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What is Causely?

Causely is an AI reliability engine that continuously understands why your systems behave the way they do. During incidents it delivers precise insights pinpointing the cause that explains the symptoms, and it prevents future incidents using the same model-driven inference.

Built on a causal reasoning engine (CRE), Causely transforms observability data into explainable, actionable insight.

Unlike observability or AIOps tools that guess correlations after an alert, Causely performs causal inference in real time to maintain reliability across complex, fast-changing systems.

welcome to causely

What Causely Provides​

Causely includes everything you need to reason about reliability in production: during active incidents and before they happen:

  • Automatic causal analysis: Agents and the mediation layer collect from your existing telemetry sources and convert signals into a stream of active/inactive symptoms.

The CRE then performs probabilistic inference over this symptom stream and your live models to pinpoint the underlying cause and surface emerging risks.

  • Automatic impact assessment & blast-radius mapping: Causely discovers and maintains a topology graph of services and dependencies, then infers which services, endpoints, databases, and SLOs are affected and how effects propagate—so you can prioritize what to fix first.

  • SLO definition and tracking: The Attribute Dependency Model encodes constraints and inter-attribute relationships (latency, throughput, utilization, etc.), tying SLO drift back to the likely upstream cause and enabling pre-emptive action.

  • Topology & dependency discovery: Continuous ingestion/reconciliation of topology from traces and inventories builds a real-time system graph (connectivity, layering, composition) that underpins impact analysis and propagation reasoning.

  • Fast, low-lift enablement: Deploy Agents and connect existing telemetry; by default, Causely can auto-instrument using OpenTelemetry, so you start diagnosing in minutes—no manual rule writing.

  • Zero-trust, production-grade design: The mediation layer keeps raw telemetry local and sends only distilled symptom/state signals for reasoning—minimizing data transfer and preserving privacy/compliance.

  • Ask Causely: Query Ask Causely with natural language to get insights about your system. LLM understanding is grounded by the causal engine for precise, explainable answers.

  • Remediation prioritization & action handoff: The engine prioritizes remediation based on inferred causes and blast radius, and delivers insights into your workflows (Slack, Jira, Opsgenie, Grafana, etc.) to drive fixes quickly.

When to Use Causely​

  • You’re buried in alerts and want to cut straight to what matters. Causely filters through floods of signals and surfaces only the few that are causally connected to actual system degradation.

  • You need to explain a production regression and stop it from spreading. When an incident hits, Causely reasons over current system symptoms and topology to isolate the triggering factor, trace propagation, and show where to intervene first.

  • You want answers, not breadcrumbs. Instead of following metrics by hand, Causely provides structured causal explanations you can trust, grounded in model-based reasoning rather than correlations.

  • You want to anticipate the next failure. Even outside incidents, Causely continuously reasons over dependencies and performance attributes to surface emerging risks, helping you act before SLOs drift.

  • You need reliability at scale. In environments with hundreds of services or fast-moving deployments, Causely gives you system-wide awareness without manual dashboards or playbooks.

How to get started​

To get started with Causely, you can follow the Quick Setup Guide.

If you want to explore Causely without installing the agent, you can use the Causely Sandbox.

What You'll Find in This Documentation​

  • Getting Started: Deploy Causely in minutes with OpenTelemetry + eBPF
  • Installation: Learn how to install the Causely agent.
  • Configuration: Learn how to configure Causely.
  • Telemetry Sources: Connect your telemetry sources to maximize symptom coverage and dependency discovery.
  • Workflow Integrations: Act faster by pushing insights directly into the tools your team uses every day.
  • Ask Causely: Interact with Causely Copilot through the web interface, Slack, or directly in your IDE using our MCP server.