How the survey works
Our AI voice agent, Mia, phones independent cafés and asks the price of a regular flat white. The answer is extracted from the call transcript and stored as a price observation. The public dashboard shows the small or regular flat white price in Australian dollars.
The survey focuses on independent cafés. Phone collection is scheduled during weekday business hours. Public contributions go into a separate review queue and are not immediately added to the phone survey.
What the numbers mean
The Sydney average is the arithmetic mean of the visible price observations. Each suburb average is calculated from the observations in that suburb. Prices in the café list and map are the amounts returned by the survey, without alternative milk or other extras.
We show the number of observations for each suburb because context matters. A suburb with one surveyed café is a sample of one, not a definitive price for the whole neighbourhood. The lowest and highest suburb averages can be tied.
Fresh data, with limits
The dashboard loads the available dataset when you visit. Its retrieval date tells you when the dashboard was prepared; it does not establish when each café was last called. The public feed currently does not include a collection date for each observation.
Automated venue matching, AI transcription, and price extraction can make mistakes. A chain or misclassified business can enter the feed. Regular and small sizes can also vary between cafés. Coverage is incomplete, and cafés can change their prices. Check with the venue before ordering, and contact us if a price looks wrong.
Open data and attribution
The dataset is available under Creative Commons Attribution 4.0. You may use it for reporting, research, and personal projects with attribution. Include the retrieval date and relevant sample size when quoting a figure.
Download the live JSON dataset ↗ · Information for AI tools ↗
About the project
Flat White Index is part of Agentic Consciousness, created by Daniel Hall, Richard Kelsey, and Geoff Huens. Our aim is simple: give a familiar daily purchase a little more context.