Voicebot Manufacturing

Every voice agent is built from scratch. For one operation.

From intake to live deployment, the manufacturing process typically takes between 1 and 5 weeks, depending on operational complexity.

A production voice agent is not activated with a switch. It is built through a structured process — from how your team handles calls, to which systems it connects to, to how it behaves under pressure.

Each voice agent is manufactured for one specific inbound customer support environment.

Step 1

Operational intake with the support team

The process starts with your team. Not with technology.

We work directly with:

  • Operations managers
  • Team leads
  • Frontline agents

Together, we document how inbound calls actually happen day to day.

This includes:

  • Common call reasons
  • Frequent variations
  • Edge cases
  • Escalation moments
  • Language and tone expectations

We learn how your operation actually runs before designing any AI behavior.

24/7 availability
Handles 100+ languages
Average handling time: 2 minutes
24/7 availability
Handles 100+ languages
Average handling time: 2 minutes
90% resolution rate
Customer satisfaction: 4.8/5
No wait times
90% resolution rate
Customer satisfaction: 4.8/5
No wait times
System analysis
Step 2

System analysis and integration mapping

In parallel, we analyze the systems the voice agent needs to work with.

This includes understanding:

  • Where customer data lives
  • Which systems agents use during calls
  • What information must be retrieved in real time
  • Which actions must be performed during a conversation

The voice agent doesn't just talk. It reads, writes, and triggers actions in your systems. This step defines exactly what it can and cannot do.

Call logic design
Step 3

Designing the call logic

This includes:

  • How calls start
  • Which paths are possible
  • Where decisions are made
  • When a human must take over
  • How calls are considered resolved

This creates a clear operational framework that mirrors real support behavior.

AI is later placed inside this structure.

Multiple agents coordination
Step 4

Coordinating multiple agents within one system

A production voicebot is not a single entity.

Behind the scenes, multiple specialized agents work together:

  • One manages the conversation flow
  • Others retrieve or update information in systems
  • Others monitor risk, uncertainty, or handover conditions

Each agent has a defined responsibility. Together, they handle complex calls without ever losing control or context.

Step 5

Training the voice agent within defined boundaries

The voice agent is trained to operate inside the predefined call logic and system constraints.

It is designed to:

  • Ask the necessary follow-up questions
  • Retrieve accurate information
  • Trigger approved actions in systems
  • Recognize uncertainty or risk
  • Remain within allowed responses

The agent does not improvise beyond its role.

Its behavior is constrained by the rules of the operation.

Voice agent training
SpiraLink AI

Getting data and training session from knowledge base.

Human handover
Step 6

Engineering human handover points

Transfer to a human agent is designed as part of the system.

We define:

  • When a transfer is triggered
  • How the agent resumes the conversation
  • What information is passed
  • What system context is included

When a human takes over, they receive the full conversation and system context.

The interaction continues without restarting.

Step 7

Internal testing before live deployment

Before going live, the voice agent is tested internally.

We simulate:

  • Realistic call scenarios
  • System interactions
  • Unexpected inputs
  • Edge cases
  • Escalation paths

It only goes live when it performs consistently across every scenario.

Internal testing
Step 8

Refinement after deployment

After launch, the system is reviewed and adjusted.

We monitor:

  • Conversation outcomes
  • System actions
  • Handover moments
  • Friction points

Adjustments are made as the operation evolves.

The voice agent improves alongside the support team.

Refinement
Spiralink

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What this process delivers

This manufacturing process results in a voice agent that:

Interacts correctly with internal systems
Coordinates multiple AI components safely
Reflects real operational behavior
Interacts correctly with internal systems
Coordinates multiple AI components safely
Reflects real operational behavior
Interacts correctly with internal systems
Coordinates multiple AI components safely
Reflects real operational behavior
Integrates cleanly with human agents
Performs consistently under live conditions
Reflects real operational behavior
Integrates cleanly with human agents
Performs consistently under live conditions
Reflects real operational behavior
Integrates cleanly with human agents
Performs consistently under live conditions
Reflects real operational behavior