Data Broker Test
// How the category uses it
Not a category term. The test is ours.
The data broker test asks: could a well-funded competitor purchase or aggregate equivalent training data for your AI platform through commercial data providers? If yes, the training corpus is commodity. The AI layer is differentiated only by model access and go-to-market. That is a reversible advantage.
// How superGM defines it
If the AI in a platform is trained on POS transaction records, labor logs, review scores, or reservation histories — that data is broadly available from multiple sources. Any competitor can acquire equivalent training data and build a competing model. The "proprietary" claim collapses under scrutiny.
// Why it matters
Operators paying premium prices for AI platforms deserve to know whether the AI is genuinely defensible or reproducible. The data broker test is one diagnostic. Platforms that cannot answer it clearly are signaling that their moat is not what they claim it is.
- superGM.ai Corpus built from observed behavioral decisions at scale in venues far larger than restaurants. Not available from any data broker. Not purchasable.
- Most AI-wrapper upstarts Training data is restaurant operational — POS, scheduling, feedback. Available from data brokers or integration partners. Commodity corpus.
One question that separates proprietary AI from commodity AI: is your training data available for purchase?
Most operators who apply
will not be selected.
We work with operators whose operation, culture, and competitive position fit what we built this for. We review every application individually. We select from the backlog.
If you are reading this because a competitor sent it to you, they may already be in production. We don’t confirm or deny active deployments.