‣ Standardized Imaging Framework Coordinate-based positioning ensures consistent scalp capture across sessions and operators.
STYLE AI PRO advances scalp and haircare management through AI, 3D modeling, and intelligent automation — transforming experience-based consultation into measurable service workflows. Designed to reduce dependency on individual expertise and enable scalable, operator-independent service delivery.
Starting with standardized data capture, we are building a structured and repeatable service system that empowers salons and medical institutions to upgrade service quality and lifecycle management. At its core, STYLE AI PRO is building a long-term scalp data infrastructure rather than a single-point diagnostic tool.
‣ Standardized Imaging Framework Coordinate-based positioning ensures consistent scalp capture across sessions and operators.
‣ Automated Indicator Quantification Transforms captured images into measurable scalp indicators using AI-driven analysis.
‣ Guided Consultation Workflow Integrates structured prompts and standardized reporting into daily service operations.
‣ Centralized Record & Trend Management Consolidates client history, session comparisons, and cross-location data visibility. Centralized Data Management.
A closed-loop workflow connecting data capture, AI-powered analysis, and operator-independent service execution.
Data Synchronization
“AI-driven longitudinal scalp analysis for condition tracking and personalized recommendations.”
Insights / Recommendations
To provide advanced scalp and hair understanding that helps make smarter haircare decisions and improve overall wellness.
Full scalp and hair imaging for accurate analysis and tracking.
AI-powered analysis with professional reports and deepest insights.
Anyone can promise results — we deliver proof.
Contact-based scalp scanning system captures high-fidelity, real-world head and scalp geometry for data-driven styling and personalization. In a fast, automated workflow, it collects dense measurement points and fuses them with facial data to generate a complete 3D head model—improving accuracy as more points are added. The result is reliable, “true-to-person” digital data that supports custom-fit products and more precise, repeatable haircut planning.
Multi-function grooming end‑effector combines adjustable dual‑comb modules with an integrated, distance‑controlled clipper to lift, guide, and cut hair with consistent control. Designed for lightweight robotic integration, it supports continuous tool orientation adjustment, flexible positioning (including added-axis motion), and robust, industrial-grade wiring for reliable real‑world operation and repeatable results.
STYLE AI JUNIOR’s Virtual Grid Safety System (VGSS) creates a configurable 3D safety envelope around the client, using layered Safe/Caution/Critical zones to continuously manage robot speed, force, and approach distance. With dynamic scaling, checkpoint-based monitoring, and pre-verified motion control, VGSS helps deliver precise, predictable performance while prioritizing safety throughout every styling workflow.
This role focuses on developing intelligent motion-planning systems that transform raw commands into safe, adaptive, and precise robotic movements. The position contributes to advanced R&D initiatives by building high-speed algorithms capable of operating within complex biological constraints while supporting the company’s strategic innovation goals.
This role focuses on driving commercial growth through market expansion, strategic partnerships, and business development initiatives. The position bridges R&D and market execution by translating technology into business value, supporting client acquisition, and contributing to the company’s growth and fundraising objectives.
Captures standardized scalp and hair condition data. Feeds Data Fusion & Development with a reliable digital baseline for personalization and scalp care tracking.
Transforms scanning insights into guided execution and operational consistency. Supports pre-cut analysis, hairstylist training simulations, and general service tasks.
Applies automation and machine learning to precision styling workflows.
Uses deep learning and outcome-based data to refine parameters and scale repeatable results.
Unifies into a closed-loop ecosystem — combining measurements, actions, and outcomes. Every session improves the next through smarter models and optimized workflows.