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AI is shifting how users work with data. Teams need analytics that answer questions, explain results, and guide decisions inside the product. This is where AI-powered analytics improves the experience. It speeds up insight delivery and supports users who need clarity without extra steps. The real value comes when AI works within the product’s rules and keeps data in the customer environment. This removes risk and gives teams a safer way to add AI features. It also reduces backlog, improves adoption, and delivers clearer answers for every user who depends on the product.

Reveal 1.8.1 introduces two major upgrades: Conditional Formatting and the Redis Cache Provider. These updates make embedded analytics faster, clearer, and easier to scale. Conditional Formatting lets users apply rule-based color logic directly to charts, turning data into instant visual insight. The Redis Cache Provider delivers enterprise-level performance with distributed in-memory caching for real-time workloads. Together, these enhancements help developers and SaaS leaders build smarter, high-performing dashboards while keeping Reveal the standard for customizable and scalable embedded BI that delivers insight without complexity.

Integration is one of the most expensive and underestimated challenges in SaaS development. Poorly embedded analytics slows delivery, inflates maintenance costs, and weakens adoption across the product lifecycle. Most issues come from fragmented data models, outdated BI tools, and reactive fixes that create long-term debt. Solving integration early through unified architecture, SDK-based embedding, and native UX reduces cost, improves scalability, and turns analytics into a reliable, built-in product capability.

SaaS leaders face pressure to differentiate, grow revenue, and keep customers engaged. Product analytics offers a direct path to do all three. By embedding insights into their products, companies can create premium feature tiers, sell analytics as add-ons, and increase retention through daily reliance. Customers now expect self-service, branded, and intelligent dashboards as part of the experience. Meeting these expectations requires SDK-first integration, white-labeling, scalable pricing, and trusted connections to data. Platforms like Reveal enable product teams to embed analytics inside the product, turning it from a cost center into a revenue engine.

In SaaS, speed to launch determines market success. Yet analytics often becomes the slowest part of the roadmap. Customers expect dashboard analytics at launch but developing that in-house can put a drain on resources which often leads to significant delays Embedded analytics solves this by integrating reporting directly into the product, cutting development cycles and improving adoption. Beyond launch, it supports retention, monetization, and advanced capabilities like AI. With SDK-first integration, self-service dashboards, white-label control, and predictable pricing, Reveal helps SaaS leaders reduce time to market and deliver analytics that scale with their product.

Product leaders need analytics that scale with their app, not retrofitted BI tools. Looker offers strong visualizations and tight Google Cloud integration. But its use of LookML, iFrames, and user-based pricing makes it hard to embed in customer-facing products. 

As SaaS teams grow, these constraints slow development, increase costs, and limit flexibility. That’s why more teams are replacing Looker with Reveal—an embedded analytics platform built for speed, scale, and predictable pricing. 
This article breaks down where Looker fits, where it falls short, and why modern SaaS teams are moving on.

Legacy BI systems create technical debt, slow product delivery, and limit user experience. Modern embedded analytics delivers real-time, branded insights, scalable architecture, and predictable costs. This guide compares old and new approaches, outlines how to choose the right platform, and shows how Reveal’s SDK-based solution helps SaaS companies and ISVs modernize without disruption.

We compared five leading white label analytics platforms across branding, integration, performance, scalability, data connectivity, user capabilities, and advanced features. Each platform offers a different balance of customization, speed, deployment flexibility, and pricing. This guide helps SaaS companies and ISVs identify which solution best fits their product requirements, customer expectations, and long-term growth plans.

FinTech products must win on trust, speed, and compliance. Yet many still struggle to deliver the insights customers expect. Customers expect secure, real-time visibility into their data. Yet too often, dashboards sit in external portals, reports take days, and compliance risk grows with every integration. These gaps limit growth, making embedded analytics in FinTech essential […]

Security with embedded analytics gets more complex when AI enters the picture. This article breaks down the key risks, offers best practices to prevent data leaks, and explains how Reveal gives SaaS teams full control over AI endpoints, data flow, and governance. If you’re embedding AI-powered analytics into your product, Reveal helps you do it securely by design.