About
Why FoodMaya
FoodMaya started from a simple frustration: understanding the nutritional value of a real meal often requires jumping between multiple tools, estimating portions manually, and guessing how ingredients translate into nutrients.
Both macro and micronutrients are essential for overall physical and mental health, but in practice they are difficult to track consistently through real meals. Instead of relying on rough estimates or fragmented tools, having a clearer, ingredient-level view of nutrition can make it easier to build a balanced and sustainable diet.
I wanted something that could take a list of ingredients—or a full recipe—and turn it into a structured, data-backed view of macros, micronutrients, and daily intake. Many existing tools return nutrition values without explaining their data sources or assumptions, making it difficult to evaluate their reliability. FoodMaya addresses this by using USDA FoodData Central as its primary data source and by exposing ingredient matching, portion assumptions, and data references so users can understand how each estimate is generated.
Who this is for
FoodMaya is designed for anyone who wants a deeper understanding of their meals, and especially for dieticians, researchers, and health-conscious individuals who need ingredient-level insights and micronutrient coverage.
If you’ve found that existing tools work well for single foods but struggle with real recipes, this tool is built with that gap in mind.
How it works
FoodMaya estimates macro and micronutrients from ingredient lists using USDA FoodData Central along with ingredient parsing and weight estimation logic.
Ingredients are parsed, matched to USDA foods, assigned weights from explicit measures, USDA portions, or fallback defaults, and aggregated into meal-level nutrition totals.
The system is designed to be transparent about ingredient parsing, matched foods, and weight sources so users can understand how results are generated.
Early stage
FoodMaya is an early-stage project. I’m continuously improving parsing accuracy, nutrient coverage, usability, and performance.
Development is ongoing and incremental, as I am currently working on this alongside a full-time role.
Important note
Some ingredients may require estimated weights when exact amounts are not provided. These estimates are intended for informational use and may not reflect exact real-world values.
Feedback
If you find this useful—or if something doesn’t work as expected—I’d really like to hear from you.