Put an AI agent to work inside CallRail

What a Fleece agent does with CallRail

CallRail turns phone calls into marketing data — tracking numbers per campaign, source and keyword-level attribution, call recordings and transcripts, and form tracking. It tells you which ad drove a call and lets you listen back. But a transcript sitting in a dashboard doesn't route the lead, update the CRM, recover the missed call, or tell marketing what callers actually asked. Someone still has to listen, classify, and act on every call. A Fleece agent takes on exactly that work — reading each transcript and doing something useful with it.

Under the hood, the connection runs through managed OAuth — you authorize CallRail once, and Fleece stores, scopes, and refreshes tokens securely; you never paste an API key, and you can revoke access from either side at any time. The agent can read call recordings and transcripts, source and keyword attribution, tracked-number activity, and form submissions. Real-time triggers let it react the moment a call comes in or is missed, and scheduled flows let it review the week — a Monday attribution digest, a call-quality theme summary, a missed-call recovery sweep — on a rhythm you set.

What makes this different from CallRail's own reports and notifications is judgment. A report tells you a call happened and where it came from; a notification pings you that it did. Neither reads the content of the call and decides what to do. A Fleece agent reads the actual transcript, classifies it — new lead, existing customer, or spam — and acts across the tools where the work lives: creating a HubSpot contact, drafting a Gmail follow-up, logging attribution to Google Sheets, alerting sales in Slack. Because Fleece agents work as a hierarchy, a lead agent can delegate the CRM update to one child agent and the follow-up drafting to another, then report back. Anything that reaches a lead or writes to your CRM waits for your one-click approval.