Today Ridge AI is generally available, delivering production-grade embedded analytics that can be built and deployed in minutes. Once deployed, Ridge’s interactive experience combines the best of traditional visual approaches and AI.
Our mission at Ridge AI is to make it easy for anyone to understand, share and act on data. This is a big step in that direction.
Embedded analytics means data where you need it.
There is a broad need for what is called “embedded analytics.” Any time you need to share a data story with a broad group of people you need scalable and well-designed analytics. Traditionally, those can take months to build and tune.
Ridge allows customers to build and deliver them in minutes. And for analytics users, Ridge pairs highly performant visual analytics with a data agent that lets people ask their own questions in natural language.
Ridge AI Platform Walkthrough
What’s new with this release?
Since we announced our closed beta in April of this year, we’ve shipped major improvements to the product:
Helping builders deliver analytics guided by value:
- Ridge’s Build Agent is smarter and more capable. It helps anyone connect data to value, reasoning about business questions and ultimately translating them into a best-practice dashboard. This means people don’t have to understand data design or charting mechanics to deliver data to their audiences.
- Streamlined editing with direct interaction, including delete and edit charts, change layout, edit text and titles, and sort.
- Better translation of user intent to dashboard layouts that execute on that intent.
- Safe exploration with unlimited undo and redo.
- More data connections.
A fast, web-native experience for consumers of the analytics:
- An embedding SDK that lets host apps interact and set initial filters based on user identity or context.
- More expressibility and natural formatting in Ridge Plot, our AI-ready plotting language.
- The ability to support more data in the browser.
A new architecture for embedded analytics.
Ridge uses a radically different architecture than traditional server-based approaches. Ridge is both browser-first and AI-native. That lets us deliver a product that is markedly different than legacy products in several ways:
Performance. By using browser-based technology we can deliver unprecedented interactive speed for analytics. Foundational technologies include DuckDB, WebAssembly, and the Mosaic open-source framework (developed by our co-founder Jeff Heer and Dominik Moritz at CMU).
Learning curve. A purpose-built agent harness lets us dramatically reduce the learning curve, and time and expense, to build analytics. Builders need only have data and questions. They can interact with Ridge’s Build Agent at the level of the business, not at the level of charting, interaction and layout. The end result is a best-practice, interactive dashboard and data agent that speak to the business questions.
Form factor. Ridge’s embedded analytics pairs a dashboard and a data agent so that customers can deliver the big picture and enable long-tail questions. Linked interactivity allows users to explore across both interfaces at once, combining the power of traditional visual analytics with AI.
Cost.
- Ridge is priced to meet the embedded market– priced by case, not by user. This means costs are predictable and customers can grow at their own pace.
- Because Ridge’s browser-first architecture uses local hardware for computation, our customers do not incur large compute costs in back-end databases.
Enterprise guardrails.
- Multiple layers of validation ensure high-quality results across Ridge’s agentic experiences.
- Ridge integrates with existing data stacks, while ensuring that users can see exactly the data they are supposed to see.
- Ridge is built secure by design and is SOC 2, Type II compliant.
Where is this going?
This is only the beginning. We hope that a better experience for both builders and consumers leads more people to share data in more places.
We also see emerging needs for analytics in agentic workflows. Ridge’s products are built with composability in mind, so that agents can access and build Ridges as easily as people can.
Thank you!
A huge thank you to early customers and everyone who gave us feedback, as well as our investors and community. We’re building Ridge AI because we believe that shared, intuitive analytics can be a positive force in organizations and in our communities.
We couldn’t do it without your support, feedback and belief in us. Thank you!