Case study · Fitness and muscular therapy
True Motion AI Chat Bot.
A custom AI-powered web application for generating personalized, print-ready corrective exercise programs with complete consistency.
- What we built
- AI-powered web app for corrective exercise programs
- Stack
- Next.js, OpenAI API
- Services
- Web appAI assistantExcel generation
About the project
What is True Motion AI Chat Bot?
The studio was launching a new corrective-exercise service and required a reliable system to translate client intake data and movement assessments into structured programs. Their existing solution, based on a generic Custom GPT, produced inconsistent outputs, especially in Excel formatting, which disrupted trainer workflows and reduced confidence in client-facing materials. The objective was to develop a studio-specific Custom GPT platform that combines AI-driven recommendations with deterministic output rules, ensuring every program is professional, editable, and printable on a single page, every time.
Project scope
The aim of this project was to build a studio-specific Custom GPT platform that combines AI-driven exercise recommendations with deterministic output rules. The project included building a chat-style interface, server-side Excel generation, equipment management, trainer customization workflows, and persistent program history. Both the AI logic and export layers were crafted to ensure reliability and professional quality.
Transforming AI into a dependable daily tool
This project shows how custom AI solutions outperform generic AI tools when reliability, formatting precision, and professional standards are critical. By combining AI-driven decision-making with deterministic output generation and trainer-controlled customization, the platform delivers consistent, print-ready corrective exercise programs.
The problem
What was slowing them down.
- 01
Inconsistent AI outputs
Generic tools produced different layouts and formats on each generation.
- 02
Excel formatting issues
Programs frequently broke across multiple pages or required manual correction before printing.
- 03
Limited trainer control
Trainers could not easily adjust exercise count, equipment usage, or progression logic.
- 04
Equipment constraints not enforced
Studio-specific equipment rules were often violated by generic AI tools.
- 05
No program history
Previously generated programs were not stored for reuse or reference, increasing manual effort.
The solution
What we built.
Phase 1: AI Program Generation
We developed a custom Next.js web application that functions as a controlled, studio-specific AI assistant rather than a general-purpose chatbot. AI handles recommendations while trainers retain full control over final outputs.
- Custom GPT interface: studio-specific AI assistant tailored for corrective exercise programming.
- AI-driven generation: uses client intake and movement assessment data to generate programs.
- Preview & confirm: trainer reviews and customizes AI output before final export.
- Equipment enforcement: hard constraints ensure studio-specific equipment rules are never violated.
- Program history: all generated programs stored for reuse and client reference.
Phase 2: Output & Delivery
- Deterministic Excel: server-side generation with fixed print rules, always one page, Letter, Landscape.
- Natural language edits: trainers customize exercises, equipment, and pacing using conversational input.
- Print-ready output: every program is professional, editable, and prints perfectly every time.
- Client data parsing: intake data automatically parsed and structured for AI processing.
- Equipment management: non-negotiable studio equipment constraints applied to every program.
- Scalable architecture: clear separation between AI logic, UI, and export layers for future expansion.
Results
What changed.
Results & Impact
100% consistent Excel outputs
Every program prints on one page — Letter size, Landscape orientation, every time.
Major reduction in manual work
Eliminated manual formatting and corrections that previously slowed down sessions.
Faster program creation
Higher confidence in quality with trainers refining programs without restarting.
Improved client experience
Clean, professional program sheets standardized across all trainers.
Scalable foundation
Architecture supports future client-facing features and multi-studio expansion.
Increased trust in AI
AI-assisted programming without sacrificing trainer control or quality standards.
Key challenges
The hard parts, and how we solved them.
AI output consistency
AI was limited to content generation while all layout and formatting were handled server-side with deterministic rules.
Print-perfect Excel requirements
Excel files generated programmatically with enforced page size, orientation, and scaling — always one page.
Equipment rule enforcement
Studio-specific equipment constraints implemented as non-negotiable logic that AI cannot override.
Trainer control vs automation
A preview-and-edit step balanced AI efficiency with human oversight, giving trainers final say.
Future scalability
Clear separation between AI logic, UI, and export layers enables future expansion without rework.
Tech stack
What it runs on.
- Frontend
- Next.js
- Backend & AI
- OpenAI API
- Authentication
- NextAuth.js
- Data & File Generation
- ExcelJSDatabase (program history)
Process
How we got there.
01Trainer Workflow
Login · Upload Data · Review Preview
02System Processing
Parse Intake · AI Generate · Apply Rules
03Output & Export
Confirm · Download Excel · Save History
Design
Typography and colour.
Typeface
Poppins
Poppins was selected for the interface to achieve a clean, approachable aesthetic suited for a professional healthcare application. Its geometric proportions bring clarity to the UI, while its versatile weights ensure consistency and readability across the chat interface and program previews.
Colour palette
Teal
#00A3AF
Light Teal
#F0F8F9
Muted
#606060
Dark
#1A2023
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