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Bynálix

Local-first personal health analytics platform. Bynálix is designed for long-term self-observation, not engagement optimization. Track, observe, and analyze your own long-term behavioral data — without relying on opaque cloud AI systems.


Philosophy

Bynálix is not designed to tell users how to live.

Instead, it helps users:

  • Record long-term personal data
  • Observe behavioral patterns
  • Explore correlations
  • Understand what actually affects them

The goal is not blind optimization, but deeper personal understanding through self-owned data.


Features

Tracking

  • Food — meals built from a searchable food library, custom meal types, reusable meal templates and saved favourite meals; a custom-food editor storing nutrition against a base quantity and unit (100 g by default) that any logged amount scales from, and drinks logged in ml can count toward the day's water automatically; category and aggregate tag filters (starch / protein / fat / favourites) with paging
  • Exercise — strength logged as sets × reps × weight by body part; interval-based cardio (running, swimming, cycling) with distance, duration and pace; other activities by duration and intensity. Calorie burn is estimated from lean body mass where body fat is known, and from body weight otherwise
  • Body — weight, body fat, skeletal muscle with segmental distribution, body water, visceral fat level, waist
  • Sleep — duration, quality and notes, with automatic detection of the overnight sleep window from screen activity on Android
  • Water — daily intake against a hydration goal

Goals

  • Eight modes — three cut rates, three bulk rates, maintenance, and fully custom
  • Calorie and macronutrient targets derived from BMR, NEAT and TDEE (Mifflin-St Jeor, or Katch-McArdle once body fat is known). Lean body mass is stored from a measured body-fat reading rather than drifting with day-to-day weight
  • Custom mode adds a free-form goal metric — any strength, cardio, body, diet or burn measure — with up to five variables scored against it

Analysis

  • History — weight, calories, macros, water, sleep, strength volume, per-exercise max, exercise distribution, activity burn and body composition over any range, with optional trend-line fitting and slope per week
  • Correlation — an influence ranking against your goal, plus a variable relationship network built on day-over-day changes (Spearman) with a 0–3 day lag search, so a shared trend cannot manufacture a link
  • Patterns — weekend-vs-weekday effects, significance gated; and relationship changes, which tells a link that has always held apart from one that measurably started partway through the record
  • Stability — a seven-axis star chart scoring how little weight, calories, the three macros, water and sleep wobble day to day, independent of any long-term trend
  • Every result carries its sample size and data density, and says "not enough data" rather than showing a number it cannot stand behind

Output

  • Any chart can be saved as an image, stamped with the export date
  • Encrypted CSV export of every table (AES-256 ZIP)
  • Full database export and import, for backup or moving to another device

Privacy & platform

  • Local-first — SQLite on your own device. No account, no server, no telemetry
  • Works fully offline
  • App lock with a password, plus biometric unlock on Android
  • Android, Windows, macOS, and an unsigned iOS build for sideloading
  • English and 繁體中文 throughout

Changelog

Full history: CHANGELOG.md · 繁體中文

Latest — v1.6.3

  • Same-day correlations between derived quantities (calories vs macros, burn vs duration) are no longer drawn — they measure arithmetic, not behaviour
  • Network edges are routed around the nodes they don't connect, instead of passing underneath them
  • Exported images no longer mis-place small text; on Android they now appear in the gallery

Why Bynálix Exists

Bynálix was created to help users verify ideas using their own long-term data, instead of relying entirely on generalized internet advice.


Correlation Analysis

Correlation does not imply causation. Bynálix provides exploratory analytics designed to help users observe potential behavioral patterns over time.


Privacy & Ownership

  • No cloud account required
  • No data collection
  • No ads
  • Your data belongs to you
  • Optional app lock (PIN / biometric)
  • SQLite database export supported
  • Local backup & restore supported

Development Environment Requirements

Tool Version
Node.js 18+
Rust stable
JDK 21 (required for Android builds; JDK 25 is not supported)
Android SDK API 24+
NDK r27

Technical Architecture

  • Frontend: React 18 + TypeScript + Tailwind CSS + Vite
  • Backend: Tauri v2 (Rust)
  • Database: SQLite (@tauri-apps/plugin-sql)
  • Platform detection: src/lib/platform.ts
  • Internationalization: src/lib/i18n.ts

Installation

Download the latest build from the Releases page:

Android

  • Download the APK from Releases
  • Install via sideloading

Windows

  • Download the .exe installer

macOS

  • Download the universal .dmg

iOS

  • An unsigned .ipa is published for sideloading when the build succeeds

Roadmap

Bynálix stays focused on local-first, long-term self-observation.

Short term:

  • UI and performance refinement
  • Core data flow and stability

Medium term:

  • Stronger visualization and interaction

Long term:

  • Fuller personal data export and migration
  • Additional languages and cross-platform polish
  • Database-at-rest encryption (SQLCipher, key derived from PIN / biometric)

License

Bynálix is open source under the Apache License 2.0.

You are free to use, modify, and distribute this software for any purpose, including commercial use, subject to the terms of the Apache 2.0 license.

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Local-first personal health analytics platform. Bynálix is designed for long-term self-observation, not engagement optimization. Track, observe, and analyze your own long-term behavioral data — without relying on opaque cloud AI systems.

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