ASHBURN, Virginia – November 9, 2021 – Today Anodot, the business monitoring company, announced the acquisition of Pileus, a cloud cost management platform for an undisclosed amount. The combined offering, powered by machine learning, will enable businesses to proactively manage and forecast their cloud costs. Valued at $396 billion, the public cloud market is fueled by businesses adopting cloud-first strategies for digital transformation and remote work initiatives. Cloud acceleration has created a significant cost driver for businesses. In fact, research shows that 69% of firms regularly overspend on their cloud budget by at least 25%. “We have witnessed first-hand the many challenges organizations face while attempting to manage their cloud costs,” said David Drai, CEO, Anodot. “Historically, cloud pricing and billing has been a complicated undertaking for many organizations - until now. Today, Anodot joins forces with Pileus to combat this growing problem. Pileus is the only technology on the market able to provide granular intelligence, visibility, and control over cloud billing.” “Anodot’s acquisition of Pileus is not only a strong move to support Anodot’s expansion into cloud cost management, but also the realization of its vision as a leader in comprehensive autonomous business monitoring and prediction,” said Alexander Assim, Partner, Alicorn. “The team at Alicorn is proud to support both companies on their journey of growth following this strategic investment.” The combined technology will integrate visualization, analytics, and cost savings recommendations, all from a single platform. Data-driven businesses will benefit from AI-powered anomaly detection, correlation, and forecasting for real-time monitoring of all cloud environments, inclusive of Kubernetes-based services. “One of the biggest challenges for customers in managing their cloud costs is the ability to forecast cloud spend and identify anomalies in cloud uses and costs. The problem becomes several times more complex, in large and dynamic environments,” said Roni Karp, CEO, Pileus. Anodot's advanced capabilities will allow Pileus to detect anomalies and forecast cloud spend, factoring in the cloud cost history in addition to related business metrics, for significantly more accurate budgeting. “Pileus has significantly helped our business keep cloud-related costs under control,” said Rubi Cohen, Cloud Center of Excellence, Director, Amdocs. “We believe that integrating machine learning capabilities for anomaly detection and accurate forecasting will help us tremendously with smarter and more accurate cloud cost management.” About Anodot Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Virginia and Israel, with sales offices worldwide. To learn more, follow Anodot on LinkedIn and Twitter. About Pileus Pileus helps companies visualize and optimize their cloud cost by monitoring their cloud environments end-to-end, including an accurate breakdown of Kubernetes cost. They enable customers like Fiverr, NICE, and Amdocs to manage, monitor and save on cloud costs using easy-to-implement recommendations on any cloud platform. Learn more about Pileus.

Amazon’s Dominance and Global Logistics Concerns Are Pushing Retailers to Use AI-tools to Improve Customer Experience, Drive Topline Revenues Originally published in Business Wire ASHBURN, Virginia – October 26, 2021 - Anodot, the autonomous business monitoring company, announced the results of an independent Researchscape survey of consumers and retailers. The survey reveals that as consumer spending is set to eclipse last year’s record numbers, retailers are under enormous pressure to deliver a seamless shopping experience amid rising concerns of supply chain disruptions that have and will impact inventory. While retailers are bullish about sales this season with 85% of survey respondents expecting to see a year-over-year increase in sales, 42% of them remained worried about supply chain disruptions having a negative impact on product inventory and timely deliveries.  Nearly half of all respondents said they were concerned about logistics challenges after last year’s bottlenecks created limited inventories and shipping, which negatively impacted revenues. Those concerns have driven retailers to begin offering Black Friday sales promotions even earlier this season.  The stakes are higher than ever this year and retailers must execute a seamless shopping experience to avoid losing customers and sales amidst an increasingly competitive environment. Today, consumers have a range of options when shopping and if small to medium-sized retailers can’t provide that seamless experience, they will not get a second chance. In fact, 82% of consumer respondents say that a negative experience with an online retailer is somewhat, very, or completely likely to turn them away from that merchant, and most likely into the arms of Amazon. Last year, Amazon swallowed 51.2% of all online sales. Not surprisingly, 55% of consumers named Amazon as their retailer of choice. 48% of retailers surveyed named Amazon as their largest competitor. Amazon’s seemingly limitless inventory, easy-to-navigate website, recommendation engine, and one-click shopping have set the bar for the consumer shopping experience.    “Based on spending projections, there are high hopes for this holiday season, but there are warning signs on the horizon,” said David Drai, CEO and founder, Anodot. “Supply chain disruptions have caused inventory issues that have shoppers nervous and retailers feeling unprepared. Providing a seamless experience is critical, and retailers are integrating AI to prevent the customer experience and supply chain issues that can frustrate shoppers.” One of the key findings from the survey is that retailers have prioritized addressing the issues that consumers have identified as critical factors in their shopping experience. The survey highlights that retailers and consumers are aligned with the most important pieces of the shopping experience where AI can be of great help. The top four areas include:  Websites that are easy to use  81% of online retailers  53% of consumers  In-stock inventory  65% of online retailers  50% of consumers  Competitive pricing  74% of online retailers  57% of consumers  Fast check-out and payment processes 67% of online retailers  46% of consumers  Retailers have continued to make big investments in AI, and 81% of retailers surveyed said they expected to increase their AI budgets in 2021. Beyond anomaly detection, merchants are using AI to drive topline revenues, with nearly one-third of respondents saying they believe AI can drive a 40% increase in revenues.   “AI-based anomaly detection isn’t new to the business sphere, but traditionally has been relegated to technical performance,” Drai said. “As companies scale, they’re finding it imperative to automate the way they monitor the entire business, from customer experience to revenue and costs, so they can meet consumer expectations. This survey confirms the expanding role of AI in eCommerce today and the applications that are proving most valuable to the business.” The survey shows online retailers are allocating their increased AI budgets to improve bottom-line results: Fraud detection – 81%  Improve customer retention – 55%  Enable targeted campaigns – 22%  Create dynamic pricing – 20%  Identify when a server is down – 19%  Marketing automation – 19%  Anticipate sales trends in different geographies – 18%   How the survey was fielded  The research firm Researchscape conducted independent surveys of consumers and retailers to understand their concerns and expectations for the 2021 holiday season. The consumer-focused survey was conducted from September 10 to 13, 2021, and 1,057 U.S.-based respondents completed the entire survey. The online retailers' survey was conducted from September 11 to 17, 2021 with 106 respondents.  To access the full survey report, please go to Anodot 2021 eCommerce Outlook Report. About Anodot  Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn and Twitter. 

Originally published in Business Wire on Sept. 23, 2021 ASHBURN, Va. – Anodot, the autonomous business monitoring company, today announced the results of an independent survey that reveals that Communication Service Providers (CSPs) are making artificial intelligence (AI) deployments an immediate priority to improve service experience for customers and reduce operational costs. >> Read the Report << Sixty seven percent of survey respondents have already deployed AI in their networks and more than 50% of those who have not deployed AI plan to do so within the next 6-24 months. Furthermore, 53% of respondents stated that improving service experience was the primary driver for implementing AI-based network monitoring and detection. These findings are based on an independent Heavy Reading global survey of nearly 100 senior networking and IT CSP decision makers commissioned by Anodot in Q3 2021. “Instead of waiting for next generation 5G network deployments to invest in AI, the majority of CSPs are already deploying AI on 4G networks now, the infrastructure most of their customers still use,” said Anodot Co-founder and CEO David Drai. “With AI-based network monitoring, CSPs can detect network issues up to 80% faster and reduce incident costs by as much as 70%.” At the same time, CSPs want to better use AI to monitor their networks as a whole and measure the quality of service they provide – rather than just monitoring network-related KPIs and minimizing network downtime, according to survey findings. In fact, 46% of survey respondents stated that network performance troubleshooting, early warnings and visibility into service degradations are critical to improving customer experience and reducing customer churn. However, most CSPs lack the specific tools that integrate with AI, existing data, and tools to perform more effective, holistic network monitoring. According to the survey, 42% of respondents cite integration with existing tools as the biggest barrier to deploying AI-based network monitoring and anomaly detection in networks. Service providers are looking for solutions that deliver a short time to value with easy integration and open APIs. They are also seeking solutions that are easy for teams to use and support without requiring significant investment in data science talent and professional services. The survey also found that more than half of respondents found that the cost of hours spent by their operations teams on monitoring service degradation is just as high as the cost of repairing the issues, which includes hardware fixes, third-party services, and truck roles. Therefore, CSPs seek to reduce the time their operations teams spend on detecting, analyzing, and understanding the root cause of network issues, with 49% of survey respondents stating that predictive impairment detection would deliver the largest cost savings for their organizations. “Anodot’s zero-touch network monitoring platform seamlessly integrates with AI and existing data while automating cross-layer network performance and service experience to free-up CSP operations teams,” said Drai. “We collect all data types, at any scale, and use AI/ML to correlate anomalies across the entire telco stack. Our platform is the ‘brain’ on top of the OSS that detects service-impacting incidents in real time, enabling the world’s largest telcos to protect their revenue and improve service experience—reducing the number of alerts by 90% and reducing time to resolve incidents by 30%,” he said. To access the full survey report: The Business Value of AI In Zero-Touch Network Monitoring About Anodot Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn and Twitter.

Originally published in Business Wire on Aug. 4, 2021 ASHBURN, Va. – Today, Anodot, the autonomous business monitoring company, announced that it has been selected by Qwilt, a leading provider of edge cloud and media delivery solutions, to help deliver better streaming experiences to its customers. With support from Anodot’s real-time, autonomous monitoring platform, Qwilt will be able to maintain the highest quality of service and reliability, two critical components when ensuring the success of any platform. Online media consumption is at an all-time high. This trend has been further augmented by the stay-at-home orders of the COVID-19 pandemic. According to Forrester, “...48% of U.S. online adults had subscribed to at least one streaming service,” and this behavior is here to stay. “Intense online media consumption is resetting consumer expectations and reshaping the content consumption experience.” Qwilt’s edge cloud and media delivery solution plays a pivotal role in this new digital reality by addressing scale, quality, and cost-related content delivery challenges at the edge. “Our next-generation content delivery solution, deeply embedded in last-mile service provider networks, is cloud-managed with open APIs for our content provider customers. Moreover, our solution is being embraced broadly and, when combined with increasing demand for more content and delivery capacity, we need to scale at a rapid pace,” said Alon Maor, CEO of Qwilt. “Anodot gives us constant insight into critical performance and quality of service issues, allowing us to deliver the highest quality of service to our customers.” Anodot is an AI-based platform that monitors and correlates business data across the entire business to identify incidents that threaten revenue, customer experience, and the partner ecosystem. Patented algorithms overcome the challenge of manual business monitoring by learning each KPI’s patterns and seasonality in order to detect anomalies in real time and with greater accuracy. Companies that use Anodot are able to, year over year, reduce mean time to detection up to 80% and cut incident costs up to 70%. Anodot customers in the streaming industry are able to build and maintain a competitive edge. Qwilt leverages Anodot’s fully autonomous platform to analyze vast volumes of generated network data to identify anomalies in critical issues such as buffering, load times, product usage, customer support, feature adoption, and content delivery. When there’s a degradation in customer experience, an alert is sent in real time to operations teams that shows contributing factors, such as related anomalies, influencing metrics and events, to guide them to the root cause. Anodot is driving faster incident detection and resolution for Qwilt and superior customer experience for its customers. “In today’s increasingly digital world, consumers are requesting high-quality online content at rapid speed,” said David Drai, CEO, Anodot. “Qwilt is transforming online content delivery and streaming services for its customers with better delivery capacity, higher quality, and lower prices. Qwilt can maintain a best-in-class competitive edge by analyzing data collected in real-time through Anodot’s AI-powered autonomous monitoring platform, eliminating things like poor video quality, declining subscription rates, and lost revenue.” About Anodot Anodot’s Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot’s patented technology to reduce time to detection and resolution for revenue-critical issues. Anodot is headquartered in the United States and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn, Facebook, and Twitter. About Qwilt Qwilt’s unique Edge Cloud Platform and Open Caching software and cloud solutions help Internet Service Providers address the dramatic growth of streaming media on their networks and the need for low latency, high scale infrastructure to support future applications. Qwilt’s cloud managed open platform, running on commodity compute and storage infrastructure, and deployed close to consumers, creates a massively distributed Edge Cloud that supports applications such as Open Caching, 4K Live Streaming, AR, VR, Self-Driving Cars and IoT. This low latency Edge Cloud architecture enables a high-quality streaming experience for consumers on a massive scale. A growing number of the world’s leading cable, telco and mobile service providers rely on Qwilt for Edge Cloud applications. Qwilt is a Founding Member of the Streaming Video Alliance and a leader of the Open Caching industry movement. Founded in 2010 by industry veterans from Cisco and Juniper, Qwilt is backed by Accel Partners, Bessemer Venture Partners, Cisco Ventures, Disrupt-ive, Innovation Endeavors, Marker, and Redpoint Ventures. Learn more at Qwilt. Follow us on Twitter @Qwilt.

The algorithm correlates cross-siloed revenue-impacting anomalies across the enterprise, speeding time to detection and remediation by 30% Originally published in Business Wire on July 8, 2021 ASHBURN, Va. – Anodot, the autonomous business monitoring company, announced that it had been granted the US patent US10891558B2 for its Heuristic Inference of Topological Representation of Metric Relationships. The patent covers Anodot’s first-of-its-kind machine learning (ML) based correlation analysis that allows enterprises to automatically discover non-obvious cross-siloed anomalies that can impact revenues. Correlation analysis identifies relationships between key performance indicators, which business teams can quickly use to determine the root cause revenue and service impacting events. Without Anodot, companies would have to use time-consuming manual techniques to determine the revenue disruption's underlying cause. By combining anomaly detection with automated cross-siloed correlation analysis, Anodot helps enterprises detect and fix revenue-impacting incidents 80% faster than any other method. “Historically, events that have produced lost revenue or service drops were difficult to detect because the correlating events could be in different places within the enterprise requiring different domain expertise. For example, the team in charge of revenue could notice a drop in sales for a particular selection of items but wouldn't know that the cause of the problem was the slow page load times for items with overly large image sizes,” said Anodot Chief Data Scientist Dr. Ira Cohen. “Using Anodot’s correlation analysis, the revenue team, which mostly likely does not have in-depth knowledge of web page design, would immediately be alerted to the problem, determine its cause, be pointed to a solution, and minimize revenue loss.” The power of the Anodot platform is its ability to accurately detect and correlate anomalies at scale without the need for any human input. Anodot invented an algorithm called abnormal correlation that groups metrics across silos if they behave abnormally at similar times. The theory is that if two metrics are affected by a common cause, companies should see that pattern repeat itself over time. Anodot uses locality-sensitive hashing (LSH) to scale its correlation techniques to sift through billions of metrics. The combination of abnormal correlation and LSH provide Anodot customers with the fastest time to remediation for events that can impact service and revenue. “Anodot goes beyond mere alerts,” said Viacheslav Tsyganov, Chief Information Officer, Vice President, Deputy Chairman of the Management Board at Tinkoff. “Anodot’s correlation analysis not only accurately alerts us when there is a disruption in service, it also shows us why the problem is happening. Because the root cause analysis helps us understand the relationships between anomalies across teams and departments, we fix problems faster and suffer fewer revenue losses.” To learn more about Anodot’s Correlation Analysis, please visit: https://www.youtube.com/watch?v=J4IKGeRw6wY About Anodot Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn, Facebook, and Twitter.

June 9, 2021 - Datanami.com If your CFO is in a state of shock over a recent AWS bill, she is not alone. According to a recent survey by Anodot, 30% of data and analytics professionals reported nearly a 50% increase in their monthly cloud bills over a six-month period last year, and one out of five saw their cloud bills double. Better monitoring and alerting to sudden spikes, Anodot says, is a potential solution. At a macro level, COVID-19 and the work-from-home mandate clearly were big drivers in cloud adoption in 2020. Gartner says cloud spending in 2021 is set to rise 18% from last year, hitting nearly $305 billion. As a percentage of total IT spending, cloud is set to grab a 14% share, up from 9% last year. While the big-picture migration of data and applications to the cloud is becoming crystal clear, that storyline doesn’t reflect the difficult circumstances that many individual organizations are facing as they adopt new cloud services and move existing IT processes into public cloud. Getting a better handle on the challenges the cloud poses to these companies is what drove Anodot in March to survey nearly 110 data and analytics professionals about their organizations’ cloud spending patterns. The results, which Anodot shared exclusively with Datanami before they were set to be released today, show that a large number of organizations are facing rapidly growing cloud costs, including large and sudden spikes, and that they’re struggling to get a handle on this. About 55% of respondents to Anodot’s survey say they have been “surprised” by cloud costs or had an incident where cloud costs suddenly spiked. About two-thirds said cloud costs were a consideration in day-to-day business activities, while slightly more than 50% said they were able to remediate cloud usage and cost issues in real time. When spikes in cloud usage occur, only about 20% said they were able to immediately detect them, while about 25% said they could detect them in a few hours. About 35% said it takes them “a few days” to detect the cloud usage spikes, while another 20% said it took them a few weeks. Less than 10% indicated it took them months to detect the spikes.   Source: Anodot cloud survey “2020 was a really rough year with cloud costs skyrocketing, and it’s just going to continue,” an Anodot spokesperson said. “Sometimes, the costs are due to mistakes and glitches. Sometimes they’re just using a lot of cloud applications. They’re working from home, and they need access to corporate data.” The migration to the cloud is in full swing, but many organizations are struggling with the move. According to Anodot’s survey, only 10% of survey respondents reported having a “extremely smooth transition” to the cloud, about 25% had a “relatively smooth transition,” whereas 30% said they had a “challenging transition.” Around 40% said “it went OK.” Anodot develops a machine learning environment that is geared toward monitoring business metrics. The offering, which specializes in automatically detecting anomalies in time-series data, has been used extensively in the telecommunications and financial services industries. With the recent spike in cloud costs, the company is pivoting its focus a bit to address that unanticipated concern. Misconfigured in the Cloud Count Kenshoo, an Israel-based provider of campaign management software and services, among the companies struggling to get a handle on cloud costs. According to Danny Zalkind, Kenshoo’s DevOps group manager, the company is very concerned about losing control of its costs as it migrates more applications to AWS. “Once you go to the cloud, it’s very easy to lose track,” Zalkind told Datanami. “Some of it is slow leaks and some of it could be human mistakes, misconfiguration. You could easily, in a couple of days or a week, pay large amounts of money for a simple misconfiguration.” Kenshoo recently had an incident where one of its employees selected the wrong EC2 instance, and it cost the company nearly $40,000 over the course of a couple of days, Zalkind said. At other times, internal users have left cloud-based GPUs spinning after work on them has stopped. “We use GPU-based instances for all kinds of machine learning and data labeling processes, so that can be very costly if you start using those expensive GPU instances and you don’t turn it off on time or once you finish,” Zalkind added. “We’ve had some experience with that.” AWS shows steady revenue growth (Source: Statista) The SaaS company runs its data analytics and data science workloads in the cloud, but it’s planning to migrate other parts of its core campaign management application, including the Web serving and database configuration management components, to AWS too. That has caused Zalkind and his colleagues in DevOps to focus more attention on addressing the cloud spikes and the unanticipated costs that are associated with them. Before the cloud bill started to grow, the company was spending around $150,000 to $200,000 per month on the cloud, Zalkind said. But several times in recent months, that bill has risen to $500,000, which Zalkind attributes to a mix of cloud instance misconfigurations as well as natural customer-driven growth. Overall, Kenshoo’s cloud bill is growing around 10% to 15% per month. That figure reflects the unanticipated spikes as well as natural growth in its business; there was also an acquisition, according to Zalkind, who indicated the monthly cloud spending should be about $300,000. “We’re constantly monitoring usage because it can very easily just go week by week, and just increase slowly,” Zalkind said. “It’s very easy to not notice and lose track, and one day you look at the bill at the end of the month and you ask yourself, how did that happen?” Kenshoo recently started using Anodot’s machine learning tool to monitor its cloud usage. For Kenshoo, it’s relying on Anodot’s capabilities with anomaly detection in time-series data to be able to remove the natural seasonality from its cloud workloads and detect when something has actually gone awry. “Before we were actively managing or monitoring and reacting to alerts, we used to grow up to 15% per month in certain services or total cost,” Zalkind said. “Now it’s very rare to see a misconfiguration that lasts more than a day. And we’re also now pretty stable on the cost. We’re proud of that.” An AI-approach to monitoring and alerting for cloud costs is superior to static, BI-based methods because AI-based methods are more adaptable, according to Anodot. For Kenshoo, the static approach didn’t work, either. “The main thing is, more accuracy,” Zalkind said. “The static threshold method creates a lot of false positives. There’s really no other way to monitor those types of seasonal datatypes without looking at seasonality and without breaking it down to multiple dimensions. Pretty much at a certain size, it’s not possible without that.” To get a copy of Anodot’s survey, go to www.anodot.com/blog/cloud-cost-survey.

Powered by autonomous learning capabilities, new enhancements prioritize alerts based on impact on the business and customer experience May 28, 2021 09:00 AM Eastern Daylight Time ASHBURN, Va.--(BUSINESS WIRE)--Anodot, the autonomous business monitoring company, continues to enhance its product by providing high-performing companies with two new tools to measure the impact of anomalies on business operations and flag relevant alerts during reoccurring but shifting events. The Business Impact Alert functionality provides a visual indication that gives companies insight into how much an anomaly is impacting a company’s bottom line. The Influencing Events functionality helps companies define recurring seasonal events that shift on the calendar, like spring and summer holidays. Anodot can contextualize historical data around the events and accurately identify anomalies that happen during those time periods. Businesses are flooded with constantly changing thresholds brought on by seasonality, changing habits due to the pandemic, and promotions that feature new product rollouts. With information siloed and scattered across the enterprise, manual monitoring fails. Anodot’s Business Impact Alerts and Influencing Events use advanced artificial intelligence and machine learning that can autonomously adapt to changes, creating real-time, actionable alerts on business incidents and the fastest mean time to resolution (MTTR) in the industry. Business Impact Alert Functionality This new feature allows enterprises to prioritize alerts based on the incidents’ impact to the business. When setting up an alert, companies can assign a monetary value for each metric they monitor, and future alerts will show how much the anomaly has cost. This allows the business owner to quickly calculate the cost of an incident and prioritize when to address it. Minor incidents can be tackled when the team has free time, whereas major incidents are immediately assigned for remediation. The prioritization based on business value enables enterprises to focus on what truly matters. Influencing Events Functionality Recurring events such as Black Friday or religious holidays like Christmas, Passover, or Ramadan affect the business in predictable ways, but the dates are not the same from year to year. When businesses don't have the opportunity to put these events in historical context, their business monitoring tools create false positive alerts, wasting resources and disappointing customers. Anodot learns the behavior of the metrics around the previous occurrences of the event and updates the baseline for the upcoming event, taking into consideration the previous influences based around that event. The algorithm will recognize which behaviors repeat themselves. Once that has been accomplished, businesses will only see alerts for anomalies that are not associated with the seasonal event. “Businesses need monitoring tools that can quickly identify issues that impact the customer experience and protect revenue,” said Ira Cohen, co-founder and chief data scientist, Anodot. “Our Business Impact Alerts and Influencing Events feature only alerts customers on issues that directly affect the business, preserving resources that would otherwise be wasted investigating issues that do not require remediation. These tools can be maintained and understood by the business owners, which allows them to create metrics that are specifically relevant to the business, eliminating a flood of unnecessary alerts.” “We’re interested in using Anodot’s Business Impact Alerts to automate a complicated process we used to manage in-house, which would free up significant resources for us,” said Christina Velzo, director of business intelligence at Ask Media Group. “With Anodot’s platform we can analyze high volumes of traffic across multiple metrics, spot anomalies and take action right away, reducing any potential downtime or business risk.” More information on Influencing Events and Business Impact Alerts is available online. About Anodot Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn, Facebook, and Twitter.

Leader in digital payments Payoneer Calls This Integration a ‘Game-Changer’ April 05, 2021 09:00 AM Eastern Daylight Time REDWOOD CITY, Calif.–(BUSINESS WIRE)–Anodot, the autonomous business monitoring company, and Coralogix, a leading observability platform, have partnered to provide an integrated solution that monitors business operations and applications faster and more accurately than ever before. The integration between Anodot’s business monitoring and Coralogix’s data platform enables customers to dramatically improve how they leverage data to find and remediate issues they would have otherwise missed while solving log maintenance autonomously. One of those customers is Payoneer, Inc., the global payment and commerce-enabling platform which powers growth for millions of small businesses, marketplaces and enterprises, including Amazon, Google and Walmart – for nearly 200 countries and territories. Payoneer delivers a suite of services that include cross-border payments, working capital, tax solutions, risk management and payment orchestration for merchants. With more than five million customers worldwide, Payoneer monitors millions of business and technical metrics to keep their payment gateway running smoothly. Previously, they used traditional monitoring and log analysis solutions that took at least 24 hours to resolve and resulted in high false positive rates. To hasten the digital payment process and improve customer experience, Payoneer integrated Anodot and Coralogix. “This integrated solution is a game-changer for us,” said Yuval Molnar, senior director of production services, Payoneer, Inc. “We have over 1,000 services and must understand their behavior to protect our clients. In doing so, we monitor all logs and autonomously detect errors and false positives. Anodot provides a zoom into the exact Coralogix logs that show the root cause. This has improved our time to resolution by 90% which is a true game changer.” About Anodot Anodot’s Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot’s patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn, Facebook, and Twitter. About Coralogix Coralogix is the modern observability platform for log analytics, metrics, and security. By providing immediate, ML-powered insights and analyzing data by use case, Coralogix enables full observability without any coverage, storage, or cost limitations. Thousands of global-leading companies including Masterclass, Monday.com, BookMyShow, Postman, and PayU use Coralogix to power their businesses. For more information, please visit https://coralogix.com/.