# Health’s Spot

> Πλατφόρμα παρακολούθησης και σχεδιασμού γυμναστικής που ενώνει προπόνηση, καρδιο, διατροφή, αποκατάσταση και δομημένα προγράμματα.

- Canonical HTML: https://www.digiminds.gr/work/healthspot
- Markdown representation: https://www.digiminds.gr/ai/el/work/healthspot.md
- Language: el-GR
- Alternate language HTML: https://www.digiminds.gr/en/work/healthspot
- Alternate language Markdown: https://www.digiminds.gr/ai/en/work/healthspot.md
- Έτος project: 2026


## Επισκόπηση

An audit of an existing fitness product, turned into a production MVP definition: what is genuinely built, what has to be fixed first, and what “ready” actually means.

## Το πρόβλημα

The product already existed as a working codebase spanning training, cardio, nutrition and recovery. The engagement started from that code rather than a blank page — establishing what was genuinely implemented, and what only looked implemented.

## Στόχος

Define a production-ready version of the product with reliable core fitness workflows, secure handling of user data, and clear release criteria.

## Ρόλος

Advisory engagement: audited the existing product, defined the production MVP scope, and translated technical risks into prioritised implementation and release criteria. The existing application code is not mine.

## Οι δυσκολίες

- Separating genuinely implemented functionality from prototype, placeholder and incomplete surfaces, without overstating readiness.
- Tracing authentication, authorization, persistence and subscription behaviour across several frontend and backend integration points.
- Turning a broad existing feature set into a smaller, testable MVP with explicit technical and product boundaries.
- Reviewing a large structured workout-content library and identifying its consistency, delivery and maintainability requirements.

## Η λύση

- Mapped the existing application architecture, routes, modules and external integrations to establish an evidence-based baseline.
- Audited the Strength, Cardio, Nutrition and Recovery workflows, separating calculators, deterministic rules and statistical features from generative AI.
- Defined production acceptance criteria covering identity, user isolation, subscriptions, module persistence, exports and operational quality.
- Sequenced the remediation work so security and data integrity are addressed before any further feature work.
- Established an MVP product model, and criteria for deciding when a feature can be called production-ready.

## Στοιχεία

- **team:** Advisory engagement
- **status:** In development

## Τεχνολογίες

- React
- Vite
- React Router
- Supabase
- Clerk
- Stripe
- Vercel
- Recharts
- jsPDF

## Source notes

This Markdown representation is generated from the same project data used by the DigiMinds case-study page. It does not add performance metrics, client claims, or outcomes that are not present in the project source.