Английская Википедия:Anodot

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Шаблон:Multiple issues Шаблон:Short description Шаблон:Infobox company Anodot is an American data analytics company that uses machine learning and artificial intelligence for business monitoring and anomaly detection.[1][2][3]

History

Anodot was founded in 2014 by David Drai along with Ira Cohen, former Chief Data Scientist at HP. Prior to that, Drai was the CTO at Akamai.[1][4][5] While working as CTO at GetTaxi, he realized that there is a need for real time data analytics. He started working on developing a software that can be paired for data analysis and visualization.[6][7] Drai sought financing to start Anodot and received the seed round of funding of $1.5 million in 2014 from Disruptive Technologies Venture Capital. In the next three years, the company raised three rounds of funding for expansion, bringing the company's total venture capital backing to $27.5 million.[8][9][10]

Anodot is one of the data analytics companies that competes with established firms to provide data analysis and visualization in a real time. The company claims that it started analyzing well over 5.2 billion data points per day within six months of its launch.[11]

In 2018, Anodot announced Andy Fenselau as Chief Marketing Officer and Amit Levi as the VP Head of Product.[12] Later in the year, Anodot partnered with Deloitte Australia, where Deloitte used its technology to process its client's data and gain insights.[13] In 2020, the company announced partnership with Amazon AWS to monitor business metrics.[14]

The company possesses two U.S. patents for algorithms of machine learning-based anomaly detection.[15][16] Anodot has offices in Israel, UK and Australia and has majority of its client base in digital business and telecom industry.[17]

Technology

Anodot launched a data analytics platform that analyzes real time structured metrics data and unstructured log data and it independently detects and correlates anomalies and forecasts business in real time.[18] According to the company, the algorithms are designed specifically to quickly identify the source of anomalies in large data sets, and perform root-cause analysis.[19]

Funding

The company raised $62.5 million in funding by April 2020 with most recent funding Series C round of $35 million led by Intel Capital[20] and included SoftBank Ventures Asia, Samsung NEXT, Aleph and Redline Capital Management.[21][22]

References

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