See AnoSys in Action

Your unified command center. The home screen gives you a real-time snapshot of platform usage — data stored, data processed, AI tokens consumed, active pipelines, and team members — all at a glance. Interactive charts below forecast your storage footprint and processed data trends, so you're never caught off guard.

Data collection starts with pixels. Create and manage ingestion endpoints for any data source — website traffic, advertising impressions, Claude Code sessions, or industrial sensor data. Each pixel is fully configurable with custom field mappings, archival toggles, and dedicated schema types.

Once your data is flowing, the Dashboard Wizard does the heavy lifting. In three simple steps — Summarization, Analysis, and Recommendation — AnoSys's AI engine profiles your data, identifies meaningful patterns, and automatically generates dashboards tailored to your dataset. Select a source, pick a time range, and let the platform build your first dashboards for you.

All your dashboards live in one organized gallery. Pin your favorites for quick access, browse across projects — from network traffic monitoring to OpenAI traces to executive overviews. Need a new one? The "Add New Dashboard" button is always one click away.

Drill into a live infrastructure monitoring dashboard. Protocol distribution in doughnut charts, error tracking with stacked bars, total packets trending over time, traffic rate in Mbps, IP count analysis, and a heatmap of top communicating IPs. Every widget is interactive — hover for details, adjust time ranges, or add new elements on the fly.

Beyond traditional dashboards — visualize how your AI agents execute. This directed graph maps agent workflows, handoffs, and responses as execution spans with timing data and parent-child relationships. Agentic AI observability at its finest.

Multiple visualization types in one graph engine. A timeline view shows agent execution durations and nested spans. Switch to a multi-series line graph with an interactive range selector — perfect for monitoring request rates, error counts, or any time-series metric.

Define and manage data processing jobs. Flag suspicious users by tracking risky IPs, monitor OpenTelemetry records for Kubernetes errors, or let an LLM perform root cause analysis automatically. Each unit can be cloned, edited, or parameterized to fit your workflow.

Three alerting methods to match any use case: Simple Alerting for basic thresholds, Rule-Based Triggers for data-driven logic, or AI Triggered for fully automated anomaly detection. Route notifications to Slack, email, or any webhook — with zero-noise suppression when queries return no results.

Pipelines tie everything together. View all your data processing workflows with active toggles, execution schedules, run durations, and status indicators. Run any pipeline on demand, review logs, or jump into the Pipeline Builder to create new multi-step processing flows. From ingestion to insight, on autopilot.