Search: Snag. Result: Hot Dog. We Fixed That.

The problem shows up on a Saturday. A client tries to log their post-hardware-store sausage sizzle. They search "Bunnings sausage sizzle" and get nothing. They search "snag" and get results for a fishing brand. They type "beef sausage, grilled" and call it close enough. The data is wrong before they have finished the onion.

This is the daily reality for Australian trainers using US nutrition apps. The food databases are built for the markets the companies operate in. Most nutrition tools, including the one Trainerize ships as a paid add-on, run on USDA data. Australia is an afterthought.

What Your Clients Are Actually Eating

Australians eat differently to Americans. Not dramatically, but enough to matter when you are tracking macros with any precision.

A client having Weet-Bix with full cream milk for breakfast. A Tim Tam mid-morning. Lunch from Guzman y Gomez. A Woolworths branded Greek yoghurt in the afternoon. A lamb chop and salad for dinner.

Search all of those in MyFitnessPal or a USDA-based app and you will get a mix of results: some close, some wrong, some missing entirely. The Woolworths Greek yoghurt almost certainly will not be there. The GYG entry, if it exists, is often user-submitted and unverified. Your client fills in the gaps with guesswork and logs it anyway.

The data quality issue compounds over weeks. A client eating slightly wrong macro numbers every day ends up working from a plan that was never accurate to begin with. You cannot make good coaching decisions on bad data.

What We Built Instead

BuildStability nutrition is built on three data sources.

AUSNUT R3 from Food Standards Australia New Zealand. This is the official Australian food composition database: the reference standard for generic Australian foods. Vegemite, Weet-Bix, meat pies, lamingtons. The foods Australians actually have in their pantry.

49,000+ barcoded Australian products from Open Food Facts AU. Scan a barcode on a Coles or Woolworths product and the entry is there with nutritional data pulled directly from the product label, not a US equivalent.

Curated Macca's, Guzman y Gomez, KFC, and Subway data. The specific items from the chains your clients actually eat at, entered from published nutritional information. Not user-submitted guesses.

Five logging methods: barcode scan, label photo (the app reads the nutrition panel via OCR), meal photo (AI estimates macros from a photo of the meal), conversational logging via Repley ("I had a beef pie and a Coke Zero for lunch"), and voice. Whichever way your client prefers to log, it all feeds the same database.

Training Days and Rest Days Are Not the Same Meal Plan

This is the piece most nutrition apps miss because they were built separately from the training software.

A client training three times a week needs different macros on Monday (legs session) than they do on Sunday (recovery). The caloric requirement on a hard session day is meaningfully higher. The carbohydrate demand is different. Giving clients the same targets every day and letting them figure out the rest is not coaching nutrition. It is printing a spreadsheet and calling it a plan.

BuildStability connects the training calendar to the nutrition targets. On a scheduled training day, the macro targets adjust to reflect the session load. On rest days, they pull back. Trainers set the overall targets and the system handles the daily variation based on what is actually in the client's calendar.

This is not a complicated idea. It is just not how most nutrition tools work, because most nutrition tools were not built alongside the training software. When they live in the same platform, the connection is the obvious default.

This Is Beta. That Is the Honest Answer.

The nutrition feature is currently in beta. Here is what that means in practice.

What works now: barcode scanning, label photo logging, meal photo logging, voice and conversational logging via Repley, macro targets by day, training day adjustments, client-facing logging, and trainer overview of client nutrition data.

What is still being built: the database improves as more trainers use it. When a barcode scan returns no result, the app prompts a label photo as a fallback. When trainers flag a missing food, it goes into the update queue. The more trainers who use the nutrition feature, the faster the gaps get filled. This is not a vague promise. It is how food databases actually improve, through real usage identifying what is missing.

We are building this specifically for the Australian fitness industry. That means Australian foods, Australian portion sizes, and a system that knows your clients eat at Woolworths, not Whole Foods.

The macros that adjust for training days are not a future roadmap item. They are in the product now, because we built nutrition alongside training from the beginning rather than bolting it on later.

If you train people who eat Vegemite toast before their morning sessions and grab a sausage sizzle on the way home from the hardware store on Saturday, this is the nutrition tool that was missing.

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BuildStability nutrition is currently in beta. The food database is actively growing. If you encounter a missing food or barcode, flag it through the app and we will add it. Features and database coverage are updated on an ongoing basis.

Nutrition data from AUSNUT R3 is sourced from Food Standards Australia New Zealand. Open Food Facts AU data is crowdsourced and may contain inaccuracies. Curated QSR data is based on publicly available nutritional information from each chain as of 2026 and may not reflect current menus. BuildStability nutrition is not a substitute for advice from a registered dietitian or nutritionist.