Embedded analytics has long been a critical feature for delivering insights within applications, empowering users to make data-driven decisions without leaving their workflow. Now, Generative AI is reshaping expectations, enabling users to interact with data in more intuitive and conversational ways. The lines between analytics and AI are blurring, creating a new frontier for product leaders: Should you build or buy when adding these transformative capabilities into your solution?

At Cube, we believe the answer is clear—build your composable embedded analytics and Generative AI solution to your unique requirements. By choosing Cube Cloud, you can create tailored embedded analytics and Generative AI experiences that align perfectly with your audience’s needs. You can even monetize extended capabilities beyond your data product, such as Data-as-a-Service with Cube’s extensive suite of APIs and integrations. While buying off-the-shelf solutions may seem quicker, it often results in compromises that limit your product’s impact. Here’s why building with Cube Cloud is the smarter choice for your embedded analytics and Generative AI solutions.

The Limitations of Buying Embedded Analytics and Generative AI Solutions

Modern BI platforms and pre-built Generative AI solutions offer a tempting promise of rapid deployment of analytics and AI capabilities without significant engineering effort. However, their one-size-fits-all approach often introduces challenges that can derail your product strategy:

  • Too Much or Too Little Functionality: BI platforms and AI tools are designed to cater to a wide range of users. This means they often include features your users don’t need or lack the specific capabilities your application demands, leaving gaps you can’t fill without additional customization.
  • Fragmented Experiences: Buying embedded analytics and Generative AI capabilities from different vendors can create new data silos from disjointed workflows. Users may have to navigate separate interfaces for analytics and AI-driven interactions, creating friction and diminishing your product’s value.
  • White-Label Challenges: Even with white labeling, pre-built solutions rarely feel native to your product. The experience can appear bolted on, undermining your brand identity and leaving users questioning its authenticity.
  • Lack of Control and Scalability: Pre-packaged solutions often lock you into a vendor’s ecosystem, limiting your ability to be agile and adapt as your product grows or your users’ needs evolve.

The Case for Building Embedded Analytics and Generative AI with Cube Cloud

Building your own embedded analytics and Generative AI capabilities allows you to create a seamless, scalable, and brand-aligned experience for your users. With Cube Cloud as your foundation, you gain the flexibility to innovate without compromise.

  • Future-Ready Data Stack: Cube’s universal semantic layer provides a unified, governed, and optimized data foundation for both analytics and AI. This ensures your solution can scale as your data grows and your AI needs evolve, without being tied to a vendor’s roadmap.
  • Unified Functionality: With Cube, embedded analytics and Generative AI capabilities can be integrated into a single, cohesive user experience. Users don’t have to switch between tools to access insights or interact with data—they get everything they need, right in your application.
  • Tailored User Experiences: Cube Cloud enables you to design analytics and AI workflows that are fully aligned with your product’s purpose and your audience’s needs. Whether it’s crafting interactive dashboards, enabling conversational data exploration, or providing predictive insights, you’re in control.
  • Brand-First Integration: Building with Cube keeps your product at the center of the experience. Embedded analytics and AI workflows feel like a natural extension of your application, enhancing your brand rather than diluting it.

How Cube Cloud Powers the Next Generation of Embedded Capabilities

Cube Cloud is more than a tool for building embedded analytics; it’s the foundation for delivering transformative data experiences. As a universal semantic layer, Cube bridges the gap between your cloud data platform and the capabilities you want to offer, while enforcing governance and security for every data consumer.

  • For Embedded Analytics: Cube unifies and optimizes your data, ensuring real-time insights are accurate, consistent, fast, and ready for consumption in your purpose-built application.
  • For Generative AI: Cube provides AI models with clean, trusted, and contextual data, enabling conversational data exploration, intelligent recommendations, and personalized predictions—all seamlessly integrated into your application.
  • For Data-as-a-Service: Cube allows you to monetize your data in new ways by providing on-demand data access for external users through Instant APIs. Now you can support both ad-hoc analytics and tool choice from BI platforms to spreadsheets, without your data engineering team’s involvement.
    This unified foundation means you don’t have to choose between analytics and AI. Cube Cloud supports both, empowering you to build a cohesive, cutting-edge experience for your users.

Why Build, Not Buy?

Embedded analytics and Generative AI are no longer separate considerations—they’re part of a unified user experience that drives engagement and delivers value. Buying pre-built solutions might promise speed, but it forces you to compromise on functionality, flexibility, and user experience.

Building with Cube Cloud gives you the power to innovate on your terms. You can create tailored solutions that integrate seamlessly into your application, scale with your growth, and set your product apart in a competitive market.

Don’t limit your vision to what pre-built solutions offer. Build with Cube Cloud and deliver the future of embedded analytics and Generative AI today. Ready to build smarter with Cube Cloud? Contact sales to learn more about Cube’s embedded analytics and Generative AI capabilities.

Interested in learning more? Register for our webinar, Stop the AI Hallucinations: Giving Context to Gen AI with a Semantic Layer.