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Everyring.ai

For service businesses, every unanswered call is a leaked customer. Everyring.ai catches them, ranks them, and uses Claude to draft the SMS or email that earns the call-back — in seconds, not hours.

Category  AI · CRMStack  Next.js · TypeScriptLLM  Anthropic ClaudeStatus  Live
Everyring.ai screenshot

The problem

For trades, clinics, and service businesses, the phone is still the single most valuable lead source. The painful truth is that 30–50% of those calls go unanswered — and the lead is gone within the hour, often forever, because they called the next number on the search page. Existing answers (call centres, IVR mazes) move the cost without solving the problem.

What we built

Everyring.ai integrates with the business’s phone system or CRM to capture missed-call events with caller ID, timestamp, and any context the system has. It scores each missed call by recency, repeat-caller status, and prior history, then prompts the operator with a Claude-drafted SMS or email tailored to what we know about the caller. The operator approves, edits, or rejects in two taps; sends happen in seconds.

The AI angle

Two prompts. The first picks the right channel and tone (text-back vs email vs voicemail-drop) based on time of day and caller history. The second drafts the actual message in the business’s voice, anchored to a short brand brief. The operator stays in control — the AI is the speed.

How it’s used

  • Trades (electricians, plumbers, locksmiths) where speed-of-response is the primary buying signal.
  • Clinics and salons turning missed calls into booked appointments.
  • Service teams recovering inbound interest the receptionist couldn’t catch.

What it taught us

The product’s value lives in the first 90 seconds after a missed call. Anything that gets in the way — an extra confirmation, a slow page load, a draft that needs heavy editing — destroys the win rate. We optimised everything for that 90-second window.

Why the operator stays in the loop

The obvious next step is to auto-send the drafted message and skip the approval tap entirely. We didn’t build it that way, because a trade or clinic’s reputation rides on every outbound message, and an AI draft that’s slightly wrong — the wrong name, a tone that reads as pushy, a promise the business can’t actually keep — costs more than the seconds saved by removing the approval step. Two taps is fast enough to preserve the speed advantage over a human callback, while still putting a person between the model and the customer for every message that goes out under the business’s name.

Scoring calls by recency and repeat-caller status also does real work: a caller who’s rung twice today is a different priority to a first-time enquiry from last night, and the queue reflects that instead of treating every missed call as equally urgent.

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