How to Develop an App like Acloset- AI Fashion Assistant for Everyone
Outfit planning is a real headache for many. Still, how you dress up is a huge part of how you present yourself. No, it’s not all about what’s trending. But fashion is more about ease, comfort, and self-expression. Even Gianni Versace said, “Don’t be into trends. Don’t make fashion own you, but you decide what you are, what you want to express by the way you dress and the way to live.”
If you believe in anything near this, creating an AI fashion assistant for every type of human will be a play for you. With AI, people can now actually assemble their outfits on their devices. They can virtually plan outfits for various occasions. Currently, people use an app like Acloset for these purposes. Still, they cannot deliver the needs of every type of person. That’s why your idea of AI fashion assistant development can be a hit. With the right level of customization, you can gain a huge user base and cater to wider needs. That said, jump into the blog to understand how you can develop such a revolutionary app easily. Dive in to explore!
- Acloset is an AI fashion assistant app that simplifies managing your clothes virtually.
- Besides convincing market stats, there are functionality-based loopholes in the existing AI fashion assistant apps that make your investment in building this platform a lucrative idea.
- Enhanced personalization, adding fashion diversity, and other features can help you outperform the current top-performing wardrobe apps.
- Ensure you have shortlisted an expert app development company like Matellio to have a successful AI fashion assistant app development.
Table of Contents
It’s an AI fashion assistant app that simplifies managing your clothes virtually. Acloset is one of the most popular apps under this category. It’s available both on Android and iOS. Using AI, it can create stylish looks based on various factors, including the weather.
With this app, users can browse through their wardrobes and see how different clothing items can be styled. It also has a search feature. Users can search for outfits based on categories like brands, body types, or occasions.
The highlight of Acloset is that it makes users wear all their clothes proportionately. It shows recently worn items, so users don’t frequently repeat outfits. Plus, it tracks which outfit they did not wear in a while. While suggesting outfits, it highlights the colors, brands, and clothing items users prefer the most. This way, it helps them manage their fashion preferences.
Why Invest in AI Fashion Assistant App Development?
Besides these market stats, there are functionality-based loopholes in the existing AI fashion assistant apps. These two factors make your idea of investing in such a platform lucrative. Many people are looking forward to more advanced tools that can take all their worries about what to wear. If you want to cater to this need, go through the next section.
Make Your AI Fashion Assistant App Development Stand Out with These Features
We’ve assessed the features of the top apps falling into this category. Based on our findings, you stand a good chance of outperforming these apps. But for this, you’ll have to ensure you add the following advanced features.
Think of building an AI fashion assistant app like building your user’s fashion companion. Choose an AI development company that can specifically design AI algorithms for your platform. Why is this necessary? Your app should truly be a personalized experience for users. And for this, it should learn and adapt to individual user preferences over time. Then, it should be able to analyze user feedback, outfit choices, and fashion history. All these factors will empower your platform to understand each user’s unique style and offer recommendations that perfectly align with their preferences.
Emphasis on Fashion Diversity
Fashion is a vibrant and diverse world. Make your app celebrate this beauty. Consider integrating a wide range of styles, designers, and trends. Show your users you respect all diverse preferences and do not promote only mainstream fashion. For this, you will have to ask your vendor to go beyond the ordinary. Ask them to make your app recommend unique and lesser-known styles to users. Doing this will make your platform look progressive. People could explore new fashion ideas, expand their horizons, and express their individuality in exciting ways.
Emotional Intelligence Integration
Emotions have a significant impact on one’s fashion choices. And most AI fashion assistant apps miss this aspect. You can take advantage of this loophole by introducing emotional intelligence. An emotionally smart app could tailor recommendations considering factors like mood, desired aesthetic, etc. Ultimately, your users will feel confident and empowered in their fashion choices. The chances of them making your app a staple will also increase.
You obviously want your AI fashion assistant app to be the true fashion advisor for your users. But without contextual clarity, this goal will always remain far. That’s why you should consider multiple contextual factors that influence outfit choices. It’s like giving a map to a smart app so that it can paint a bigger picture. So some of the factors that you can consider for your app to assess could be:
- Existing wardrobe
- Weather conditions
- Cultural sensitivities
- Occasion-specific requirements, etc.
Having these contextual insights, you could provide practical and suitable recommendations. These recommendations will align with the user’s specific circumstances and ensure they wear what’s best for their situation.
Interactive User Interface
Want to hook the user leaving a lasting impression? Ensure your AI fashion assistant app has an interactive user interface. It’s literally the face of your app. So everything from colors to text should resonate with your underlying idea of creating that platform. When we come to interaction, let users provide feedback on recommended outfits. Don’t make the conversation one-sided but create a valuable feedback loop. This continuous interaction will help the algorithm to understand the user’s preferences and refine its recommendations over time.
That’s not all. You can also allow users to fine-tune suggestions. Enable them to tweak parameters like color preferences or specific item exclusions. This level of control through the interface will ensure a truly personalized and collaborative experience.
Integration with Virtual Try-On Technology
Yes, this feature already exists among many AI fashion assistant apps. But most of them lack that immersive experience this feature is supposed to provide. So, while creating the app, ensure the virtual try-on experience is more life-like for users. Also, the visualization should be of high quality, clearly showcasing users how different outfits would look on them. Adding this feature, harnessing the full power of AI and digital transformation services will leave no room for guesswork. It will boost users’ confidence in their choices and improve their fashion sense.
Continuous Learning and Improvement
AI models need continuous learning and improvement. So if you want to leverage user interactions and keep up with the trends, keep refining your platform’s automated recommendations. For this, you and your development partner should consistently analyze user data and trends to stay at the forefront of evolving fashion preferences. Your proactive approach will not go in vain. It will result in maintaining an updated app that offers relevant suggestions. This way, you can deliver a platform that has the potential to become an indispensable part of the fashion journey, even for the people least interested in styling.
AI Fashion Assistant Development: Key Steps
Before starting the process, we have a quick heads-up for you. Ensure you have shortlisted an expert mobile app development company. Trust the process but trust this prerequisite even more for a smooth development sail. That said, dive into these key development steps to create an advanced fashion assistant app.
Research and Planning
Here you have to brainstorm with your team. Bring all the ideas to a single table. Make your team research and plan together. When you have your preferences ready, go straight to your selected vendor. Seek their expert guidance to answer questions like:
- Who is your target audience?
- What are their pain points?
- What AI technologies and data sources can power the app?
- What will be the basic and advanced features?
- What will be the project timeline? etc.
Once you’re done with the planning with all the stakeholders, it’s time to focus on design. Here, you have to finalize the following:
- User flows
- Visual design
Therefore, you have to collaborate with UI/UX designers to craft an intuitive and visually appealing interface. Ensure the design aligns with your brand identity and provides a seamless user experience.
Now comes the real action time! During core AI fashion assistant app development, you select and finalize the integration of AI technologies. Some of the key options you shouldn’t miss are:
- Machine learning models for fashion trend analysis
- Recommendation engines for automated suggestions
- Natural language processing for user interactions
- Cloud integration services for user data management and sharing
Besides this, observe the below-given table for the tech stack. It will give you an idea about the best tech options you will have when you reach this step.
|Front-end Framework||React, Angular|
|AI and ML Frameworks||TensorFlow, Keras, PyTorch, Scikit-learn|
|Natural Language Processing||NLTK, SpaCy, Gensim|
|Recommendation Engine||Collaborative Filtering, Content-Based Filtering|
|Cloud Computing||Amazon Web Services (AWS), Google Cloud Platform (GCP)|
|Testing Frameworks||Selenium, JUnit, pytest|
|Data Processing||Pandas, NumPy, Scikit-learn|
|Data Visualization||Matplotlib, Plotly, D3.js|
|Version Control||Git, GitHub, Bitbucket|
|API Development||RESTful APIs, GraphQL|
|Testing Frameworks||PyTest, Selenium, Jest|
This is one of the most important steps during AI fashion assistant app development. Why? Because the platform will need continuous access to relevant and up-to-date fashion data. And for this, the integration with various data sources is crucial. These sources could be:
- APIs from fashion retailers
- Fashion catalogs
- Social media data
- User-generated content
The smart algorithms will then aggregate and analyze the collected data themselves. Finally, your app will become all set to provide accurate and real-time fashion insights to users.
Building an MVP
By this step, you will have a final prototype of your app. So, it’s best to launch this form of your app as an MVP (Minimum Viable Product). Reason? It will help you market your app quickly and gather user feedback.
Remember that the MVP focuses on implementing the core functionalities of the app. In the case of an AI-based wardrobe or fashion app, the key functionalities could be fashion trend analysis, basic recommendation features, etc. Hopefully, if all goes right, the MVP will help you validate your app’s concept, gather user feedback, and make iterative improvements based on market response.
Testing and Quality Assurance
Rigorous testing and quality assurance are essential to ensure your AI fashion assistant app functions reliably across different devices and platforms. Whether you choose iOS, Android, or both, this step is inevitable. Your team can run various types of tests, such as functional, performance, or user acceptance, to become sure that your app is up to your expectations. Moreover, rigorous testing will also help them find and fix potential bugs and issues.
It’s time to give the final touch to your wardrobe app. Assess the user feedback and market insights you’ve collected so far. Now decide what features should be added, removed, tweaked, etc. You can also fine-tune the accuracy of recommendations the platform provides and pay attention to other usability issues. The goal of taking these measures is to ensure it’s working at the best level and catering to user needs and market demands.
Deployment and Launch
Once the AI fashion assistant app meets your expectations and has undergone thorough testing, it’s all set for deployment. Launch the app to the desired platforms, such as mobile app stores or web platforms. Initiate marketing to create awareness and drive user adoption.
Ongoing Maintenance and Updates
After the app’s launch, regular maintenance ensures a smooth flow of incorporating new AI advancements, fashion trends, addressing issues, etc. Make it a practice to monitor user feedback and data analytics continuously. It will help you make data-driven decisions for further enhancements and improvements to your app.
So, that was all about AI fashion app development. Still, this was just a glance. You can gain a detailed picture only when you partner with a seasoned team of experts. And here is a brownie point for you: choose an experienced and professional company. Why? Though the reason can be countless, some major convincing reasons are:
- Proven Track Record – While freelancers can be novices, companies with previous records can never make silly mistakes with your project.
- AI Expertise – Again, new companies may prove to be unreliable with advanced technologies. That would not be the case with a company having expertise in next-gen technologies.
- Cost-Effective – This is one of the major reasons why you should opt for industry experts only. Partnering with them will be just a one-time investment. Then no overspending on repetitive bugs and AI model training. All will be taken care of by the experts.
Excited already? Stop your chase for an expert vendor by partnering with Matellio. We can be your one-stop solution for all your software development needs involving legacy and next-gen technologies. Whether it’s cloud integration, enterprise solutions, machine learning solutions, you name it! We’re here to help. So what are you waiting for? Get started to create your dream AI fashion app now!
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