Eyer

Eyer is an AI-powered observability and AIOps platform designed to simplify the monitoring and management of complex software systems. Its core value proposition lies in transforming raw time-series data and metrics into actionable insights through machine learning, enabling teams to proactively detect anomalies, understand system behavior, and automate incident response. By learning the normal patterns of an environment, it reduces alert fatigue and provides context-rich notifications that help engineers resolve issues faster, ultimately improving system reliability and operational efficiency.

Key features: The platform offers automated anomaly detection that identifies deviations from learned baselines without manual threshold setting. It provides contextual alerting that correlates alerts with environmental changes and relevant logs. Users can build custom scripts and leverage integrated machine learning models for predictive analysis. The platform supports scalable metrics ingestion and real-time monitoring, integrates with tools like Grafana for dashboard visualization, and includes an AI chatbot for operational queries to assist in triage and investigation processes.

What sets Eyer apart is its headless, API-first architecture, which allows for deep integration into existing DevOps toolchains and custom workflows without being tied to a specific UI. It emphasizes environment learning, where its models continuously adapt to system behavior, making it particularly effective for dynamic cloud-native environments. Technically, it supports extensive API integrations, allowing teams to pull data from various sources and push insights to communication and ticketing systems, creating a closed-loop automation system for incident management.

Ideal for DevOps teams, SREs, and platform engineers in technology companies, SaaS providers, and financial services who manage large-scale, distributed systems. Specific use cases include monitoring microservices performance, automating root cause analysis for production incidents, managing cloud infrastructure costs by detecting inefficiencies, and ensuring compliance through continuous performance auditing. It is also valuable for product teams needing to understand how new features impact system health and user experience.

The platform operates on a freemium model. A free tier is available with basic monitoring capabilities and limited data retention. Paid plans start from $199 per month, offering advanced features like unlimited metrics, longer data history, custom ML models, priority support, and enhanced integration options for enterprise-scale deployments.