Skip to main content

Recovered Project

The Recovered project provides AI-powered analysis of wellbeing check-in data through a three-phase architecture that transforms raw user data into actionable insights.

What is Recovered?​

Recovered is a wellbeing tracking application that captures:

  • Emotional check-ins (mood, feelings, notes)
  • Stress levels (daily stress ratings)
  • Sleep quality (sleep patterns, disturbances)
  • Energy levels (0-10 scale)
  • Cycle tracking (physical, emotional, behavioral symptoms)
  • Habits & routines (water intake, reading, exercise, etc.)

Architecture​

The Recovered analysis pipeline uses a three-phase workflow:

Phase 1: Normalize    Phase 2: Reasoning Engine    Phase 3: Business Logic
Raw Export Data  →   Canonical Format    →    Analysis Results   →   Dashboard Output
(Small/Large)        (series, datasets)         (insights, trends)     (formatted JSON)

Phase 1: Normalization (Intake Adapters)​

Transforms raw Recovered exports into a canonical format that the reasoning engine understands.

Phase 2: Reasoning Engine​

Executes multi-agent analysis pipeline (temporal, pattern, correlation, domain knowledge, explanation, validation).

Phase 3: Business Logic (Output Adapters)​

Applies Recovered-specific formatting for dashboard consumption, including headline generation and confidence scoring.

Key Features​

  • Format-agnostic input: Accepts both raw exports (Small/Large format) and preprocessed canonical JSON
  • Multi-agent analysis: 8 specialized agents analyze different aspects of wellbeing data
  • Domain-aware insights: Incorporates health knowledge about stress, sleep, cycles, and energy
  • Adaptive narratives: Generates explanations tailored to the user's question
  • Confidence scoring: Validates findings and flags low-confidence results

Quick Start​

Using the Workflow UI​

  1. Navigate to: http://localhost:4111/workflows/recoveredAnalysisWorkflow/graph
  2. Paste your JSON data (raw export or preprocessed)
  3. Enter your question: e.g., "How have I been doing?"
  4. Click Run
  5. View the narrative output and insights

Supported Input Formats​

Raw Small Format (from Recovered export):

[
  {
    "Created At": "2025-12-12T08:32",
    "Label": "emotion-checkin",
    "Value": "{\"options\":[\"depressed\"],\"date\":\"2025-12-12T08:32\"}",
    "Kind": "emotion-checkin"
  }
]

Preprocessed Canonical Format:

{
  "objective": "Analyze my stress patterns",
  "series": [...],
  "datasets": [...],
  "compactedRows": [...]
}

Documentation Structure​

Reasoning Engine

Learn how adapters, normalization, and multi-agent analysis work

Workflow Guide

Understand the three-phase pipeline and workflow structure

Database

Schema, persistence, and query patterns

Admin Tools

Configuration and management