Trax

Image Recognition for Retail Analytics and Points of Sale

Retail, Visual Monitor
Artificial Intelligence Computer Vision Machine Learning

Business Overview

Trax Image Recognition provides cutting-edge image-recognition technology and market-data services to tier-one manufacturers. The company assures tighter in-store execution controls and the ability to unlock revenue opportunities at all points of sale. Trax’s technology can be integrated as a plug-in to existing merchandising or retail execution systems. The company’s platform utilizes iOS, Android, and Windows smartphones and tablets to capture images of retail shelves. Analysis within the Trax cloud provides immediate, actionable mobile reports to sales reps and aggregated web reports to management teams. Trax’s solutions replace manual auditing methods by up to 60%, allowing sales reps to focus more time on in-store sales development activities. Trax is a trusted OEM partner of more than 25 leading retail solution providers, and many top brands use Trax to manage their in-store execution and increase revenues, including Coca-Cola, AB InBev, Nestle, and Henkel.

Operating Status
Active
Founded
November 2010
Employees
600
Business model
B2B
Offering type
Software
Funding stage
Series E
Business stage
Launched
Revenue status
Revenue Generating
Total funding
$1032.8 Million
Sectors
Retail, Visual Monitor

Founders

Trax
Joel Bar-El
Chief Commercial Officer
Trax
Dror Feldheim
Executive Chairman
Serial Entrepreneur

Funding Rounds

Calculated as the average ratio between the current funding round amount raised and the previous funding round amount raised. Note that 'plus' rounds are summed together. i.e. Series A = Series A and Series A+.
Funding Growth Multiple
1.4x

New wpDataTable

Date Announced

Funding Round

Amount Raised

Investors

April 2021
Series E
$640 M
July 2018
Series E
$125 M

AI Technology Stack

AI Description

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.

AI employees
31
AI application
Vertical AI
AI types
Artificial Intelligence, Computer Vision, Machine Learning
ML types
Supervised Learning, Unsupervised Learning
AI algorithms
A*, Agglomerative, ARIMA, Auto Encoders, Boltzman Machines, Boosting, Clustering, DBScan, Decision Trees, Density Estimation, Genetic Algorithms, Holt-Winters, K-Means, Local Search, Naive Bayes Classifiers, Nearest Neighbor, Neural Networks, Non-Linear, Non-Negative Matrix Factorization, Simulated Annealing, Support Vector Machines (SVM), t-SNE
AI tools
Keras, Scikit-Learn, TensorFlow
Coding
Python
AI hardware
CPU, GPU
Cloud provider
Amazon Web Services

In The News

Big-Tech 50 adds four more companies to portfolio | News – Globes

March 29, 2021

Trax plans New York IPO at $2b valuation, Israel layoffs | News – Globes

January 20, 2021

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