Yosh.AI designed and implemented a solution which combined visual search with auto-tagging and a recommendation engine.
The chatbot created that way relied on AI solutions and self-learning algorithms to increase the effectiveness of the business and optimize costs.
Visual search, based on advanced, state-of-the-art machine learning methods using neural networks, allows to customer to search for product in an intuitive, fast manner, unencumbered by the constraints of language.
For autotagging, we offer a semi-supervised approach for efficient model training, whose ontologies are based on the latest research articles created in collaboration with the domain specialists. Yosh’s Autotagger, compared to its competition, covers more categories with consistent labelling and offers higher accuracy. It can be tailored towards the client’s needs and is deployed on cloud service for 24/7 availability and autoscaling.
Finally, a predictive recommendation engine feeds on data gathered to provide the most relevant products to the potential customer by making predicitons about future behaviour. AI-based predictions, especially when compared with traditional methods of data gathering, carries online sales to the next level.
Based on this, we were recognized as a pioneer in introducing AI solutions to customer care, which resulted in receiving the …. Award in 20??. We strongly believe that this approach is the future of customer care, and the options and solutions AI offers cannot be overstated or matched by any of the traditional approached or solutions.