iHairium.

iHairium is a mobile application designed to help users assess visible signs of hair loss and receive recommendations for hair and scalp care at home.

The application uses artificial intelligence and neural-network technologies to analyse user-provided visual information. A user can submit a photo or video of the head following the examples provided in the application.

Based on the submitted material, the system provides an assessment and recommendations related to possible ways of improving hair and scalp condition.

iHairium brings AI-assisted hair analysis into an accessible mobile experience focused on early awareness and everyday care.

Hair loss and scalp condition are personal topics that users may prefer to explore privately before consulting a specialist. A mobile application can provide an accessible first step for observing visible changes and learning more about possible care directions.

The main challenge is to make the process simple for users while maintaining a clear distinction between an AI-assisted assessment and a professional medical examination.

iHairium was developed around the idea of combining visual input, machine-learning technology and practical recommendations in one mobile product.

The solution is an iOS application that guides the user through the process of submitting visual information and receiving an AI-generated assessment.

The product was structured around the following principles:

Make hair-loss assessment accessible through a mobile device.

Guide users when taking or submitting a photo or video.

Apply AI and neural-network technology to visual input.

Present the result in an understandable and user-oriented format.

Provide recommendations for everyday hair and scalp care.

Visual user input

Users can provide a photo or video of their head using examples and instructions available in the application. This helps establish a consistent starting point for the analysis process.

AI-assisted assessment

The application uses a neural network to process the submitted visual information and assess visible signs associated with hair loss.

Personalised recommendations

After processing the input, the application provides recommendations related to hair and scalp care at home. The recommendations are intended to support user awareness and everyday care decisions.

Mobile-first experience

The iOS format allows the user to complete the assessment process using a device that is already available in everyday life. This reduces friction and makes repeated observation more convenient.

The user journey begins with a personal concern or interest in the condition of the hair and scalp. The application then guides the user through image capture and submission.

The AI layer transforms visual information into an assessment that can be presented in a clear and understandable way. The final step is a set of recommendations focused on possible care actions at home.

This approach creates a connection between machine-learning technology and a practical consumer experience.

Sparkler Soft developed the iOS application and the digital product experience supporting AI-assisted hair-loss assessment.

The development scope covered the mobile interface, visual-input flow and the application logic required to connect user submissions with assessment and recommendation functionality.

The exact neural-network architecture, training dataset, validation process and server-side implementation are not disclosed in the available project information.

iOS mobile application development.

Photo and video submission flow.

Guidance for capturing visual input.

AI and neural-network integration.

Assessment result presentation.

Hair and scalp care recommendations.

Mobile user experience and product navigation.

The project combines native iOS development with machine-learning and neural-network capabilities. The exact implementation details are not specified in the publicly available project information.

Platform

Native iOS application

AI

Artificial intelligence and neural networks

Input

Photo and video of the user’s head

Analysis

AI-assisted visible hair-loss assessment

Output

Recommendations for hair and scalp care

Integration

Mobile application and ML service layer

AI-powered health and care applications can include mobile interfaces, secure media upload, machine-learning services, backend APIs, user profiles and recommendation systems.

Sparkler Soft develops native mobile applications, backend services, custom APIs, mobile SDKs and integrations with external services. These capabilities provide a foundation for extending products that combine mobile input with AI processing.

Any future version involving personal images, health-related data or medical claims should be designed with appropriate privacy, security, consent and regulatory requirements in mind.

iHairium demonstrates how AI can be applied to a consumer-facing hair-care product and presented through a simple mobile workflow.

The product makes it possible to connect visual user input with personalised recommendations, creating a more relevant experience than generic hair-care content.

From a development perspective, the project demonstrates Sparkler Soft’s ability to combine native mobile development with machine learning, image-based analysis and recommendation-oriented product logic.

AI-powered iOS application.

Neural-network-based visual assessment.

Photo and video user input.

Hair-loss and baldness assessment.

Personalised hair-care recommendations.

Scalp-care guidance for home use.

Machine-learning and mobile technology integration.

The visual used on this page is a conceptual portfolio cover created to represent AI-assisted hair analysis, visual diagnostics and personalised care recommendations.

It is not presented as a direct screenshot of the original iHairium interface. The original project presentation and supplied App Store artwork are included below.

AI hair analysis

Care recommendations