What Sets Quodor Data Apart?

Our AI agent assistant isn't a feature we slapped on to an already designed product, it's built into the core of our product from the beginning.  Our agent has the complete context on exactly how you and your coworkers are using the tool, what the underlying data looks like, and what the reports and dashboards look like.  It can automate anything you can do, and the changes it makes are always easy to preview, accept, reject, or modify.  No other company has so thoroughly reimagined the entire User Experience of a BI tool to work so seamlessly with an AI assistant.

Our BI platform encompasses not just the final presentation of data in reports and dashboards, but the entire stack of data transformations leading up to it, starting from the raw input data.  See our blog post on why this is an absolute essential feature in a new BI tool and why it's especially important for getting the most out of the AI assistant.

Even when other BI tools do support Data Pipelines, they only support a very limited number of transformation types.  In particular, you might get just a SQL query, and maybe a python script that reads and writes from disk.  Our model for Data Pipelines is much more flexible.  You can leave intermediate stages in memory (this can give you a HUGE boost in performance!), you can use a wide variety of languages and programming styles, plus version control on the changes.  Other tools offer partially featured data pipelines and give guidance on when or when not to use them.  Our tool lets you build whatever data pipeline you want, in the languages and tools of your choice.

We're dramatically simpler to use than comparable tools.  When you try it for yourself, you'll see than we let you accomplish the same kinds of data transformation and dashboarding tasks using far fewer concepts, screens, guides and docs.

A lot of this simplicity comes from us relying on the AI agent.  Most of the features our competitors offer can be replaced with a simple prompt to your AI assistant.  The rest comes from us being clever about our data model.  It's clean, simple, and it always gets the job done.

Creativity is different in the age of AI.  You're no longer supposed to be writing precise logic and computer code yourself, that's largely a task for a robot.  Your role is to be the critic, or the evaluator of the AI agent's work. Our product recognized that shift and orients itself around previews, evaluating results, accepting, rejecting or modifying them.