Food businesses often rely on broad labels such as cuisine, category, dietary requirements, and nutritional facts, but these do not capture how a dish actually feels or tastes to a person. That means many decisions are still based on surface-level metadata rather than a deep understanding of preference.



Without that layer of insight, it becomes difficult to personalise discovery, predict product performance, refine offerings, or understand why certain items underperform. The result is missed opportunity across recommendation, innovation, localisation, and waste reduction.



ayme solves this with a proprietary multi-dimensional food profiling model that captures granular perceptual characteristics. It tags large recipe and product datasets with a richer description of what food is actually like, not just what it is called.