Amla started from a simple frustration: reading a food or cosmetic label shouldn't require a chemistry degree. Every ingredient list is technically “available” to you, but almost nobody has the time or background to actually decode it product by product, aisle by aisle.
So we built a scanner that does the decoding for you — and shows its work.
Amla combines Nutri-Score, a nutrition-balance system developed by public health researchers, with NOVA, a processing classification developed by researchers in Brazil. Both are open, peer-reviewed, and used across multiple countries — not something we invented, and not something any single country owns. We layer in specific, well-evidenced red flags — like the WHO's classification of processed meat, or additives with real regulatory action behind them — because some risks are serious enough that a good overall nutrition profile shouldn't be allowed to hide them.
We're starting in Mauritius, expanding to India, with Singapore and the UAE on the horizon after that. We're a small, self-funded team — this isn't a scanner built to sell your data or push you toward “sponsored” products. It's built to be trusted, which means we'd rather stay small and honest than grow fast and compromise on that.
Have a product we should add, or a score you think we got wrong? Tell us →
Amla