FitWithPari

    Long Profile Assessment Automation – FitWithPari

    An AI + RAG-powered system that transforms raw assessments into detailed fitness intelligence.

    Problem Statement

    FitWithPari works with students across yoga, pilates, strength training, conditioning, and hybrid fitness programs. Each student completes long onboarding and assessment forms that contain: Experience levels across multiple fitness domains, Medical conditions, Movement limitations, Numeric test results, Multi-step physical assessments, Coach notes and improvement directions. Earlier, coaches had to manually read through every response, rewrite fitness summaries, combine new and old results, and maintain separate documents for each student. This led to: Hours of manual processing, Inconsistent summaries, Lost progress history, Mistakes when merging old and new assessments, Coaches spending time on admin instead of coaching. FitWithPari needed an intelligent system that could automatically convert raw form inputs into meaningful, structured, and long-term fitness profiles.

    The Solution

    Automation Overview

    We built a complete AI-driven assessment system that turns onboarding and assessment responses into a detailed long fitness profile using RAG + Supabase + n8n. The system merges old and new assessments, processes coach notes, analyzes test results, and generates a comprehensive, personalized fitness summary — completely automatically.

    Full Onboarding & Assessment Data Extraction

    The system captures every response from FitWithPari’s long assessment forms, including: Numeric test scores, Multi-select capability data, Text-based explanations, Coach notes, Improvement areas, Limitations, Schedule, goals, and experience. Every field is cleaned and normalized before processing.

    Smart Data Interpretation

    The automation understands different field types: Numeric → test scores, Text → explanations, Multi-select → categories, Ternary → yes/no/maybe, Coach notes → qualitative insights. It builds a fully structured tests[] object automatically.

    Seamless Merging of Old + New Profiles

    The system retrieves: Previous long profile, Past assessment results, Coach notes, Improvement histories. Then merges everything cleanly with the new assessment to maintain long-term student progress.

    RAG-Powered AI Profile Generation

    A custom Retrieval-Augmented Generation (RAG) agent powers the long summary. Using the knowledge base trained on: Fitness evaluation frameworks, PT methodology, Movement patterns, Posture issues, Strength/stability scoring. The agent produces a long, detailed fitness profile for each student. This includes: Posture & movement analysis, Strength/stability breakdown, Mobility issues, Progress changes compared to older assessments, Improvement directions, High-priority recommendations, Safety flags, Personalized next steps. Every summary is human-readable and coaching-ready.

    Coach Notes Syncing

    Coaches add: Focus areas, Improvement notes, Training priorities. The system automatically merges these into the new long profile, ensuring nothing is lost.

    Clean Supabase Sync

    The final structured output is stored in two places: Long profile table → full JSON structure + long summary, Short profile table → fast-access summary (for sessions). Both stay constantly updated as students complete new assessments.

    Integrations & Connected Systems

    n8n – Core logic, parsing, merging, processing; RAG AI Agent – Long profile generation; Supabase – Storage for long & short profiles; FitWithPari assessment forms – Input source; Custom knowledge base – Fitness and movement reference context.

    Smart Logic & Reliability

    • Detects incomplete assessments
    • Handles null / missing fields gracefully
    • Normalizes all test names
    • Auto-merges legacy data with new assessments
    • Ensures coach notes never get overwritten
    • Produces clean JSON outputs for downstream use
    • Guarantees stable database syncing
    • This system is built for long-term coaching operations

    Before

    Coaches spent hours reading assessments, writing long summaries, merging old data, and organizing notes manually.

    After

    Every student gets an accurate, detailed long fitness profile automatically — complete with progress tracking, insights, and recommendations — in seconds.

    Tools Used

    n8n
    Supabase
    RAG AI Model
    Custom knowledge base
    Assessment form data parser
    Data normalizer and validator

    Our Process

    1

    Discover

    Understood the full assessment flow and pain points of manual evaluation.

    2

    Design

    Built the RAG architecture and structured long-profile schema.

    3

    Build

    Implemented onboarding data extraction, merging, and profile generation.

    4

    Integrate

    Synced Supabase with long/short profile systems.

    5

    Deploy

    Tuned the AI agent, ensured stable outputs, fixed missing field issues, and optimized speed.

    Business Impact

    Hours of manual assessment time saved per student

    Zero data loss across assessment cycles

    Clean, structured long-term progress tracking

    AI-generated fitness insights aligned with coaching logic

    Consistent profile quality across all coaches

    Scalable system for thousands of student assessments

    "This automation gives FitWithPari a powerful end-to-end system for handling long fitness assessments. With AI-driven summaries, profile merging, structured data storage, and RAG-powered insights, the platform now delivers accurate, high-quality profiles instantly — helping coaches focus on what matters most: training their students."

    Want a system like this for your business?

    Let’s build it.