Voice Simulation: Define Agents, Personas, and Run Call Tests

Go to app.futureagi.com → Simulate → Agent Definition → Create agent definition.

The creation wizard has three steps:

Step 1: Basic Info

Field	Value
Agent type	Voice
Agent name	voice-support-agent
Select language	English

Step 2: Configuration

Voice agents require provider and contact details:

Field	Value
Voice/Chat Provider	Select your provider (Vapi, Retell, or Others)
Authentication Method	API Key
Provider API Key	Your provider’s API key
Assistant ID	Your assistant/agent ID from the provider
Country Code	Your country code (e.g. +1)
Contact Number	The phone number for inbound/outbound calls
Inbound/Outbound	Toggle between inbound (agent receives calls) and outbound (agent initiates calls)

Step 3: Behaviour

Field	Value
Prompt / Chains	You are a helpful customer support agent for TechStore. You assist customers with orders, returns, and product questions over the phone. Always be professional, empathetic, and solution-oriented. Keep responses concise: this is a voice call, not a chat. If you cannot resolve an issue, offer to transfer to a human agent.
Knowledge Base	(optional) Select a KB for grounded responses
Commit Message	Initial voice agent prompt

Click Create.

Still on the Configuration step of the agent creation wizard, you can optionally toggle Enable observability (Requires API key) to monitor your voice agent’s calls. This toggle becomes available only after you fill in both Provider API Key and Assistant ID — it is disabled until both fields are provided.

Once enabled, FutureAGI auto-creates an Observe project named after your agent. After you run simulations (Step 5) or your agent receives real calls, voice provider logs are automatically imported into this project. No SDK setup or manual instrumentation is needed.

To view voice traces, go to Tracing (left sidebar under OBSERVE) and select the auto-created project. Each voice call is logged with metadata such as call duration, status, and transcript.

Go to Simulate → Personas → Create your own persona.

Voice personas have Behavioural Settings (Personality, Communication Style, and voice-only Accent) and Conversation Settings (voice-specific settings including speed, background noise, and sensitivity sliders).

Create these three personas (select type Voice for each):

cooperative-caller

Section	Field	Value
Basic Info	Name	cooperative-caller
Basic Info	Description	A calm, patient customer who explains their issue clearly and follows instructions step by step.
Behavioural	Personality	Friendly and cooperative
Behavioural	Communication Style	Direct and concise
Behavioural	Accent	american
Conversation	Conversation Speed	1.0
Conversation	Background Noise	No
Custom Properties	patience_level	high

frustrated-caller

Section	Field	Value
Basic Info	Name	frustrated-caller
Basic Info	Description	An impatient caller who has tried to resolve this twice. Speaks in short sentences and may threaten to cancel.
Behavioural	Personality	Impatient and direct
Behavioural	Communication Style	Assertive
Behavioural	Accent	american
Conversation	Conversation Speed	1.25
Conversation	Background Noise	Yes
Custom Properties	patience_level	low

confused-caller

Section	Field	Value
Basic Info	Name	confused-caller
Basic Info	Description	A non-technical caller unsure what information to provide. Asks for clarification frequently.
Behavioural	Personality	Anxious
Behavioural	Communication Style	Questioning
Behavioural	Accent	american
Conversation	Conversation Speed	0.75
Conversation	Background Noise	No
Custom Properties	tech_literacy	low

Go to Simulate → Scenarios → Create New Scenario.

Select Workflow builder and fill in:

Field	Value
Scenario Name	broken-device-return
Description	A customer received a laptop with a cracked screen and wants to start a return. They have their order number but don’t know the return process.
Choose source	Select voice-support-agent (Agent Definition)
Choose version	v1
No. of scenarios	10

In the Persona section, leave Add by default on to auto-add all active personas, or turn it off and click Add persona to select specific ones.

Click Create.

Go to Simulate → Run Simulation → Create a Simulation.

The creation wizard has four steps:

Step 1: Add simulation details

Field	Value
Simulation name	return-flow-voice-test
Choose Agent definition	voice-support-agent
Choose version	v1
Description	Testing return flow with 3 caller personas

Step 2: Choose Scenario(s)

Select the broken-device-return scenario.

Step 3: Select Evaluations

Click Add Evaluations and under Groups, select Conversational agent evaluation for broad coverage (10 built-in evals covering loop detection, context retention, query handling, conversation quality, and more).

Step 4: Summary

Review your configuration and click Run Simulation.

FutureAGI places calls to your agent in parallel. Each call runs to completion before the result is logged.

Once the run completes, the results page shows three tabs:

• Call Details — per-call transcripts, CSAT scores, and evaluation scores
• Analytics — evaluation score distributions across personas
• Optimization Runs — results from prompt optimization runs

Click any transcript to read the full conversation. Look for:

• Turns where the frustrated persona escalated
• Turns where the confused persona stopped understanding
• Whether the cooperative persona reached a successful resolution every time

Fix My Agent: Click the Fix My Agent button to open the diagnostic drawer. The platform analyzes your simulation traces and surfaces two categories of recommendations:

• Fixable Recommendations: organized into two tabs:
  • Agent Level: prompt and behavior improvements you can apply directly (e.g. missing empathy phrases, unclear escalation paths)
  • Branch Level: domain-specific issues grouped by conversation topic or flow (e.g. return policy gaps, billing confusion)
  • Each recommendation highlights which specific calls are affected, so you can trace issues back to exact conversations
• Non-Fixable Recommendations: system-level issues that require infrastructure changes (e.g. missing integrations, data access limitations), plus a human comparison summary showing where a human agent would have handled the situation differently
• Overall Insights: a synthesis of patterns across all calls

Optimize My Agent: Inside the Fix My Agent drawer, click Optimize My Agent to auto-generate improved prompt variants:

1. Enter a Name for the optimization run
2. Choose Optimizer — select from available optimizers (e.g. Bayesian Search, MetaPrompt, ProTeGi, GEPA, PromptWizard, Random Search)
3. Language Model — select the model for optimization
4. Click Start Optimizing your agent

Review results in the Optimization Runs tab. Compare generated prompt variants and their scores to decide which version to promote.