Health, home and travel decision
BioStacks
A technical user can implement a working scanner, parser, and scoring engine (the core useful workflow) in a few weeks, but reproducing BioStacks' curated clinical dataset, polished mobile UX, and production-grade ingestion/coverage would be expensive and time-consuming—so building a narrow replacement is realistic, but matching the full paid product is not.
Visit website↗$3.33/mo
$40/yr
Read off the official pricing page.
$100one-off74 h to build
$30/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 12 seats.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- User photographs or scans a supplement label → OCR extracts Supplement Facts → normalize ingredient names and doses → scoring engine compares to curated clinical dose ranges and form bioavailability rules → return product score, interaction flags, and citations.
What it still won’t have
- The vendor-curated clinical database and precompiled dose ranges and mappings
- Polished mobile app UX and in-app billing on App Store / Google Play
- Extensive ingredient name variant normalization (~2,200 variants)
- The vendor's prewritten citation links and curated reading-room content
What remains hard
- Proprietary data
620 clinical actives Each with therapeutic dose ranges pulled from RCTs and meta-analyses, not Daily Value tables.
- Proprietary data
Every stat on this page maps to a number in the codebase. No marketing inflation.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 12 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal BioStacks-like service using React Native for mobile (Expo), a Node.js + Express backend, and Postgres. Core features in scope: 1) mobile camera barcode scanner and photo upload; 2) server-side OCR using Google Vision API to extract supplement facts; 3) ingredient name normalization table and unit conversion service; 4) rule-based scoring engine implementing (dose vs clinical range, form bioavailability, evidence weight, simple interaction rules) that returns a 0–100 score and safety flags; 5) REST API and Postgres schema for actives, rules, scanned products, and user stacks; 6) simple web admin UI to edit mappings and clinical ranges; 7) subscription gating (mockable) and in-app purchase hooks left as integration points. Explicitly out of scope: training models or assembling an exhaustive curated clinical database (supply a small seed CSV instead), advanced AI chat about stacks, and publishing to App Stores. Require error handling for OCR failures and label parsing edge cases, unit tests for parsing/normalization and scoring logic, and basic CI that runs tests on push.
How we checked
How the score was reached
- Partly verdict base52
- 2 cited sources+1
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score57
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productBioStacks — official product page
- official pricingBioStacks Pricing
Integrity checks
What held up, and what did not.
