How Zero Code AI is Revolutionizing the Fashion Industry
The fashion industry has never been an aggressive adopter of technology until now. The last few years have re-written most business models with Digital first strategies becoming mainstream. AI is an integral part of this whole transformation.
AI seeks to automate and scale repetitive processes. To build these automations you need qualified data scientists, engineers and domain experts working together. But the supply of data scientists is a lot less than the demand for them. Zero code environments were developed to bridge this gap.
These are platforms that come pre-programmed with multiple models. Domain experts can feed their data to optimize these models for their requirements. It allows a person to build prediction models with almost no knowledge about AI or coding.
Businesses can -
- Automate manual processes
- Automatic tagging and cataloging
- Design collections with AI
- Predict trends and more
For the shopper AI offers
- Personalized shopping experiences
- Intuitive Search
- Recommendations like a professional stylist
- Latest trends
At Streamoid we use AI studio our No code AI platform extensively to build our solutions. With a data-centric approach, we build products with man-machine partnerships. The No code platform enables our Domain specialists who understand fashion to build models to solve their problems.
BUILDING YOUR OWN AI
AI studio platform gives you a dashboard that enables you to manage your experiments with ease. The quality of the model depends on the quality of training data. So, a lot of emphasis and work has gone into identifying the kind of data required, creating training and validation data sets, getting high accuracies with smaller data sets, and so on.
This domain-specific AI system has the intelligence to give data insights and guide the non-technical users to manage biases and the kind of additional data to be added etc. It has got data visualization to enable the stylists to visualize the kind of data inputted in the systems.
Here is how Streamoid has used the AI studio to build solutions for Fashion
AUTOMATED DEEP TAGGING AND CATALOGING
Catalogix, Streamoid’s Hero product has a lot of AI models built into the process. We will discuss a few here:
Category detection: It is critical to identify the right category of Mens, Womens and Kids. You make mistakes here and you lose the trust of your shoppers right off the bat.
Fine Grained classification: Models have been trained to identify the different attributes of a garment. These range from the simple Checks and Stripes to more abstract and difficult aesthetic classifications of Occasions and styles.
Background detection and removal: Identifying the back ground and replacing it without cropping the main images at any point.
Collage generation: Creating outfits into beautiful collages automatically
These are the few AI components that enable us to auto-tag catalog images and convert them into other marketplace and channel Taxonomies. This saves the seller an enormous amount of labor and time.
AI STYLING ENGINE
Streamoid Styling engine has been built in such a way that the stylist can use a simple dashboard and write the algorithms or the step-by-step rules to capture the fundamental aspects of fashion styling. The system understands the hierarchy of data, identifies conflicting rules and brings them up for manual intervention.
This engine powers many of the recommendations such as complementary product pairing, outfit recommendations, Theme based product clustering and so on.
It understands a brands style from its catalog images and recommends accordingly. Given an understanding of local styles in different countries it can curate the same catalog differently for each country. For example, for Russia the outfits will be sexier with stilettoes and for Japan it will be a layered outfits with comfortable footwear.
All the feedback is looped back to AI studio to improve the models on a continuous basis.
Computer vision and AI
Models have been trained to identify multiple fashion products in any image (multi-object detection). Pose estimation to help with predicting the product category. Background occlusion- ignores noisy background. All of these are used to automatically add bounding boxes, identify the category and retrieve similar products from the catalog.
NLP and AI
Natual language models trained on an advanced Taxonomy make search fashion oriented and more intuitive.
These are just some applications of Zero code AI. Trend and price predictions, sentiment analysis, Key word predictions; Automating markdowns and promotions, forecasting models are just some areas that companies are working on today.
Zero code AI is here to stay. With no code involved in the technology, it opens gates of opportunity for people with no technical knowledge. While we have covered examples for fashion the same platform can be used to solve problems in all other industries as well.
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