Eyer: AI Observability Platform
Eyer helps operations, DevOps, and SRE teams identify system deviations without manual threshold setting. It is designed for businesses managing complex IT or OT environments that need to reduce alert noise.
At a glance
- Category
- Software Development
- Best for
- DevOps and SRE teams, Operations managers, IT and OT environment managers
- Pricing
- Pricing is scoped to the specific deployment based on metrics, environments, and support needs. A 4-week free trial is available with no credit card required.
- Key use cases
- IT and Cloud Operations, Boomi Integration Monitoring, OT and Manufacturing, Aquaculture Monitoring
- Integrations
- Prometheus, Telegraf, InfluxDB, Boomi, REST APIs
- Official website
- eyer.ai
Eyer is a headless AI anomaly detection platform designed for time series data. It is built for operations teams managing complex environments across IT, manufacturing (OT), and specialized sectors like aquaculture who need to identify signals within large volumes of monitoring data.
The platform works by autonomously learning normal behavior for every ingested metric, which supports the removal of manual threshold configuration or the need for data scientists to write rules. When a deviation occurs, its correlation engine maps relationships across systems to provide root cause direction.
Buyers should note that the tool is API-first and headless, meaning it is designed to integrate into existing technology landscapes. Potential users may test the platform by sharing historical data for a preliminary analysis before moving to a live trial.
Key Features
Learns normal behavior across time series metrics automatically without requiring manual threshold configuration.
Maps relationships between systems and metrics to identify upstream and downstream effects during an incident.
Provides alerts that point toward the cause of an anomaly rather than just the symptom.
Connects to existing infrastructure via open APIs to ingest data without requiring proprietary sensors.
Includes a Model Context Protocol server to connect anomaly detection output to LLMs or AI agents.
Use Cases
Monitoring infrastructure and service performance to help reduce alert fatigue and identify gradual service degradation.
Detecting drift in process execution times and throughput in Boomi environments.
Identifying equipment drift and process deviations in operational technology environments to support downtime prevention.
Correlating water quality, feed, and sensor data to detect mortality signals or equipment deviation.
Best For
Integrations
Pricing
Pricing is scoped to the specific deployment based on metrics, environments, and support needs. A 4-week free trial is available with no credit card required.
FAQ
Eyer is a headless AI anomaly detection platform for time series data that automatically learns normal behavior across metrics to alert teams of meaningful deviations.
No, the platform is designed to be autonomous, building and maintaining baselines without requiring data scientists or manual rule writing.
Pricing is scoped based on the number of metrics, environments, and support requirements of the specific deployment.
Yes, a 4-week free trial is available, and the evidence indicates no credit card is required to start.
Source category: Software Development
Source subcategory: Observability Platform
