Observo AI: Revolutionizing Telemetry Control with AI
The AI boom has led to an explosion of data in today’s digital landscape. With AI models requiring massive datasets to train on and the continuous generation of telemetry data from workloads, organizations are facing challenges in keeping up with the sheer volume of information. This has made it harder for them to detect and respond to incidents in a timely manner. Enter Observo AI, a California-based startup that is changing the game in telemetry control.
The Problem: Rule-Based Telemetry Control
Modern enterprise systems generate petabyte-scale operational data regularly. However, not every data point is a critical signal for incident identification. This results in teams being overwhelmed with data to filter through for response systems. Traditional observability tools have rule-based filters to reduce noise, but these approaches don’t adapt well to surging data volumes. This can lead to missed threat detection and response.
Observo AI addresses this gap by optimizing operational data pipelines using AI. Developed by Gurjeet Arora, who previously led engineering at Rubrik, Observo sits between telemetry sources and destinations, using ML models to analyze incoming data streams. It filters out noise and routes high-importance signals to the appropriate systems, be it incident alert and response or a data lake. The platform evolves its understanding continuously, adjusting filtering rules in real-time to keep up with emerging threats and anomalies.
The Value to Enterprises
Observo AI has quickly gained traction with over a dozen enterprise customers, including Informatica, Bill.com, and Rubrik. The platform has seen significant revenue growth quarter-over-quarter, attracting customers from competitors like Cribl. Observo’s use of AI sets it apart, optimizing data pipelines to reduce noise by 60-70%, compared to competitors’ 20-30%.
One case study highlighted how Observo helped a large North American hospital reduce log volumes by over 78% while fully onboarding critical data, leading to a 50% reduction in total Sentinel costs. Another global data and AI company saw a 70% reduction in log volumes and a 40% decrease in Observability and SIEM costs. These improvements allowed teams to prioritize critical alerts and reduce mean time to resolve incidents.
Plan Ahead
Observo AI plans to accelerate its go-to-market efforts and compete with industry giants like Splunk and DataDog. The company aims to enhance its product with more AI capabilities, anomaly detection, data policy engine, analytics, and additional connectors. With the global observability tools and platforms market expected to grow to $4.1 billion by 2028, Observo AI is well-positioned to lead the charge in revolutionizing telemetry control with AI technology.
