Health, home and travel decision
Nourish
A narrow self-hosted replacement (photo intake + basic scoring and logs) is realistic for a capable developer using existing vision APIs, but reproducing the full polished mobile product, curated scoring quality, and App Store UX is a larger effort and not fully covered by the supplied pages.
Visit website↗Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off76 h to build
$50/mo6 h/mo upkeep
No published price to break even against.
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 takes a meal photo (or types/scan barcode) → backend classifies meal and estimates nutrition → scoring engine computes a gut score and breakdown → user logs reaction and other metrics → weekly insights surface patterns.
What it still won’t have
- Polished App Store presence and native iOS UX
- Proprietary model/score tuning and curated food database powering the app
- Built-in privacy/terms assurances tied to the vendor ("Your health data is never shared with third parties")
- Convenience features like barcode scanning and one-tap water logging as integrated mobile affordances
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Nourish does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
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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 meal-scoring web service and simple iOS client. Stack: Node.js + Express API, Postgres, AWS S3, background worker (Bull or similar) on an EC2 or small container, SwiftUI iOS app; use Google Cloud Vision or AWS Rekognition for image labels and a small rule-based nutrition lookup (or USDA API) to estimate fiber/processing. In scope: photo upload, image->labels inference, nutrition estimation, scoring engine that outputs 0–100 plus microbiome/digestibility/inflammation breakdowns, user auth, logging reactions/sleep/water, weekly aggregation job, and a simple UI to view meals and insights. Out of scope: training custom image models, multi-user teams, payment/subscription handling, and advanced personalization. Include error handling, logging, and automated tests for the API and scoring logic.
How we checked
How the score was reached
- Partly verdict base52
- 3/3 assessment runs agreed+4
- Evidence score56
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 →Integrity checks
What held up, and what did not.
