Causal Reasoning Software with Causely’s Francis Cordon
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What Is a Causal Model in Observability?
A causal model isn’t an LLM. Here’s what causal models are, how they differ from rules engines and correlation, and why agents need them.
Your agents trust your telemetry. Should they?
Your agents read telemetry fast and literally. OllyGarden shows how missing, contradictory, and split data quietly produce wrong answers, and Causely shows why even clean data needs causal context before an agent opens the wrong PR.
Causely Feature Demo: Diagnosing Failures in an Agentic App
Causely maps an agentic app's agent sessions, MCP tools and services, then traces failed runs to the cause: a broken tool contract or an MCP server exception.
Causely Upgrades Its MCP Server So Background Agents Are Faster to Deploy, Easier to Trust, and Cheaper to Run
Causely’s MCP server upgrades help background agents deploy faster, produce traceable decisions, and use fewer tokens, with new open source examples.