about our product

Features:

SHatNEZ Detection:

Using teachable machine image training, Hot-Shatz recognizes the difference between wool and linen through it's unique neural network. The database contains numerous images of wool, linen and cotton under a microscope categorized by type. The program associates distinct features of each thread type with their proper name, and gives accurate read outs when a new picture stimulus is presented.

The Shatz-List:

In order to make the process easier, there is a preprogrammed Shatz-List as part of our app. This is a user inputted list that keeps track of certain brands and items that are already deemed "Shatz" or "Notz." Before checking an item for Shatnez, users are prompted to scan the item's tag to see if it is already programmed into the Shatz list. If it isn't there, the Shatnez checking application of the app will be used to determine if there is in fact Shatnez present in the item. This is extremely innovate because even without the clip on microscope items can be checked on just rudimentary level, to see if others have already found Shatnez in a specific item, or deemed that the item is clear of this mixture.

Market Research:

As of 2021, there is approximately 15.7 million Jews in the world. With the 11% that fall into the orthodox or ultraorthodox category, that makes well over 1.7 million Jews that may follow the commandments in the Torah. Although that can seem small, these Jews are struggling to keep the commandment of Shatnez due to the lack of label accuracy and the inconvenience of getting an item professionally checked. With less than 100 Shatnez labs in the United States, the inconveniences accompanied with observing this commandment are enhanced. From the checker end, there are many inconveniences as well, 2 years of training are necessary for Shatnez testers to become experienced and knowledgeable of the fabrics. Additionally, checking with a fabric of “undefined fabrics” is done by removing fabric from 3 different areas of the garment and checking them, which is even more inefficient.

Proof of Concept:

The current way of checking Shatnez is both inefficient and costly. Hiring a professional Shatnez tester for every garment purchased costs approximately $15 an item, and with the average American buying 68 new garments of clothing each year where wool and linen are in the top 3 most common clothing fabrics, the estimated yearly total is $1,020 for fabric checking. And the $15 fee can be exacerbated based on the size of the garment. A blanket, for example, would cost much more and raise this average significantly. Additionally, it is a hassle to take each garment to and from the professional checkers and wait a few days before wearing the item and to possibly deal with returning items that are found to have Shatnez. Our item, on the other hand, can be brought into the store to avoid that step all together.

Why our product is innovative:

The true innovation of our product and company lies in multiple facets of our business model. For one, we truly have no competition since no other AI based shatnez detecting technology exists on the market at the moment. The current model of bringing items to a shatnez checker is simply outdated, and has no positive upsides when compared with our product. We make checking potential shatnez both easier and cheaper! Another reason why our product and technology is so innovative, is because it has infinite room for expansion into many other markets (as you can see on the following two pages). AI integration currently dominates all sectors of life. With continued expansion of the fabric neural network we have started to develop, we will be able to make slight modifications to our technology in order to become extremely profitable in other fields, markets, and sectors related in any shape or form to textile and thread.