Handling issues in the cloud are mission-critical and need to be handled immediately to keep the system up and stable. DevOps teams spend too much time detecting and resolving cloud issues, because they are using separate, manual IT operation tools to find the source of these issues. They could be prevented as they were primarily caused by human errors, power outage, network problems and configuration issues. This is where qaTT comes in.


qaTT is an ML engine that auto-detects metrics from multiple resources (logs, traces, ticking system and APM solution), classifies them, and using historical data can provide playbooks and automation to cut the issues faster and smarter!

With qaTT, outages caused by human errors are prevented, time dedicated to solving issues is saved, and monitoring and resolving processes are automated. qaTT enables DevOps teams to respond more quickly - even proactively - to slowdowns and outages, with a lot of less effort.


The market of AIOps infrastructure and digital applications monitoring tools is expected to increase 6X within the next 5 years, reaching $24B by 2025 according to many market research companies (Gartner, researchandmarkets, etc.)


Competitors' solutions such as New Relic, Logzio and Moogsoft are using multiple separate, manual IT operation tools to find the Root Cause Analysis for issues and fix them. Unlike our competition, we offer a single and fully automated solution.



Co-Founder and CEO


Co-Founder and CTO

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