A smarter answering service that turns missed calls into structured, actionable summaries — built to solve a real problem I was experiencing as a busy professional.
Standard voicemail is passive and slow. Calls go unanswered, you lose the context of why someone called, and the callback number is buried somewhere in a recording you have to listen to in full before you can act. Important calls slip through. Cold calls waste time with no filtering. The system hasn't meaningfully improved in decades.
I wanted to fix this for myself: stop managing voicemail reactively and treat every missed call as a structured piece of information I can act on immediately.
When a call comes in and goes unanswered, an AI assistant picks up, greets the caller, and records their message. The moment the call ends, the recording is transcribed, the key details are extracted by an AI model, and a structured summary is delivered to my inbox — within 30 seconds of hang-up.
No app to open. No recordings to scrub through. Just a clear, actionable email every time someone calls.
Every missed call generates one email containing:
- Caller name — as stated by the caller
- Reason for calling — a one or two sentence AI summary of their stated purpose
- Callback number — extracted from the message, with caller ID as a fallback
- Call duration — total length of the recording
- Full transcript — the complete verbatim message, available when you need the detail
Every call is accounted for. Nothing to chase down.
- Real use exposes what prototypes don't. Building for your own daily workflow forces a level of reliability and edge-case handling that demo-mode development never surfaces. When it's your actual phone calls, failure isn't theoretical.
- AI summarisation quality is a prompting problem. The difference between a genuinely useful one-line summary and a shorter version of the transcript comes down to how precisely you instruct the model. Getting this right took iteration against real calls.
- Shipping and using beats planning and testing. Running on live data every day surfaces improvements within days. The feedback loop of real personal use is faster than any structured test plan I could have designed.
- Caller history and profiles — recognise repeat callers, build named profiles for known contacts, and include history context in the summary.
- Urgency detection — flag time-sensitive messages automatically and trigger an immediate SMS alert so genuinely urgent calls are never missed.
- Self-serve onboarding — the step that makes this available to other professionals, not just me. Building the signup and configuration flow to remove all manual setup and unlock commercial use.
Interested in how this works or where it's heading? Get in touch.