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Ridge AI

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(11)4.9/5

Ridge AI is an embedded analytics platform that turns AI-built dashboards into secure, fast, interactive analytics. Companies use Ridge to produce customer-facing dashboards and data agents. Data and business teams use it to share analytics with large non-technical audiences, such as executives and field teams. AI has made creating analytics easy. Putting that dashboard in front of 10,000 customers is a different problem. It needs live data, permissions, per-customer data partitioning, performance at scale, and ongoing upkeep. Ridge is the infrastructure layer that handles that work, so analytics can be shared, trusted and acted on. Ridge adds a data agent to every dashboard, so your users get both visual analytics as well as conversational analytics. How Ridge works: Insanely fast interactive performance. Dashboards respond in under a second on datasets of up to 3 million records. Data agent. Each Ridge pairs a dashboard with an Explore Agent that answers end users’ follow-up questions in natural language, on the same data. Secure multi-tenancy. Each embedded session can be scoped to one customer, and customer data is isolated at the row level. Ridge has completed a SOC 2 Type 2 audit. Data integrations. Ridge connects to Snowflake, Databricks, BigQuery, object storage, and more. Semantics, transformation and governance stay where they already live. Native look & feel. An Embed SDK and theming mean Ridges natively fit with the host application when embedded. MCP: Ridges can be created programmatically, for example at the end of an agentic workflow. Predictable costs. Interactions run in the browser, so every click doesn’t add to your warehouse bill. Pricing is per use case, so teams can forecast costs as their audience grows. Build anywhere. Use AI tools such as Claude, Ridge's Build Agent, or even build from an image. Ridge lets you edit with AI as well as directly manipulate layout and text. Common use cases Customer-facing analytics that show customers the measurable value they get from your product, without building and maintaining analytics infrastructure in-house. Replacing embedded BI tools that are slow, costly or hard to maintain. Sharing curated analytics with executives, regional leaders and frontline managers. Ridge was founded by CEO Ellie Fields, a 12-year Tableau veteran and former Salesloft product leader, and chief scientist Jeff Heer, a University of Washington professor who co-created D3, Vega-Lite and Mosaic. Ridge is backed by Madrona. A 30-day free trial includes customer data partitioning.

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[Kenny D.](https://www.g2.com/users/2a546652-4450-4a18-826e-9aa18d70a41c "Kenny D.")

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3 days ago

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[
# How are you balancing speed vs shareability in Ridge AI for quick data questions?
](/discussions/how-are-you-balancing-speed-vs-shareability-in-ridge-ai-for-quick-data-questions)
I like that Ridge AI lets me drop in data and get useful insights quickly without setting anything up first, and the image-to-dashboard feature has been great. The biggest value is turning a pile of data into something I can actually look at and share with other people, fast. For one-off... [Read more](/discussions/how-are-you-balancing-speed-vs-shareability-in-ridge-ai-for-quick-data-questions)

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3 days ago

Design Partner | Health informatics | Software Engineer | Environmental Science | University of Rochester Medical Center |

Design Partner | Health informatics | Software Engineer | Environmental Science | University of Rochester Medical Center |

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[
# How do you handle data-cleansing style questions in Ridge AI without losing the metric?
](/discussions/how-do-you-handle-data-cleansing-style-questions-in-ridge-ai-without-losing-the-metric)
I like Ridge AI’s short prompts and focused, direct answers, and I’ve found the team very responsive when issues come up (like exact counts, date sorting, and a CSV load error). One challenge is that the AI sometimes won’t act on natural-language requests that sound like data cleansing, like... [Read more](/discussions/how-do-you-handle-data-cleansing-style-questions-in-ridge-ai-without-losing-the-metric)

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