Ativafit AI
Ativafit AI provides a movement intelligence layer for physical therapy, capturing objective data like repetitions and range of motion during rehab exercises. The platform converts this data into documentation-ready outputs and tracks progress over time, reducing documentation friction for clinicians. It is initially deployed in fitness-forward orthopedic settings to validate workflow fit.
- Healthcare Technology
- Digital Health
- Artificial Intelligence
- Software Only
- Data & Analytics
Funding
Founders
Founder details are not available yet.
Product
Problem
Physical therapists observe clinically meaningful movement signals every day—range of motion, repetitions, fatigue, pain response, compensation, and progress—but these signals are typically captured through manual observation and patient self-reporting. The EMR may record the visit; the clinical note may summarize the session; but the movement itself is often not structured as usable data. This creates documentation friction and limits the ability to track recovery consistently over time.
Solution
Ativafit AI is building a movement intelligence layer for physical therapy workflows that helps clinicians capture objective movement data during rehab exercises and translate it into usable documentation and progress insight. The platform captures structured movement metrics including repetitions, range of motion, and patient-reported pain or exertion response, then converts these into documentation-ready Objective outputs that clinicians can review and edit. It also tracks movement evidence over time to support clearer patient progress conversations and consistent recovery monitoring. The tool is designed to fit into existing PT workflows rather than replacing clinical judgment or the EMR.
Target Audience
Primary users are physical therapists, particularly those in fitness-forward orthopedic settings, who need objective movement data to reduce documentation friction and track patient recovery more consistently.
Features
- Objective capture of movement metrics during rehab exercises, including repetitions and range of motion
- Integration of patient-reported pain and exertion response alongside quantitative movement data
- Documentation-ready Objective outputs that clinicians can review, edit, and use in existing workflows
- Progress tracking over time to support recovery monitoring and patient conversations
- Focused deployment in fitness-forward orthopedic physical therapy environments to validate workflow fit before broader expansion