Features
DashboardGPT is built around one loop — ask, see, explore. Every feature below exists to keep that loop fast.
Capabilities
Eight things the workspace does, each of which you can exercise in the public demo or on your own data.
Ask a question and get a real answer: the query runs against your data, and the result is visualised the way the result deserves.
Answers are objects on a canvas, not tiles in a grid. Arrange them, group them, and keep the thread of an investigation visible.
No SQL, no drag-and-drop field wells. Questions and follow-ups are written the way you'd ask a colleague.
Start with a CSV or Excel file in seconds. Warehouse connections are coming soon, for the whole picture.
Use your own AI provider credentials. Model usage is billed to your account, under your organisation's terms.
When the answer is an explanation rather than a chart, you get an explanation — with the numbers it was drawn from.
Columns are profiled into dimensions, measures and time grains, so questions resolve to the right fields without configuration.
Query execution and chart rendering are built on Apache Superset, so the engine underneath is a proven analytics stack.
Interactive canvas
Analysis rarely arrives in a tidy 3×2 layout. DashboardGPT gives every answer a place on a surface that grows with the question.
Every chart, metric, table and insight is a node you can move, resize, duplicate or delete. Nothing is locked into a grid someone else designed.
Follow-ups sit beside what prompted them, so the shape of an investigation — what you asked, what you found, what you asked next — is the artefact.
Collect the nodes that answer one question into a group, tidy the rest with a single layout action, and keep the canvas legible as it grows.
There is no publish step and no dashboard to maintain. The canvas is a workspace you keep open while the question is still live.
AI analyst
Show revenue by month.
Here's the monthly revenue trend for the last two years.
Added Revenue trend
Break it down by region.
North America leads on volume, but APAC is growing fastest.
Added Revenue by region
Which region performed best?
Two answers, depending on what you mean by best — here's both.
Added Regional performance
Change this to a bar chart.
Conversational analytics
Select a chart and ask “compare this with last year”. You don't restate the measure, the filter or the time range — the conversation carries them.
Your data, your models
DashboardGPT is designed to sit on top of what you already have, using credentials you already control.
Start with a file. Drop in a CSV or Excel export and DashboardGPT profiles every column — types, cardinality, date grains, likely measures — so your first question works without any modelling step.
Use your organisation's own AI provider credentials. Model usage is billed to your account, governed by the agreement you already hold with that provider, and the key can be rotated or revoked by an administrator at any time.
Use cases
The product doesn't change per department — only the dataset and the question do.
Pipeline, bookings and quota attainment, sliced by team, territory and segment.
Which regions are behind plan this quarter?
Channel performance and acquisition cost without waiting on a reporting queue.
Which channel has the lowest cost per new customer?
ARR, expansion, churn and cohort retention from the subscription data you already have.
How is net revenue retention trending by plan?
Revenue, margin and spend, reconciled across periods and entities.
Show gross margin by product line, quarter over quarter.
Throughput, fulfilment and service levels, with the outliers called out.
Where did fulfilment time get worse last month?
Adoption, activation and feature usage, tied back to revenue.
Which features do our highest-retention accounts use most?
The demo opens straight into the product — a real dataset, a real AI analyst, a real canvas. No account, no install.
