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Observo AI

AI-powered data pipeline for security & DevOps telemetry optimization

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Observo AI Description

Observo AI is an AI-powered data pipeline platform designed for security and DevOps teams to optimize telemetry data management. The platform processes security logs, metrics, and observability data to reduce data volume, control costs, and improve threat detection capabilities. The platform uses artificial intelligence to automate data pipeline operations including parsing, filtering, routing, and enrichment of security and operational data. It enables organizations to filter noisy security data, reduce SIEM ingestion costs, and accelerate threat detection and incident response times. Observo AI supports SIEM migration capabilities, allowing organizations to compare multiple SIEM platforms side-by-side with live data and migrate between security tools. The platform includes multi-destination data routing to send optimized data to SIEM, SOAR, and data lake destinations from a single collection point. The platform provides AI-powered sentiment analysis for threat hunting, automated parsing for custom log onboarding, and pattern recognition for sensitive data compliance including GDPR, CCPA, and PCI requirements. It includes a security data lake capability for long-term storage of security data with natural language search and instant rehydration features. Observo AI offers metrics optimization to eliminate unused metrics, filter excessive tags, and aggregate noisy data. The platform integrates with over 500 sources and destinations for data collection and routing. It operates as a cloud-based service that processes data at scale for enterprise security and DevOps operations.

Observo AI FAQ

Common questions about Observo AI including features, pricing, alternatives, and user reviews.

Observo AI is AI-powered data pipeline for security & DevOps telemetry optimization developed by Observo AI. It is a Security Operations solution designed to help security teams with AI Powered Security, SIEM, Threat Detection.

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