Autonomous Reliability

Your reliability agents shouldn't need a human to tell them what's wrong.

Causely gives your agents a live causal model of your system so they can detect, diagnose, and act before users notice.

In Production

Martin Roberts, Cloud & Platform Operations Lead at Fountain, uses Causely to continuously monitor his systems and catch issues before they escalate. When Causely detects a problem, it sends a structured alert containing the diagnosis, the affected services, and the required fix, directly to a background agent with repo access. The agent opens a PR based on that diagnosis.

Martin puts it simply: what used to take hours now takes minutes.

In this recording, Martin walks through his setup end to end: his use of Open-Inspect as the background agent framework, and how Causely's causal model produces the diagnosis the agent acts on.

How It Works
01

Deploy Causely

Causely builds a live causal model of your system — services, dependencies, and failure paths.

02

Connect your agent via MCP

One config snippet. Works with Claude, Cursor, Codex, and any MCP-compatible agent.

03

Your agent acts

Root cause, blast radius, and safe actions. Delivered to your agent the moment something changes.

100%fault accuracy
48%fewer tokens
63%faster time to answer

Based on 72 experiments across four agent frameworks.