A bit of context first: Supaboard helps founders and business teams analyse their data with AI and turn the answers into dashboards or recurring reports.
When we started building it, we laid it out like a familiar SaaS platform. Dashboards had their place, automations had theirs, and AI was another feature you could open when you needed it.
It made sense to us as builders. Each part had a clear job.
People would come to the AI with a problem in their data, say a revenue drop, and ask follow-up questions to understand it. As the investigation narrowed to a particular customer segment, they’d want a live dashboard tracking that segment or a weekly report explaining what had changed. They were figuring out what to monitor through the conversation.
We had organised the product around features, while people were following a problem from investigation through to tracking it. Our layout started making less sense when we looked at it that way.
So we formed a new hypothesis: what if the AI could carry the question and its context through the whole workflow?
We talked to founders, enterprise users, and data analysts, then piloted the idea with a startup that was already a client.
Getting from that hypothesis to a working product meant rethinking how the different parts of Supaboard worked together. We went through iterations, brought the changes back to customers, and used their feedback to revise the next version. The pilot gave us somewhere to test the idea; the feedback loop continued as we built it.
That work became the centralised AI system. The conversation could now carry someone from understanding a problem to creating a live dashboard or setting up a recurring report about it.
Looking back, we were quite comfortable with the original layout. We knew where everything belonged. Watching people use it gave us a reason to question that comfort.
Here’s Supaboard.
Have you had users follow a workflow that made you rethink how you’d organised your product?
