User:Sarath Narayanan Shyamala/sandbox/ViSenze

ViSenze powers visual commerce at scale for retailers and publishers. The company delivers intelligent image recognition solutions that shorten the path to action as consumers search and discover on the visual web. Retailers like Rakuten and ASOS use ViSenze to convert images into immediate product search opportunities, improving conversion rates. Media companies use ViSenze to turn any image or video into an engagement opportunity, driving more new and incremental dollars.

ViSenze - AI for Visual Commerce

Venture-backed by Rakuten and WI Harper, ViSenze is built by web specialists and computer scientists with deep machine learning and computer vision experience. ViSenze has offices in US, UK, India, China and Singapore. The company originally started as a part of NExT, a leading research centre jointly established between National University of Singapore and Tsinghua University of China

History

ViSenze was founded in 2012 by Roger Yuen, Oliver Tan, Chua Tat-Seng, and Li Guangda. In 2014 and 2016, the company closed a USD $3.5M Series A funding round and a USD $10.5M Series B funding round, led by Rakuten Ventures with participation from Walden International and UOB Venture Management. The company is now actively expanding to markets like China and the USA.

With a bachelor’s degree (honours) in economics from the University of London and an MBA from Royal Holloway, University of London, Oliver has over 19 years of diversified business experience in the technology, media, and telecommunications (TMT) space. An former venture capitalist himself, he noted that he enjoys working with startups, having spent five years as a key staff in a technology startup till its successful exit.

Solutions and use cases

1. Visually Similar recommendations

Find Similar

When consumers browse the website listing page/ detail page, they can click Find Similar to search for visually similar product recommendations from product catalog.

You May Also Like

Display visually similar product recommendations from product catalog on the listing page/detail page.

Out of Stock

When certain products are out of stock, display visually similar product recommendations from product catalog.

2. Search By Image

Snap and Shop

The consumer takes a photo (or take a screenshot/web download image), upload to an e-commerce website and searches for products.

Online Search for Copyrighted Image

Search a large volume of online social media images against customer’s own copyrighted image database to find an exact same image.

Trademark & Patent Search

Facilitate patent filing and search process by uploading a trademark image and search for an exact same image.

3. Multiple Product search

Shop the Look / Room We Love

Enhance e-commerce site user experiences. When the consumers browse the website, it shows multiple objects detected within 1 image and show similar products for each.

Discovery Search

User upload an UGC image, multiple objects would be detected and find similar products for all of them.

Embedded in Moderation Tools

Client use it as an internal tool to first detect a list of product and then go through the manual moderation process before exposing the results to their consumers.

Browse & Discovery Refinement

Empower attribute filters and increase discoverability in the product listing page (PLP) and product detail page (PDP)

Internal Catalogue Management

Used in customer’s internal data management tool. Customers can upload batches of their product images, and specific attributes will be extracted and returned based on category-specific tag groups.

Low quality image moderation

Predict low quality images that are collaged, mosaic, watermark etc which improves customer browsing experience.

External links

• www.example.com