Senser emerged from stealth with $9.5 million in seed funding to launch an AIOps platform that leverages Extended Berkeley Packet Filter (eBPF) technology to provide enterprises with deep insights into their complex cloud and IT environments.

The seed round was led by Eclipse with participation by Amdocs and other private investors.

Harnessing the power of groundbreaking eBPF technology, Senser's platform enables dynamic, non-intrusive data collection with zero instrumentation or configuration required. The platform also leverages machine learning (ML) to deliver automated insights into root cause and business impact when issues like outages or service degradations arise. Senser's AI-powered chatbot enables users from a variety of technical backgrounds to quickly answer critical questions about their production environment using only natural language prompts.

"Downtime costs enterprises an average of $1 million per hour and a long-term loss of customer trust," said Amir Krayden, Co-Founder and CEO of Senser. "We built Senser to make it easy for SRE and DevOps leaders to go past alerts and dashboards and solve issues quickly. The average Senser customer reduces mean time to detect (MTTD) by 83% – an outcome made possible because eBPF enables immediate visibility across production systems with no overhead, and ML delivers answers, rather than alert floods."

In addition to identifying service degradations, Senser's technology helps companies manage the health and performance of their production environment more broadly. This includes identifying hidden drivers of cloud computing costs and leakage of potentially sensitive assets.