NestVoice AI Calling Suite
An end-to-end AI voice platform that qualifies inbound leads, books discovery calls and dispatches follow-ups — with no human agent in the loop.
- Client
- NestVoice
- Industry
- AI & SaaS
- Engagement type
- Product design, AI pipeline engineering, telephony integration, backend and cloud
- Technology
- WebRTC, SIP / PSTN telephony, Streaming speech-to-text +5 more
- Year
- 2025
- Platforms
- Web, API
01 — Context
Where this started.
NestVoice was founded on the observation that the first human a prospect speaks to at most companies is a sales rep who has not yet earned the conversation. Qualification calls follow a script that an AI could handle more consistently, at any hour, without staffing constraints.
02 — Challenge
The hard part.
The core engineering challenge was latency. A voice agent that hesitates for three seconds sounds broken, not intelligent. Every component in the chain — speech recognition, LLM inference, text-to-speech synthesis — had to be chosen and tuned for the round-trip time a real phone call demands.
03 — Strategy
What we decided.
Rather than building a chatbot with a phone number, we designed the system around call flow states: greeting, qualification, objection handling, booking, and handoff. Each state has a bounded set of expected responses, which made it possible to pre-cache common utterances and shorten the perceived lag without actually reducing model quality.
04 — Experience
How it works for the person using it.
From the prospect's side the interaction is a professional phone call. From the operator's side it is a dashboard: live call transcripts, a configurable qualification script, calendar integration for booking, and a CRM connector that writes the outcome back. Operators can listen to flagged calls and feed corrections back into the prompt layer.
05 — Engineering
How it is built.
Telephony runs over a WebRTC stack with a SIP trunk for inbound PSTN calls. Speech-to-text uses a streaming transcription API so the model starts reasoning before the caller has finished speaking. The LLM layer is stateless per utterance but maintains a call-level context object so responses remain coherent across the full conversation. Calendar availability is checked in real time during the call, so a booking confirmation is given before the call ends, not in a follow-up email.
- WebRTC
- SIP / PSTN telephony
- Streaming speech-to-text
- Claude
- Text-to-speech synthesis
- Node.js
- PostgreSQL
- Vercel
06 — Feature stories
The decisions that mattered.
-
Sub-two-second response latency
The full pipeline from speech detection to audio playback runs in under two seconds on average, which is within the natural pause range of a human conversation.
-
Configurable qualification scripts
Operators define the qualifying questions and acceptable answer ranges in a no-code interface. The AI adapts the conversation to elicit those answers without reading from a visible script.
-
Real-time calendar booking
Available slots are fetched mid-call and confirmed before hang-up. A confirmed booking fires a calendar invite and a CRM record simultaneously.
-
Call transcript and coaching layer
Every call is transcribed, scored against the qualification criteria, and flagged for human review when it deviates. The flagged examples become prompt-improvement data.
07 — Results
What we can prove.
- Live
- Operating on inbound lead queues
- <2s
- Average voice response latency
- 24/7
- Coverage with no staffing cost
Source: NestVoice production deployment
Source: Internal call log metrics
Source: NestVoice deployment documentation
Only verifiable figures appear here. We do not publish uplift percentages or revenue claims we cannot evidence, and we do not restate a client's internal numbers as our own.
08 — Ownership
What was handed over.
At launch, everything below transferred to NestVoice. Nothing in this product depends on DevXAI to keep running.
- Full Git repository with commit history
- Infrastructure and store accounts in the client’s own name
- Architecture and deployment documentation
- Walkthrough session with the client’s team
- 30-day post-launch defect warranty
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