Transforming

Transforming

OrthoFX

through AI Powered

through AI

OrthoFX

through AI

Image Detection to improve Patient Compliance

Image Detection to improve Patient Compliance

Client

Client

Restocq

Restocq

Technology

Technology

iOS, Flutter, YOLOv11

iOS, Flutter, YOLOv11

Introduction

Introduction

OrthoFX is a global clear aligner provider delivering comprehensive orthodontic treatments through a digitally driven workflow. With a growing patient base seeking convenience, remote care, and fewer in-clinic visits, OrthoFX required a scalable way to monitor treatment progress without compromising clinical accuracy.


FXOnTrack was introduced as an AI-powered remote monitoring platform that enables doctors to track patient aligner progress from home, proactively detect off-track cases, and intervene early—reducing unnecessary visits while improving treatment adherence.

“OrthoFX is adopting an AI first practice to improve patient compliance and remote monitoring.”

“OrthoFX is adopting an AI first practice to improve patient compliance and remote monitoring.”

The Challenge

The Challenge

Clear aligner treatments require continuous monitoring to ensure tooth movement stays on track. However, traditional in-clinic checkups create multiple challenges:

  • Low patient compliance or delayed check-ins leading to undetected treatment deviations

  • High operational and logistical overhead for clinics

  • Limited scalability due to frequent in-person visits

  • Reduced clinic efficiency caused by blocked schedules and staff dependency

Without early detection, off-track cases often result in mid-course corrections, extended treatment timelines, or failures.

Our Approach

Our Approach

We designed FXOnTrack as a mobile AI-led platform where clinical accuracy and patient convenience were equally critical.

Discovery and validation were conducted in close collaboration with multiple OrthoFX teams.


Onsite engagement was used selectively during phases where clinical workflows and accuracy required direct feedback. AI proof-of-concepts were executed within controlled discovery windows to ensure feasibility before full-scale implementation.


The solution was delivered through phased execution, avoiding uncontrolled scope expansion while maintaining milestone-driven progress.

We approached Restocq as more than a procurement tool — it was designed as an system that continuously learns from usage, purchasing patterns, and supplier data.


By combining automation with AI-driven insights, the goal was to reduce manual effort, standardize product data across suppliers, and support smarter purchasing decisions. Feature development was guided by customer feedback and real operational priorities, ensuring the platform remained stable while continuously improving the user experience.


Close collaboration between the technology and operations teams, supported by regular stakeholder engagement, ensured rapid issue resolution and alignment with real-world workflows.

Implementation

Implementation

FXOnTrack was implemented through a phased execution model covering discovery, build, AI validation, and rollout. The platform was designed as a mobile-first solution, enabling patients to upload progress photos from home while providing clinicians with a dedicated portal for review and oversight. 


AI-powered computer vision models compare uploaded images to automatically detect the quality of images submitted towards the end medical doctor. 


When potential issues are identified, clinicians can intervene remotely, including issuing corrective actions or rescue aligners without requiring a full in-clinic visit. This integrated approach reduces operational overhead, improves compliance, and maintains treatment quality while minimizing unnecessary appointment

Restocq was delivered through a phased execution model spanning discovery, build, AI validation, and rollout.


The platform includes:


  • Centralized ordering across multiple suppliers

  • Real-time inventory management with intelligent reordering

  • Budgeting, spend tracking, and alerts

  • Multi-user access with role-based controls

  • Supplier management and price comparison


AI capabilities were embedded across the platform, including recommendation engines, demand forecasting, price optimization, and NLP-driven data correction and product categorization.

Impact

Impact

FXOnTrack is actively improving orthodontic care delivery by reducing unnecessary clinic visits while maintaining high treatment accuracy.


Clinics are identifying off-track cases earlier, improving compliance, and minimizing treatment failures or mid-course corrections. Patients benefit from convenience, reduced travel, and faster interventions, while providers gain increased capacity and operational efficiency.

Conclusion

Conclusion

FXOnTrack demonstrates how AI-driven remote monitoring can reshape orthodontic care at scale.


By combining mobile accessibility, computer vision, and clinician-led oversight, OrthoFX is enabling proactive, data-backed treatment management that improves outcomes for patients while unlocking efficiency and scalability for providers.


This is the future of orthodontic monitoring remote, intelligent and clinically reliable.


What we did?

What we did?

UX Design

AI & ML Imaging

AI & ML Imaging

Development

Image Detection Engine

Image Classification

Web, responisve

Image Classification

Image Detection Engine

What we did?

AI & ML Imaging

Image Detection Engine

Image Classification

UX Design

Mobile App Development

Shaping Smarter

Shaping Smarter

Dental Practices

Dental Practices

Together.

Together.

AI Adaptive

AI Adaptive

Connected

Connected

Scalable

Scalable

The complete solution for modern dental practices. Streamline operations, enhance patient care and grow your practice.

The complete solution for modern dental practices. Streamline operations, enhance patient care, and grow your practice.

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© 2026 CuroTwin. All rights reserved.

© 2026 CuroTwin. All rights reserved.

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