"AI-powered" is the most over-used phrase in health technology. Here is how we try to use it honestly — as a testable hypothesis, not a marketing badge.
The credibility problem
Almost every new diagnostic claims to be AI-powered. Most of the time the phrase carries no testable meaning. For a research-stage company, leaning on it as a selling point is not just lazy — it is a credibility risk with exactly the scientists, engineers, and investors who can tell the difference.
AI as a hypothesis
We treat machine intelligence as a research hypothesis: that continuous, multi-signal observation interpreted by trained models can extract earlier or richer information than fixed-endpoint methods. A hypothesis is something you state precisely and then try to disprove — not something you assert and decorate.
That framing has a practical consequence. It means being explicit that our models are unproven, that performance has not been demonstrated, and that the interesting claims are the ones still ahead of us. Honesty about stage is not a weakness in deep tech; it is the foundation of trust.
AI-assisted approaches across BIQADX programs are research-stage hypotheses. No diagnostic performance has been validated.