Active

2010

858

-1.7%

$1.08B

Debt

11

14

0.1 years

Trax’s mission is to enable brands and retailers to harness the power of digital technologies to produce the best shopping experiences imaginable. Trax’s retail platform allows customers to understand what is happening on shelf, in every store, all the time so they can focus on what they do best – delighting shoppers. Many of the world’s top CPG companies and retailers use Trax’s dynamic merchandising, in-store execution, shopper engagement, market measurement, analytics, and shelf monitoring solutions at scale to drive positive shopper experiences and unlock revenue opportunities at all points of sale. As pioneers in computer vision, Trax continues to lead the industry in innovation and excellence through development of advanced technologies and autonomous data collection methods. Trax is a global company with hubs in the United States, Singapore and Israel, serving customers in more than 90 countries worldwide. To learn more about Trax, please visit http://www.traxretail.com.

-1.7%

-4.2%

-7.6%

Employee counts updated on a monthly basis.

NamePositionMilitaryClassificationContact
hiddenDror Feldheim
Executive ChairmanSerial Entrepreneur
hiddenJoel Bar-El
Chief Commercial Officer

$1.03B

$50M

RoundDateCapital RaisedValuationInvestors
April 2021
hidden$640M
$2.25B
4
June 2019
hidden$100M
$1.1B
4
June 2018
hidden$125M
$1B
2
May 2017
hidden$64M
1
January 2017
hidden$19.5M
1
May 2016
hidden$40M
1
November 2014
hidden$15M
1
January 2014
hidden$15.7M
July 2013
hidden$6.6M
May 2011
hidden$7M
November 2023
hidden$50M
1
InvestorInvestor TypeLocation
Investment FirmJapan
Venture CapitalJapan
Investment FirmUnited States
Corporate Venture CapitalJapan
PensionCanada
GovernmentSingapore
GovernmentSingapore
CompanySouth Africa
Private EquityUnited States
CompanyScotland
CompanyScotland
Investment FirmIsrael
Investment FirmIsrael
Venture CapitalIsrael
Patent TitleStatusDatePatent ID
Application
August 2019
US-2019236531-A1
Application
July 2015
WO-2015101979-A1
Application
March 2014
IL-229806-D0
Application
June 2015
WO-2015083170-A1
Application
June 2019
US-2019197561-A1
Application
July 2017
US-2017200068-A1
Granted
US-10402777-B2
Granted
US-10122915-B2
Application
September 2020
WO-2020181066-A1
Granted
US-10521645-B2
Application
March 2020
US-2020074402-A1
Granted
US-10387996-B2
Granted
US-10368662-B2
Application
November 2014
WO-2014181323-A1
Application
March 2020
WO-2020051213-A1
Application
May 2019
US-2019149725-A1
Application
March 2019
WO-2019048924-A1

31

We use AI for improving our own decision-making processes, for improving our products, and as a driver for new products. Internally, we leverage Time Series analysis (mostly Holt Winters Triple Exponential Smoothing or ARIMA) to predict the expected workload (images, analysis times and costs as well as identifying system performance issues (anomaly detection using GMM). AI is also ingrained in our products: we use non linear regression to predict our customer sales performance, Auto Encoders and NMF to create dense representation of outlets that are then fed into unsupervised clustering methods (often density based such as DBScan), and classification to build profiles of these outlets. Prediction results are often fed into planning and optimizing tools to generate concrete actions. These include heuristic search (A*, AKA œA-Star), Genetic Algorithms, and local search with simulated annealing.

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