Anodot announced $8 million in funding led by Aleph Venture Capital with participation by Disruptive Technologies L.P., bringing Anodot’s total funding to $12.5 million.
The funds will be used to expand the company’s global sales and operations and meet demand for its service.
Anodot was co-founded by David Drai, the former CTO of GetTaxi and co-founder of Contendo (acquired by Akamai), Shay Lang, former VP Engineering at Trustwave, and Dr. Ira Cohen, former Chief Data Scientist at HP.
Anodot brings machine learning and real-time streaming data together to identify, report, and visualize business incidents as they occur, enabling its customers – often Business Intelligence analysts serving all aspects of a company’s operations – to quickly and effectively manage crises and uncover business opportunities. Instead of the usual days or weeks it currently takes companies to detect and understand data anomalies, Anodot’s SaaS solution is capable of identifying and notifying customers about issues in mere minutes.
“Today’s digital businesses operate in dynamic environments, but Business Intelligence analysts are hampered by their existing static tools, so they are the last to know when something happens that can impact their business. As a former CTO, I’ve seen how the inability to identify business incidents and delayed reactions can turn manageable issues into major crises, from the extended time it takes to recognize an issue to the even longer period necessary to understand the cause,” said David Drai, CEO and co-founder of Anodot. “Our patented algorithms automatically learn the normal behavior of any time series data – MixPanel, Google Analytics, Graphite, and so on – and then rapidly identify anomalies which typically indicate business incidents. Seasonality is a huge challenge for the industry, and the subtle changes that wouldn’t trigger static thresholds are caught by Anodot.”
“The promise of Big Data and Business Intelligence is vast, but so few companies have unlocked its potential. Anodot is channeling the most advanced machine learning algorithms to make Business Intelligence real-time and its potential impact is enormous,” said Eden Shochat, Founder & Partner at Aleph. “Aleph is focused on finding companies who rethink stagnant industries that are ripe for change, and we’re thrilled to be joining Anodot on their journey.”
“From the beginning, we believed in Anodot’s vision of revolutionizing the BI market, and Anodot continues to move the needle for businesses looking for the best analytic capabilities,” said Tal Barnoach, General Partner at Disruptive “Disruptive is committed to finding disruptive ideas, technologies and products that change existing habits and the way users interact with products, and Anodot is a great fit for this mission.”
The Latest
For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...
FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...
Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...
While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...
A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...