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Intelligence Node honored with Aegis Graham Award

Fiinews by Fiinews
March 26, 2020
in Technology
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Recognition of ML and AI

Retail analytics and pricing intelligence leader Intelligence Node was honored by the Aegis School of Business, Data Science, Cyber Security and Telecommunication with the Aegis Graham Bell Innovation in Data Science Award.

The award is designed to promote technology innovation and reward exceptional contributions by innovators, said Intelligence Node on 25 Mar 2020.

Intelligence Node was recognized for its machine learning and artificial intelligence capabilities for e-commerce pricing. While many dynamic pricing algorithms rely on historical pricing data only, Intelligence Node’s algorithm incorporates the key factor called “visibility,” which identifies how easily a product can be spotted on any search engine, which is critical in this Google driven retail world.

Intelligence Node’s proprietary process of measuring visibility is based on product attribute listings and an image score based on displayed product images. It also includes elements including seasonality, real-time buying trends, holidays and promotional offers, making it a 360-degree optimization of search engine results for any product. Intelligence Node developed an algorithm to account for all of these factors and more, bringing customers smarter pricing recommendations and a record refresh rate of ten seconds.

“You can’t buy a product if you can’t see it,” said Sanjeev Sularia, CEO, Intelligence Node.

“We are proud to say that we have the most advanced formula on the market for measuring product visibility and its impact on pricing. We are excited to continue to push the envelope in advancing price optimization technology and are honored to be recognized by the Aegis School for our work in moving technology innovation forward,” he said.

Intelligence Node, with offices in London, Mumbai and New York, is a real-time retail price intelligence platform that empowers businesses to drive product level profitability and grow margins using data-driven competitive insights. fiinews.com

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