Shmuel Kliger and Ellen Rubin, Causely
1) Tell us about your background and how Causely was started?
Shmuel was thinking about how to automate IT environments to eliminate the need for human troubleshooting, including root cause analysis and optimization problems. Ellen was thinking about her AWS experience, where teams were caught up in complex service issues that often required hours or days of troubleshooting. Together, they determined there was an opportunity to build a new venture that focused on capturing causality in software – something that has not yet been done in the IT industry, which relies on human expertise and lots of data to address application failures and optimization of the application environment.
2) How is AI changing the industry?
Causely is a pioneer in causal AI for IT. Causal AI is an artificial intelligence system that captures, represents, explains, and analyzes cause and effect. To date, the IT industry has relied on correlation and anomaly detection as the leading AI approaches, but these don’t address causation. While causal AI has been known in the academic world for several years, no one has applied this technology to complex and dynamic IT environments. Causely’s groundbreaking causal AI platform enables end-to-end automation, from observability through orchestration and remediation.
3) What are the key problems Causely is addressing?
For years, the IT industry has struggled to make sense of the overwhelming amounts of data coming from dozens of observability platforms and monitoring tools. In a dynamic world of cloud and edge computing, with constantly increasing application complexity and scale, these systems gather metrics and logs about every aspect of application and IT environments. In the end, all this data still requires human troubleshooting to respond to alerts, make sense of patterns, identify root cause, and ultimately determine the best action for remediation. This process, which has not changed fundamentally in decades, is slow, reactive, costly, and labor-intensive. As a result, many problems can cause end-user and business impact, especially in situations where complex problems propagate across multiple layers and components of an application.
4) What have you enjoyed or what do you look forward to about working with Tau Ventures?
From the first discussions, it’s been clear that the Tau team is smart, entrepreneurial, and intellectually engaged. We very much enjoyed their insightful questions and advice. As we scale the team and bring on more design partners and early customers, we are looking forward to Tau’s hands-on approach and network of smart advisors to help us grow!
