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AI voice operations

Ringlyst / Clientic Voice Agent

A polished AI front-desk product for appointment-heavy teams, with intake, qualification, booking suggestions, and follow-up handoff.

Outcome
A live product surface that turns missed calls and web conversations into structured appointment opportunities.
Next.jsTypeScriptOpenAIVoice AIVercel
Ringlyst AI front desk landing page and live intake console.
Challenge
Service teams lose high-intent leads when staff are busy, closed, or unable to capture full intake context during calls.
Approach
01

Frame the product around appointment-heavy teams such as clinics, salons, hotels, agencies, and local services.

02

Design a live intake console that shows caller intent, priority, source, booking suggestions, and follow-up status.

03

Keep the voice workflow tied to a clear handoff: answer, qualify, book, sync, and summarize.

Project article

Why this project matters.

A short review of the product surface, workflow signal, and portfolio value.

Ringlyst shows the difference between a voice demo and a productized voice workflow. The page is not only a marketing surface; it demonstrates the operating model with voice activity, caller turns, qualification signals, booking suggestion, and follow-up sync.

The strongest portfolio signal is the domain-specific workflow. Instead of promising generic AI calls, the product is built around concrete service-team outcomes: capture demand, qualify urgency, collect visit context, and move a conversation toward a booked appointment.

This is useful as a public portfolio article because it proves the ability to combine product positioning, realtime interaction design, AI workflow structure, and Vercel production deployment into one coherent app.

Proof points

What the system makes visible.

These are the artifacts that make the project usable beyond the first demo.

Live intake console
Lead qualification
Booking suggestion workflow
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