistance goes beyond typical ticket-based support; the team is described as hands-on, helping development teams through initial integration and deployment challenges. For a product that requires developer involvement to set up, this level of support quality matters more than it would for a plug-and-play SaaS tool.

One area where support could improve: there is no mention of dedicated customer success managers, tiered support plans, or premium support options with faster SLAs. For enterprise customers with mission-critical embedded analytics deployments, the one-business-day response guarantee may not be fast enough during outage scenarios. It is worth confirming support SLA details during the sales process.

Pros and Cons

Based on our analysis of the platform’s capabilities, pricing model, deployment flexibility, and real-world performance feedback, here is where Reveal stands out and where it falls short.

Who Should Use Reveal?

Reveal is best suited for SaaS companies and enterprise software teams that want to add analytics as a core feature of their product. If you have a development team (at minimum, professional-level .NET, Java, or Node.js developers), you are building or maintaining a multi-tenant application, and you need dashboards and reporting to feel like a native part of your product, Reveal is a strong fit.

The ideal customer profile is a software company with a growing user base where per-user analytics pricing would become unsustainable. Companies in regulated industries (finance, healthcare, insurance, government) benefit particularly from the self-hosted and air-gapped deployment options and the fact that Reveal never touches your data.

Teams of 10 to 200 developers at mid-size to large software companies represent the sweet spot. Startups with small engineering teams can technically implement Reveal, but the upfront cost of the embedded license may be hard to justify before reaching meaningful revenue. Companies with fewer than five developers or no dedicated front-end resources will struggle with the integration work required.

Reveal is not the right choice if you need a standalone BI tool for internal business users (look at Power BI, Tableau, or Looker instead), if you need advanced statistical modeling or data science capabilities, or if your team lacks the development resources to implement and maintain an SDK-based integration. It is also not ideal if you need built-in alerting, auto-scheduled report delivery, or macOS desktop application support, as these features are currently absent.

Reveal Alternatives

Power BI Embedded

Microsoft’s embedded analytics offering is the most common alternative, especially for organizations already in the Microsoft ecosystem. Power BI Embedded offers a deeper set of visualization types and stronger advanced analytics capabilities. However, it uses capacity-based pricing (starting around $735/month for A1 capacity) that can become expensive and unpredictable as usage grows. The integration model relies more heavily on iFrames and Azure infrastructure, giving developers less control over the embedded UX compared to Reveal’s native SDK approach. Choose Power BI Embedded if you are already heavily invested in Azure and need the broadest possible visualization library.

Sisense

Sisense is an enterprise-grade embedded analytics platform with more advanced data modeling capabilities and a broader connector ecosystem than Reveal. It handles complex data architectures well and supports larger-scale enterprise deployments. The tradeoff is cost and complexity: Sisense typically requires custom quotes in the mid-six figures range, and implementation timelines are longer. Choose Sisense if you have a large enterprise budget, complex data requirements, and need a more mature enterprise analytics platform.

Embeddable

Embeddable is a newer entrant that uses a fixed annual pricing model similar to Reveal’s. It positions itself as a developer-friendly embedded analytics tool with a focus on speed of integration and modern web frameworks. It lacks the depth of Reveal’s AI features and the breadth of deployment options (no self-hosted or air-gapped support at the same level). Choose Embeddable if you are a smaller team looking for a simpler, potentially more affordable embedded analytics SDK without the enterprise security requirements.

Qrvey

Qrvey offers flat-fee annual pricing and is built for AWS environments specifically. It includes embedded analytics, data collection, and automation capabilities in a single platform. It is more AWS-centric than Reveal, which is cloud-agnostic. Choose Qrvey if your entire infrastructure runs on AWS and you want analytics combined with data collection and workflow automation in one tool.

Holistics

Holistics is a more affordable embedded analytics option at approximately $800/month flat, making it accessible to smaller companies that find Reveal’s pricing prohibitive. It focuses on SQL-based analytics and is particularly strong for teams with data engineering expertise. It offers less front-end customization and fewer AI features than Reveal. Choose Holistics if you have a strong SQL-oriented team and need embedded analytics at a lower price point.

Frequently Asked Questions

Does Reveal offer a free trial?

Yes. Reveal offers a free trial of its standalone BI product with no credit card required. For the embedded analytics SDK, you can request a demo through the vendor’s website. The standalone trial lets you evaluate the dashboard builder, visualization engine, and data connectivity before committing to the embedded offering.

Does Reveal charge per user for embedded analytics?

No. The embedded analytics offering uses a fixed annual license with flat-rate pricing. You can add unlimited end users without any per-user fees, token spikes, or usage-based charges. This is one of Reveal’s primary differentiators in a market where many competitors use per-user or consumption-based pricing that scales with your user count.

Can Reveal be deployed on-premises or in air-gapped environments?

Yes. Reveal supports cloud deployment (AWS, Azure, GCP), private cloud deployment, and fully self-hosted deployment including air-gapped environments with no external connections. The platform runs on Windows, Linux, and macOS server operating systems. This flexibility makes it suitable for regulated industries with strict data sovereignty requirements.

What programming languages and frameworks does Reveal support?

Reveal provides server SDKs for .NET Core, Java, and Node.js. Front-end SDKs are available for React, Angular, Blazor, Vue (as Web Components), jQuery, MVC, and Java Frameworks. Windows desktop SDKs for WPF and WinForms are also available. The platform works across web, Windows, iOS, and Android application surfaces.

Does Reveal store my data?

No. Reveal’s SDK runs within your application’s infrastructure and security context. Reveal does not store your data, credentials, or connection information. Data source authentication supports username/password, tokens, and OAuth, with connection data obfuscated and encoded. For AI features, models run inside your infrastructure using your own configurations.

How does Reveal handle multi-tenant security?

Reveal includes row-level security (via custom queries), role-based access (via JWT-authenticated APIs), audit logging, and per-tenant usage caps. The SDK integrates with your application’s existing security model rather than requiring a separate authentication layer. These features are built into the platform for SaaS applications serving multiple customer organizations.

What data sources does Reveal connect to?

Reveal supports 25+ native data connectors including SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, BigQuery, Redshift, Salesforce, HubSpot, QuickBooks, Microsoft Dynamics CRM, Google Analytics, Google Drive, OneDrive, Dropbox, SharePoint, and REST APIs. Data blending from multiple sources is supported natively. Modern lakehouse formats like Apache Iceberg and Delta Lake are not yet supported.

The Bottom Line

Reveal is a well-executed embedded analytics platform that does one thing and does it well: letting software companies ship native-feeling analytics inside their own products without the complexity of building from scratch or the UX compromises of iFrame-based embedding. The SDK-first architecture, flat-rate pricing model, and flexible deployment options (including fully self-hosted and air-gapped) combine to create a product that is genuinely differentiated in its category.

The platform earns our strongest recommendation for mid-size to large SaaS companies and enterprise software builders with professional development teams who need predictable analytics costs as their user base scales. The AI-native features, multi-tenant security, and white-labeling included in the base price make it a complete package for this specific audience. We rate it 4.0 out of 5.0 overall, with the deductions coming from the lack of pricing transparency, gaps in advanced analytics and alerting capabilities, and a cost structure that can exclude smaller teams.

If you are a startup with a small budget and a lean engineering team, look at Holistics or Embeddable as more accessible starting points. If you need a standalone BI tool for internal business intelligence, Reveal is not your product; consider Power BI or Looker instead. But if you are building software that needs embedded analytics, and you want a flat-rate SDK that your developers will genuinely enjoy working with, Reveal belongs on your shortlist.