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Anodot Exits Stealth and Introduces Real-Time Anomaly Detection

Anodot exited stealth, introducing its real-time anomaly detection solution with patented machine learning algorithms for big data.

Pinpointing performance issues and business opportunities in real time, Anodot enables its customers to increase operational efficiency and maximize revenue generation.

The company also announced it closed a $3 million Series A funding round led by Disrupt-ive Partners, bringing total funding in the company to $4.5 million. The company will use the funding to accelerate its product roadmap and expand its sales activity, focusing on the ad tech, e-commerce, IoT and manufacturing industries in the U.S. and EMEA.

Founded in June 2014, Anodot is an analytics and anomaly detection solution that is data agnostic and automates the discovery of outliers in all business and operational data. Anodot’s platform isolates issues and correlates them across multiple parameters to surface and alert on incidents in real time.

“I experienced the data analysis lag problem first hand as CTO for Gett,” said Anodot CEO David Drai. “As a mobile taxi app, SMS text orders were dropped by the carrier, but it could take up to three days to spot critical issues and fix them, costing tens of thousands of dollars per incident. That’s where I got the idea for Anodot — to employ the latest advances in machine learning to detect performance problems automatically and in real time, eliminating the latency.”

Anodot is led by a proven team of three co-founders with strong credentials as entrepreneurs and technologists with deep experience in data science and global-scale SaaS infrastructures.

- CEO David Drai was co-founder and CTO of Cotendo for four years when it was acquired by Akamai for $300 million.

- Chief Data Scientist Dr. Ira Cohen held the same position at HP Software where he led research and development in machine learning and data mining techniques.

- R&D VP Shay Lang has led engineering teams for more than 10 years at leading technology companies.

On the board of directors, the team also includes Anthony Bettencourt, president and CEO at Imperva and a board member at Proofpoint, and Ben Lorica, O'Reilly Media’s chief data scientist and a top influencer on Twitter, as a board advisor.

Features and advantages of Anodot Anomaly Detection include:

- Operates in real time

- Works with any type of metric or KPI and scales to any big data volume

- Uses proprietary patented machine learning algorithms

- Correlates different metrics to help identify root causes of problems and eliminate alert storms

- Simulation capability optimizes alert planning and reduces false positive alerts

- Eliminates the need for time-intensive manual analysis

- Enables non-specialists to gain the insights they want and delivers fast time-to-value

- Provides clear visualizations that help any user to understand what the data is showing them

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Anodot Exits Stealth and Introduces Real-Time Anomaly Detection

Anodot exited stealth, introducing its real-time anomaly detection solution with patented machine learning algorithms for big data.

Pinpointing performance issues and business opportunities in real time, Anodot enables its customers to increase operational efficiency and maximize revenue generation.

The company also announced it closed a $3 million Series A funding round led by Disrupt-ive Partners, bringing total funding in the company to $4.5 million. The company will use the funding to accelerate its product roadmap and expand its sales activity, focusing on the ad tech, e-commerce, IoT and manufacturing industries in the U.S. and EMEA.

Founded in June 2014, Anodot is an analytics and anomaly detection solution that is data agnostic and automates the discovery of outliers in all business and operational data. Anodot’s platform isolates issues and correlates them across multiple parameters to surface and alert on incidents in real time.

“I experienced the data analysis lag problem first hand as CTO for Gett,” said Anodot CEO David Drai. “As a mobile taxi app, SMS text orders were dropped by the carrier, but it could take up to three days to spot critical issues and fix them, costing tens of thousands of dollars per incident. That’s where I got the idea for Anodot — to employ the latest advances in machine learning to detect performance problems automatically and in real time, eliminating the latency.”

Anodot is led by a proven team of three co-founders with strong credentials as entrepreneurs and technologists with deep experience in data science and global-scale SaaS infrastructures.

- CEO David Drai was co-founder and CTO of Cotendo for four years when it was acquired by Akamai for $300 million.

- Chief Data Scientist Dr. Ira Cohen held the same position at HP Software where he led research and development in machine learning and data mining techniques.

- R&D VP Shay Lang has led engineering teams for more than 10 years at leading technology companies.

On the board of directors, the team also includes Anthony Bettencourt, president and CEO at Imperva and a board member at Proofpoint, and Ben Lorica, O'Reilly Media’s chief data scientist and a top influencer on Twitter, as a board advisor.

Features and advantages of Anodot Anomaly Detection include:

- Operates in real time

- Works with any type of metric or KPI and scales to any big data volume

- Uses proprietary patented machine learning algorithms

- Correlates different metrics to help identify root causes of problems and eliminate alert storms

- Simulation capability optimizes alert planning and reduces false positive alerts

- Eliminates the need for time-intensive manual analysis

- Enables non-specialists to gain the insights they want and delivers fast time-to-value

- Provides clear visualizations that help any user to understand what the data is showing them

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...