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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.
Year
2025
Role
Product architecture · Full-stack · AI
Category
AI voice operations
Status
Live · shipped
Next.jsTypeScriptOpenAI RealtimePrismaTwilioPostgreSQL
01Outcome
Reception load dropped while answer quality stayed consistent — every call produces a structured record instead of a sticky note.
24/7
Call handling
96%
Intake accuracy
<1.2s
Handoff latency
+38%
Booking lift
02The challenge
Appointment-heavy teams lose revenue on missed and half-captured calls. Existing IVR flows feel robotic, and human receptionists cannot triage, qualify, and book at the same time during peak hours.
03Approach
- 01
Designed a conversation state machine so intake, qualification, and booking stay deterministic even when callers ramble.
- 02
Built a live agent console that streams transcript, intent, and confidence, letting a human take over mid-call without losing context.
- 03
Structured every call into a typed record — service, urgency, preferred slots, follow-up owner — written straight into the CRM.
- 04
Added guardrails for medical, pricing, and legal questions with clean escalation paths instead of hallucinated answers.
04Build context
Stack in production
Next.jsTypeScriptOpenAI RealtimePrismaTwilioPostgreSQL
Delivery shape
- Discovery & workflow map
- Sliced delivery, weekly demos
- Perf + cost verification
- Documented handoff
10Get in touch
Bring the product pressure,
the constraints, and the
expected business outcome.
Send the desired outcome, the users, the current bottleneck, the stack, and the timeline. You'll get a practical senior engineering path for the build — not a brochure.