AUTOMATING REI LEAD QUALIFICATION WITH AN AI VOICE AGENT
Designed an AI-powered phone agent that qualifies inbound leads in real time — reducing manual effort and filtering out ~80% of low-quality inquiries.
Year
2025
Field
Real Estate
Client :
Pebblerei CRM
Category
Feature

PROBLEM
The team relied on manual calls to qualify inbound leads, which was time-consuming and inconsistent.
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads
WHAT I DID
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads
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AUTOMATING REI LEAD QUALIFICATION WITH AN AI VOICE AGENT
Designed an AI-powered phone agent that qualifies inbound leads in real time — reducing manual effort and filtering out ~80% of low-quality inquiries.
Year
2025
Field
Real Estate
Client :
Pebblerei CRM
Category
Feature

PROBLEM
The team relied on manual calls to qualify inbound leads, which was time-consuming and inconsistent.
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads
WHAT I DID
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads
More Projects
More Projects
AUTOMATING REI LEAD QUALIFICATION WITH AN AI VOICE AGENT
Designed an AI-powered phone agent that qualifies inbound leads in real time — reducing manual effort and filtering out ~80% of low-quality inquiries.
Year
2025
Field
Real Estate
Client :
Pebblerei CRM
Category
Feature

PROBLEM
The team relied on manual calls to qualify inbound leads, which was time-consuming and inconsistent.
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads
WHAT I DID
Designed an AI voice agent integrated with Retell AI that:
conducts real-time conversations with leads
captures structured data during calls
routes qualified leads to the team

KEY CONVERSATION DESIGN DECISIONS
Designing the AI agent required balancing natural conversation with the business need to collect structured qualification data. The challenge was not only defining what the AI should ask, but also how it should handle uncertainty, build trust, and guide users toward meaningful outcomes.
Challenge | Design Decision |
|---|---|
Unpredictable responses | Introduced fallback paths and clarification prompts |
Low user trust | Clear AI introduction and transparent messaging |
Missing qualification data | Progressive follow-up questions |
Ambiguous answers | Confidence scoring and routing logic |
AGENT TESTING AND QUALIFICATION FLOW

UX flow defining how users configure, test, validate, and review AI-generated lead qualification results before deploying the agent.
(1) Configure Agent > (2) Agent Connects > (3) Conversation in Progress > (4) Processing Results > (5) Summary

IMPACT
Filtered out ~80% of non-relevant inquiries
Reduced manual workload for the team
Enabled faster identification of high-intent leads




