Pre-develop recipe variants with AI
Food manufacturers develop new recipes and flavour variants
Fits: Research & development
Aim: instead of cooking one variant after another in the pilot plant, the AI uses your own recipe and test data to suggest the variants most likely to succeed. To be honest: this depends entirely on your data. Without many of your own recipes with properly recorded sensory and analytical values, it remains a matter of collecting ideas, and taste predictions have so far only been demonstrated in individual research studies.
Is this for you?
- You regularly develop new variants of a product group, e.g. different sweetening, less salt, plant-based substitutes.
- From years of development, you have recipes with test, analytical and sensory values, including variants that never went to market.
- You can run a limited project on one product group without a product launch depending on it.
First check whether your data is sufficient: use the template below to check a made-up or anonymised overview of your development data for one product group to see what is enough for predictions and what is missing. The result is a list of requirements, not yet a recipe.
How to go about it
- Define the development goal and hard limits
- Provide your own recipe, analytical and sensory data
- Have a limited number of variants suggested
- Check recipe, legal and technical aspects and select
- Produce in the pilot plant and test for sensory quality
- Feed panel and analytical values back
Templates to copy
The complete guide
- 6 steps explaining exactly what to do
- 3 proven templates to copy into your own AI
- Safe use: data, checking, deciding, informing
- Pitfalls, effort and how to recognise success
With the training you get all 430 guides for as long as your access runs.
Same approach, other use cases
15 more use cases follow the pattern “Designing & simulating”.
LK-01 · Legal status 08.10.2026