FASHINZA LEVERAGING TECHNOLOGY

Summary: The countless obstacles faced by the fashion industry, especially after the pandemic, shed light on how important it is to leverage technology to any brand's advantage. With an impeccable vision and using technology the right way, Fashinza is the new-age platform for all needs!

So, What is Fashinza?

Fashinza is an AI-driven and tech-enabled apparel manufacturing platform for fashion brands, manufacturers, and retailers. It's a B2B marketplace designed to help brands with a unique digitized supply chain.

Fashinza offers end-to-end production visibility to brands, which means brands can track every step of the production process, monitor where their raw materials are sourced from, and verify whether the factories are compliant and ethical. Such transparency and control over the production cycle empower brands, who can build transparent relationships with their customers.

Technology Behind Fashinza that makes it stand out!

ARTIFICIAL INTELLIGIENCE(AI)

The application of AI has been recognized in the F&A industry at various stages such as apparel design, pattern making, forecasting sales production, and supply chain management. 

Fashinza uses AI to drive dynamic supply booking depending on capacity and availability. 

Recently, Fashinza through intelligent quality app software collects and analyses garments inspection data (no of pieces has been Approved, Rejected, or Altered) of factories, where they are manufactured, and at what time, and date of the month. This data is used by Fashinza to predict factory capacity and identify assembly line faults so that we can assign new orders accordingly.

Using predictive analytics, our AI platform provides fashion brands with real-time order updates, including recommendations when their orders are nearing completion and offer aimed at increasing their booking time.

MACHINE LEARNING(ML)

We are also using deep learning and prediction algorithms to offer sustainable supply chain solutions. With the right data and technology, Fashinza believes that people and organizations involved in fashion and lifestyle retail can address difficult problems and transform the world. As such, we’re deploying AI to predict demand patterns and emerging fashion trends. Such data-driven production helps brands with inventory management and improving business impact decisions. Fashinza creates demand forecasts based on customer behavior online.

Fashinza has a team of more than 20 people to supervise the machine learning algorithms which inform every action from designing garments to optimizing logistics.

With further improvements in the AI support systems, our partner brands will have the scope to make more informed decisions about product development, sustainable production, and profit optimization.

Data Led Trendy Collection as per Brand Literature!

Fashinza allows you to get your hands on personalized and customized outfits that are hot selling & trending in the market. It aims to streamline the fashion B2B experience for customers with intelligent garment tags based on data. 

Fashinza allows brands with M2O with trending fashionable designs as a suggestion in our application. Not only is this a great gimmick to drive sales, but it also collects a huge amount of useful data that machine learning algorithms can use to design future products and deliver personalized recommendations for a specific category.

Fashinza uses Google AutoML to power its design and engineering processes, sales, and customer support. Predictive analytics are used to create futuristic trending designs.

Worry no more about your privacy!

We implement multiple procedures to ensure consumer data privacy, which includes:

1. We secure limited access to data.

 Limiting access to data means there are fewer points of vulnerability for the users.  We also have limited employees with access to our customer data, which reduces any risk of internal data abuse. 

2. We Encrypt customers' data using encryption algorithms. Presently we use the AES256 encryption algorithm to encrypt the password & customer-related information.

3. We avoid data silos.

4. We have a strong authentication process in place. To validate brand and supplier logins, we use token-based authentication and OTP. 

We feed ethical principles to our AI systems by identifying existing problems such as biases and privacy concerns. As such, we’ve taken measures to ensure there are no biases such as the ones related to race-based face detection. We also ensure that we’re not capturing any confidential information from our brands and suppliers. The data that is captured from our users, with their consent, is also encrypted to protect their privacy.

Data Collected Ethically

We have a series of procedures in place to ensure that the data we collect from our users is done in an ethical manner. First and foremost, we convey our cookie policies in detail and collect clearly stated consent from the customers. 

Next, while opting for third-party plug-and-play data sets, we ensure that the service provider follows compliance measures and promotes web transparency, they clearly communicate their monitoring methods against illegitimate data, and that they can prove they are GRPR and CCPA compliant while also following all existing laws.

Avoiding Biases from our AI

 AI biases could arise due to a few reasons. The primary ones are,

    (a) Algorithms that are a result of the classification algorithm type selected, or

    (b) Insufficient data or a problem that is not representative enough. These impact the generalization ability of an algorithm.

We try to ensure that such biases resulting from the algorithm can be reduced by making sure we choose an algorithm that does not overfit (eg. an ensemble approach). We also either prioritize the selection of representative data or consider a large dataset covering all possible scenarios. The results are monitored closely.

Fashinza team has a number of ML models deployed for various use cases. The company is continuously developing new ones as well as modifying and improving the existing ones. Depending on the nature of the problem, the models are re-trained at pre-defined frequencies. 

To sum it up, we do not go by the hype of data/ML/AI in choosing our trend forecasting solutions. In both the data and algorithm, we look for bias. Social signals are used only after they have been sufficiently validated. We take great care when reading our own omnichannel data to avoid biases.

Conclusion

If you want to take your business to next level, it's high time fashion brands leverage technology and makes use of it to the fullest. From designing and producing materials to having a one-of-a-kind trend-predicting algorithm, Fashinza promises to reinvent the fashion supply chain that is future-ready!
Reform your business with a brand that makes use of technology wisely, connect with us at fashinza !