Build with AI. Deploy with Ridge.
AI-native analytics, ready for real users. Claude can build you a dashboard in minutes. Putting it in front of 10,000 customers is a different job. Ridge AI turns AI-built analytics into fast, secure, embedded experiences on live data, with an agent that answers the questions the dashboard doesn't.
The dashboard was never the hard part.
To ship it, you need
A dashboard from an AI chat
Building the rest yourself
Ridge
Live data
A snapshot from when you prompted
A refresh pipeline you build and run
Connected to your data and kept fresh
Each customer sees only their data
Not built in
Permissions you build, test and audit
Per-customer partitioning for charts, filters and AI questions
Speed at scale
Data aggregated to fit the chat
Performance tuning, forever
Sub-second in the browser, on the full dataset
Answers to the next question
Another prompt, by you
An AI agent with guardrails you build
An Explore Agent on the whole dataset
A home in your product
A link or a screenshot
Front-end work for every surface
Embedded with the Embed SDK, themed to match
Costs that don't spike
Not built to serve thousands of users
Warehouse queries on every click
Browser compute, priced per Ridge
The analysts agree: shipping is the hard part.
“Ridge also addresses the build-versus-buy question product teams now face as AI coding tools make custom dashboards look easy. The hard part of customer analytics is tenancy, validation, and upkeep.” Herb Blecher, Research Director, Enterprise Management Associates (EMA). In hands-on testing, EMA measured sub-second dashboard interaction on datasets up to 3 million records, with each embedded session scoped to its tenant and an Explore Agent alongside every dashboard.
Build anywhere. Deploy with Ridge.
Start from a dashboard you made in Claude: an image or its HTML is enough. Bring one from legacy BI, sketch one on a napkin, or let the Build Agent build it. Working in Claude or ChatGPT? The Ridge MCP lets you build without leaving the chat.
Ridge rebuilds it on your full dataset, not the sample an AI chat could handle. It connects to your data, keeps it fresh and partitions it by customer. Interactions run in the browser, so they're fast.
Put it in your product with the Embed SDK, themed to match. Every Ridge comes with an Explore Agent that answers your users' follow-up questions about the whole dataset.
From people who've shipped analytics before.
Founders, product leaders and data leaders on what changes when analytics are fast, embedded and AI-native.
"Sub-second buttery interactions."
"Ok, this is really f***ing cool."
"The performance was insane."
"This is what I want to see built for data in the age of AI."
"Ridge is solving a deep problem I've seen up close: quickly getting beautiful, interactive analytics in front of your customers."
"Quickly putting together a dashboard is super powerful for showing clients their business outcomes."
"It's brought the data alive. We were really impressed with how fast it was, and how it had a sense of the data with questions that I didn't even think to ask."
"Being able to ask free-form questions in the data agent makes dashboards vastly more flexible and useful."
“Why not just build it all with Claude?”
Do. Build it in Claude. Then the real work starts: embedding it in your product, making sure every customer sees only their own data, keeping it refreshed and fast, updating it when the business changes, and putting guardrails on an AI agent your customers will use. Ridge does that part, and Ridge is SOC 2 Type II compliant. You can build all of that yourself. Or you can spend that time on your core product.