As humans keep evolving, technology keeps advancing. Gabriel Eze and Maven Harry have co-founded an evolutionary way of engaging with pictures — Touchabl.
Touchabl is social-commerce platform that enables people search and shop for items in pictures simply by touching them, even when the names of such items are unknown. It was launched on October 7, 2017.
Together, the founding team has led other developers and worked on the object detection algorithm for about 6 years. The team also prides the application as being indigenious. “Touchabl is made in Nigeria for the world,” says Gabriel. Gabriel also claims that currently, the application is arguably Africa’s most advanced AI project in the area of computer vision.
Usage scenario of Touchabl
Jane Doe shares a picture on her timeline, and her followers like/comment on the picture. But there’s this fine red shoe she is wearing in the picture that particularly caught Fiona’s (Jane’s follower) eyes. Fiona is more than eager to know more about this shoe and probably where to buy it.
Instead of asking Jane, in the comment section, necessary details about the shoe, all Fiona needs to do is touch the picture and boom! She gets all information she wants. She also sees other items similar kinds to the one she touched in the result Touchabl returns. Then Fiona can either buy the shoe or bookmark it for later.
Another instance is Sabina, a fashion-savvy girl. If she is not able to afford Jane’s shoe the app displays other similar but cheaper shoes in the search result. Sabina is also able to touch Jane’s other fashions stuff to get perfect recommendations for her budget.
How Touchabl works
Tha app captures and stores Fiona’s touch as a “Fip” aka fingertip. It does same for other people who, like Fiona, may be interested in some other pieces in Jane’s picture (handbag, dress, watch, etc). With these “Fips”, the app measures what people touch in pictures — such as Jane’s –, when they were touched, and how many people touched what.
Advertising companies (AdCos) will find the app exceptionally useful. With it, they can get better insight or metrics on how people engage with any picture(s) on their platform (via likes, comments, bookmarks and Fips). The app also creates a campaign targeting interest which appears in user result when they touch kinds of stuff in other people’s picture.
We are young, ambitious, self-taught, and dedicated to making an impact. The object detection algorithm took 6 years and so many developers to achieve. Within this period, developers have come, contributed to the code base and left; collectively resulting to today’s Touchabl image recognition engine. Every engineer that left still contribute towards the project when called upon. For us, taking on a project in the field of Artificial Intelligence is bold statement that we can aim for greatness. All developers are indigenous — Gabriel Eze (Cofounder/UX Lead).
You can experience this exciting application by visiting the online platform.
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