LAS VEGAS, Nevada, November 28, 2017 -- Anodot, an AI-powered analytics company, announced today at AWS re:Invent 2017 that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. This designation recognizes Anodot as a SaaS/API Provider, offering a solution that enables predictive capabilities within customer applications. Achieving the AWS ML Competency differentiates Anodot as an AWS Partner Network (APN) member that has built solutions that help organizations solve their data challenges, enable machine learning and data science workflows or offer SaaS/API based capabilities that enhance end applications with machine intelligence. Attaining the AWS ML Competency demonstrates to its customers that Anodot has validated ML expertise on AWS. "Achieving AWS ML Competency status recognizes Anodot's proven track record of using machine learning to uncover our customers' business blind spots automatically and in real time," said Anodot Chief Data Scientist and Co-Founder Ira Cohen. "Our team is dedicated to helping customers leverage their massive amounts of data to gain competitive advantage and prevent revenue or brand damage." AWS is enabling scalable, flexible, and cost-effective solutions from startups to global enterprises. To support the seamless integration and deployment of these solutions, AWS established the AWS Partner Competency Program to help customers identify Consulting and Technology APN Partners with deep industry experience and expertise. Anodot's AI Analytics uses patented machine learning algorithms to isolate and correlate issues across multiple data metrics in real time, supporting rapid business decisions. In effect, Anodot uses machine learning to discover and solve incidents that otherwise would become major losses for companies that could hurt revenue or damage a company's brand. Anodot correlates the anomalies it discovers across multiple systems, such as AWS, business systems, application events, and more. Anodot and Amazon Web Services are working together to provide organizations critical observations using Machine Learning to give valuable business insights based on real time data analysis. "Not every machine learning problem requires starting from scratch and building a custom solution, and not all of our customers have access to a dedicated data science team with the time and expertise to build a production workflow for large scale predictions," said Joseph Spisak, Global Lead for Artificial Intelligence and Machine Learning Partnerships, Amazon Web Services, Inc. "We are delighted to welcome Anodot to the Artificial Intelligence and Machine Learning Competency Program to provide off-the-shelf machine learning solutions that can help speed time to market and bring intelligence to any application." One of the largest ad exchanges in the world, Rubicon Project uses proprietary computing systems to automate the buying and selling of advertising. Working with Anodot for more than two years, Rubicon's systems process more than twice as many transactions as the Nasdaq stock exchange. "We want the Supply and Demand Partners to know that we're watching things very closely. Deviations in trading can have a devastating effect on both the advertisers and the exchange," said Rich Galan, Director of Analytics at Rubicon Project, "With Anodot's alerts and correlation capabilities, Rubicon can easily track all of the data in real time. We can determine if we need to reach out to a Partner in real time to fix an issue. We're not just helping our business, we're helping our partner's business. That's the level of service that we want to provide." About Anodot Anodot illuminates business blind spots with AI-powered analytics, so you will never miss another revenue leak or brand-damaging incident. Its automated machine learning algorithms continuously analyze all your business data, detect the business incidents that matter, and identify why they are happening by correlating across multiple data sources. Anodot customers in fintech, ad-tech, web & mobile apps, and other data-heavy industries use Anodot to drive real business benefits like significant cost savings, increased revenue and upturn in customer satisfaction. The company was founded in 2014, is headquartered in Ra'anana, Israel, and has offices in Silicon Valley. Learn more at: http://www.anodot.com .

(Sunnyvale, CA and Ra’anana, Israel) November 21, 2017 –– Anodot, the AI-powered analytics company, announced today the launch of  "AI Analytics for Retail" just in time for the upcoming holiday shopping season. With Black Friday and Cyber Monday accounting for 6-10x revenue compared to a regular shopping day, Anodot's system for retail will help companies increase profits this holiday season. During Black Friday and Cyber Monday, retailers lose, on average, $250,000 per incident on glitches that would set a company back approximately $40,000 outside the holiday season. Anodot AI Analytics for Retail uncovers hidden insights in vast troves of business data, identifying outliers in key performance indicators, correlating across multiple sources, and providing valuable real-time insights. For example, Anodot enables retailers to maintain confidence in market presence (search/comparison sites/forums), product presence (inventory, types, options, product images), site and store performance, customer journey, payment process, shipping process, returns process, and more. "For retailers, the critical holiday season means online shopping spikes, and glitches can lead to larger losses, both monetarily and reputationally," said David Drai, CEO and Co-founder of Anodot. "Today's environment allows very little margin for error. Our solution ensures our retail customers' sites and interactions are perfectly consistent across platforms. It effectively tracks exact customer activity and delivers concise data that is dependable, allowing us to ensure that consumers are having a best-in-class experience." Retailers' Secret Sauce Anodot's AI-powered data analytics system -- with multiple patents pending -- uncovers incidents in real time, revealing glitches that would cost retailers millions in lost revenue, and identifying opportunities. Traditional BI tools, such as dashboards, cannot keep up with the constantly changing and massive amounts of data in today's retail. They prove useless for finding glitches quickly, as they typically display historical data, not real-time data. Dashboards require humans to create and interpret them, which is time consuming and frustrating, when every hour costs retailers significant revenue loss. The challenge to retailers is amplified with mobile users, who are less patient than desktop users, and will jump to a competitor site when running into the smallest slowdown or glitch. "No matter the commerce channel, having an overall view of shopper purchase and selection behavior and the support systems surrounding them is the key to future retail success," said John L. Myers, Managing Research Director, Enterprise Management Associates (EMA), a Boulder, CO based industry analysis firm. "Incorporating real-time analytics, AI, and machine learning into brick and mortar, e-commerce or a hybrid strategy allows retailers to gain greater insights into customer experience and consumer trends. The Anodot platform enables retailers across multiple categories to protect themselves from unforeseen developments in consumer tastes, customer transactions and per store revenue, saving millions of dollars in lost opportunities and brand reputation." The following are examples of common and costly glitches that Anodot can detect: $2,000 televisions were being sold for $200. Identifying a drop in mobile sales for a particular set of products after incorrectly updating a batch of SKUs on the site. Quickly identifying correlation between a celebrity's Instagram post and a revenue spike for a particular product and allowing the retailer to leverage it to bundle another product and shift inventory orders to ensure adequate inventory Identifying cross promotion glitches to ensure the proper products are recommended for the appropriate customer profiles Identifying a revenue drop for kitchen supplies as a result of a competitor's increased ad bids for kitchen supplies. "During the peak shopping season, any glitches that occur can cost an order of magnitude more than during the rest of the year," said David Drai, Founder & CEO, Anodot. "Online retailers need to learn to identify and rectify glitches in real time to avoid losing revenue and prevent brand damage. This is a difficult task because of the sheer volume of data and because e-commerce sites use many interconnected data systems and any one of them or a combination of systems can have a glitch due to human error or a technical issue." A Deep Dive into Anodot's Technology Anodot discovers issues at a much finer granularity in real time, giving immediate results and saving companies hours spent on creating and analyzing dashboards. Anodot's retail system also automatically alerts about any abnormal data behaviors on your site, app, or in-store and notifications can be received through Slack, SMS, Pager Duty, or Email. Anodot AI for Retail works with: ERP Systems for tracking inventory, product families, pricing history, shipping information  Inventory systems (e.g. ERP) Web/ Mobile analytics (e.g. Google Analytics, Adobe Analytics, MixPanel) Point-of-Sale data including groupings by SKUs and cross promotion information Call Center (e.g. CRM) Social Media Monitoring Marketing campaigns including coupon redemption Shipping information Devops/IT data Anodot is capable of bringing in any type of internal or external data. For example: Weather Competitor prices Competitor advertising bids Social Media Monitoring Demographic Information Search engines Product comparison sites About Anodot Anodot  illuminates business blind spots with AI analytics, so you will never miss another revenue leak or brand-damaging incident. Its automated machine learning algorithms continuously analyze all your business data, detect the business incidents that matter, and identify why they are happening by correlating across multiple data sources. Anodot customers in fintech, ad-tech, web & mobile apps, and other data-heavy industries use Anodot to drive real business benefits like significant cost savings, increased revenue and upturn in customer satisfaction. The company was founded in 2014, is headquartered in Ra'anana, Israel, and has offices in Silicon Valley.  Learn more at:  www.anodot.com.