Sisense blog: AI, analytics, and the future of insights

By Yael Lev and Maria Ciampa October 6, 2026

The semantic harness: How leaders govern AI in production

Product and engineering teams are under pressure to put AI into the products they build. But there’s a framing problem hiding in most AI analytics strategies: everyone is competing on the wrong 10%. The model, which is the LLM itself,…

generative ai for data analytics feature

By Sisense Team September 25, 2026

Generative AI for data analytics: Turning data into insights

AI advancements are making it easier for anyone to get trustworthy, actionable insights from their data. Generative AI for data analytics brings embedded analytics, grounded in governed data, directly into the applications where people already make decisions. From asking a…

By Maria Ciampa and Steve Lewis August 14, 2026

Sisense product roundup: MCP, AI-powered search, and smarter modeling in 2026.3

With the 2026.3 release, Sisense continues to advance AI-powered analytics across the full builder workflow. This release introduces MCP Server (beta), bringing governed data access to external AI agents. This release also brings new tools to help your users find…

By Sisense Team June 17, 2026

What is a unified data analytics platform? The what, why, and how

A unified data analytics platform turns the traditional, disconnected business intelligence (BI) workflow on its head. Instead of switching between different tools, teams can access all their data in one place: seamless, consistent, and holistic. Unified data analytics platforms solve…

By Sisense Team June 16, 2026

Low-code vs. pro-code analytics: How to choose the right approach for embedded analytics

Embedded analytics are fast becoming an expectation, not an exception, in modern software products. Today’s customers expect data-rich, interactive experiences built directly in-platform. For software creators, this is a product strategy decision and a technical decision. The analytics experience you…

By Sisense Team June 11, 2026

Embedded analytics security: Best practices for software creators

As a SaaS product leader, you know that keeping end-users’ data secure is paramount. When you implement embedded analytics, security becomes an even more crucial—and complex—concern. Unlike with standalone BI tools, embedded analytics deliver data-driven insights directly inside customer-facing applications,…

By Sisense Team June 9, 2026

White label analytics: What they are and how they work

As analytics experiences become a standard expectation in modern software products, more creators are looking for ways to deliver customer-facing dashboards and reporting. The challenge: building a full analytics platform from scratch is a massive undertaking. The solution: white label…

By Sisense Team June 8, 2026

Embedded analytics requirements: What to consider before choosing a platform

Landing on the right embedded analytics platform for your organization is more than a feature decision. It’s a strategic product and infrastructure investment. The platform you choose impacts everything from end-user experience and developer workflows to foundational aspects of your…

By Sisense Team June 4, 2026

Embedded analytics for SaaS: A practical guide for product teams

Embedded analytics for SaaS has evolved from a nice-to-have feature into a core driver of product differentiation, customer retention, and expansion revenue. Today’s end-users expect insights to arise directly within the applications and workflows they already use—not in disconnected BI…

By Sisense Team June 2, 2026

Embedded analytics for multi-tenant architectures: A guide for SaaS teams

Most SaaS products are built on multi-tenant architecture. Most embedded analytics tools are not. That gap between how your product is built and how analytics platforms are designed is where implementation projects stall, security risks surface, and engineering resources get…

By Sisense Team June 2, 2026

AI-powered embedded analytics: A strategic guide for software creators

How we compile, analyze, and deliver data insights is changing quickly. Data has never been more available. But availability was never the hard part. Understanding it, and acting on it fast enough to matter, is where most products still fall…

By Sisense Team May 28, 2026

Embedded analytics features: Essential capabilities for modern applications

Today’s business world is driven by data. Unlocking value from that data hinges on making it immediate, accessible, and actionable. Embedded analytics directly integrate data—and, crucially, the insights they reveals—into the platforms and workflows people use every day. Robust embedded…

A man with a focused expression examines glowing digital graphs and data charts on a transparent screen, conveying a high-tech, analytical atmosphere.

By Maria Ciampa May 11, 2026

Generating revenue, not reports: How Clari redefines in-product analytics

Snapshot The challenge: Faced with a build vs. buy decision, Clari needed to evolve from static, siloed analytics to a scalable, embedded analytics platform that could deliver interactive, trustworthy insights directly within its product experience. The solution: Sisense provided a…

By Maria Ciampa and Prathith Venkatakrishnan April 29, 2026

Sisense product roundup: Smarter AI responses, data modeling flexibility, and embedded workflows in 2026.2

A simpler path to AI adoption, with Sisense-managed LLM and Sisense Credits Sisense-managed LLM was introduced earlier this year as a simpler way to run Sisense Intelligence on managed cloud. With this release, Sisense Managed LLM is paired with Sisense…

By Sisense Team April 27, 2026

The ultimate guide to comparing embedded analytics solutions

In this guide, we look at the most important capabilities organizations should evaluate when selecting an embedded analytics solution. By understanding how different platforms support AI-powered insights, developer-friendly integration, customization, and scalable data architectures, product and engineering teams can choose…

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