Blueprint · Voice AI · Telephony

AI voice platform for calls, follow-ups and CRM updates

A voice agent that answers or places calls, understands the conversation with an LLM, takes actions through tools and writes the outcome back to your CRM.

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Layers

AnalyticsCost, outcomes, escalations
CRMOutcomes written back
ToolsBooking, lookups, hand-off
LLMConversation, retrieval, memory
SpeechSTT and TTS, low latency
VoiceTwilio / SIP, streaming audio

Built for

Sales, support and operations teams that handle high call volumes and want software, not scripts, to carry the routine ones.

Typical timeline

First agent in production in 6 to 10 weeks

Typical team

3 engineers: real-time, AI, integration

Practices

What it includes

The components, and what each one is for.

01
Telephony layer
Inbound and outbound calls on Twilio or SIP, with recording, transfer and real-time streaming of audio.
02
Speech and understanding
Streaming speech-to-text, an LLM with your knowledge base behind it, and low-latency text-to-speech.
03
Tools and actions
Booking, lookups, ticket creation and hand-off to a human, exposed to the model as safe, typed tools.
04
CRM and analytics
Every call summarised and written to the CRM; dashboards for outcomes, cost per call and escalation rate.
05
Evaluation and guardrails
Test sets, transcripts review, refusal rules and cost caps so the agent behaves in production.

Stack we reach for

Twilio
WebRTC
OpenAI
Deepgram or Whisper
ElevenLabs
Node.js
PostgreSQL
LangChain
Grafana

How it would run

Discovery first, then a pilot you can measure.

Every blueprint starts as a two-week discovery that adapts it to your hardware, your data and your constraints. The pilot that follows is scoped to prove the riskiest assumption first.

Read about our process

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