Case Study: DeductiveAI achieves up to 90% faster root cause analysis with Akka

DeductiveAI accelerates root cause analysis by 90% with Akka

DeductiveAI, an AI-native observability company, faced the challenge of automating root cause analysis for large, distributed systems. Their engineering teams needed to correlate billions of time series, petabytes of logs, and hundreds of millions of lines of code changes across various sources, a manual process that took hours during live incidents. They turned to the vendor Akka to build a solution that could handle this stateful, long-running, and concurrent workload at scale.

Using the Akka Agentic AI Platform, DeductiveAI built a multi-agent system that autonomously investigates incidents. The solution ingests telemetry in real time to build a knowledge graph, allowing agents to detect and rank probable causes. This implementation resulted in root cause analysis becoming up to 90% faster and reduced the average time-to-mitigation by 70%. The system, operated by a 10-person team, now handles billions of time series and remains stable under peak event volume.

DeductiveAI