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Qzentra

Capability caseAI Agents & Voice AI

Voice AI Systems

Voice systems on real telephony: AI receptionists, inbound support, outbound qualification, appointment booking, and CRM-integrated calling, with transcription, call analysis, and escalation to people.

Enters through
03AI Agents & Voice AI
System type
Telephony-connected voice agents
Also demonstrates
telephony integration · speech · LLM conversation logic · CRM actions · human transfer01AI Systems & Automation
A voice system on the system section.Seven stages. The call enters through telephony, is transcribed and reasoned over, acts through automation, is spoken back, is analysed, and can be transferred to a person at any point.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data1234567
  1. 1Telephony: inbound or outbound callAPIs
  2. 2Speech recognitionAI
  3. 3LLM conversation logicAI
  4. 4Tools and CRM actionsAutomation
  5. 5Speech synthesisAI
  6. 6Transcription and call analysisData
  7. 7Escalation and human transferApplication

01 Context

The class of problem

Phone workloads, from reception and support to outbound qualification and booking, depend on how many people are available to answer. The systems in this capability case handle the routine calls, act in business systems during the call, and hand the rest to a person.

This is a capability case rather than a single client project: it documents the voice systems Qzentra builds and the architecture they share.

What made it non-trivial

  • Latency: speech recognition, reasoning, and synthesis have to fit inside a natural conversational pause
  • The system has to act in CRMs and calendars during the call, not after it
  • Every call needs a safe path to a person

02 The system

Systems we can build

Voice systems are built on a telephony layer, real-time speech recognition, an LLM for conversation logic, tool calls into CRMs and booking systems, and speech synthesis back to the caller. Calls are transcribed and analysed, and anything outside scope is transferred to a person.

System types

  1. AI receptionist
  2. Inbound customer support
  3. Lead qualification
  4. Outbound calling
  5. Appointment booking
  6. CRM-integrated voice workflows
  7. Transcription and call analysis
  8. Escalation and human transfer

03 The route

How a voice system works

The loop a single call travels. Recognition, reasoning, and synthesis have to complete inside a conversational pause; the actions run in the business's own systems.

  1. Telephony: inbound or outbound call

    APIs

    A call arrives or is placed through the telephony layer.

  2. Speech recognition

    AI

    The caller’s speech is transcribed in real time.

  3. LLM conversation logic

    AI

    An LLM decides what to say and what to do next, inside defined guardrails.

  4. Tools and CRM actions

    Automation

    During the call the system can look up or book, and it logs the call and its outcome to the CRM.

  5. Speech synthesis

    AI

    The response is spoken back to the caller.

  6. Transcription and call analysis

    Data

    Calls are transcribed and analysed for intents and outcomes, feeding reporting or review.

  7. Escalation and human transfer

    Application

    Anything outside scope, or anything the caller asks for, is transferred to a person.

04 Decisions

Architecture may include

  1. Telephony as the boundary

    Twilio, Vapi, or Retell AI carry the call; the rest of the system sits behind that boundary and can change without changing the number the caller dials.

  2. Speech layers tuned for latency

    Recognition with Deepgram and synthesis with ElevenLabs are chosen and configured so that the round trip fits a conversational pause.

  3. Actions through webhooks and workflows

    CRM lookups, bookings, and logging run through n8n and webhooks, so the voice layer stays thin and the business logic stays in one place.

  4. Escalation designed in

    Out-of-scope requests and explicit asks for a person transfer the call with the context so far.

05 Verified outcomes

What these systems are built to do

  • Routine inbound and outbound calls handled without a person on the line
  • Bookings, lookups, and CRM updates made during the call
  • Every call transcribed and analysed
  • Calls outside scope transferred to a person

06 Technology and capabilities

Technology, after the architecture

Named last, with the role each played. The capabilities are what the project demonstrates beyond its primary service.

  • TwilioTelephony
  • VapiVoice agent platform
  • Retell AIVoice agent platform
  • DeepgramSpeech recognition
  • ElevenLabsSpeech synthesis
  • LLM APIsConversation logic
  • n8n and webhooksWorkflow, CRM, and API integration

Capabilities demonstrated

  • voice AI architecture
  • telephony integration
  • speech recognition and synthesis
  • LLM conversation design
  • CRM integration
  • human handoff

07 Related work

Other case files

Systems that share a layer, a capability, or a decision with this one.

  1. 01Case fileAI Systems & Automation

    Multimodal AI Sales Funnel

    An end-to-end sales funnel for a crypto-mining hardware enterprise: Instagram and WhatsApp leads qualified, answered from a catalog of 500+ ASIC miners, scored, and handed to sales.

    Verified factAirtable-backed catalog of 500+ ASIC miners

    Enters through01AI Systems & Automation

    Read the case file
    Multimodal AI Sales Funnel: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data12345678
    1. 1Instagram DMsAPIs
    2. 2Lead qualificationAutomation
    3. 3WhatsAppAPIs
    4. 4Multimodal AI (text, voice notes, images)AI
    5. 5Product knowledge retrievalData
    6. 6Lead scoringAutomation
    7. 7Human sales handoffApplication
    8. 8Automated follow-up or cold-lead archivingAutomation

08 Discuss a project

Have calls that a person is answering when a system could?

Tell us the call types, the systems the voice agent must act in, and when a person should take over. That is the specification to start from.

Discuss a ProjectAll work