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CrewAI Multifamily Demand Lead Qualification & Voice Scheduling Agent with Bland AI

Multifamily leasing teams lose qualified prospective tenants due to delayed phone inquiry responses during peak leasing windows. Build an agent system using CrewAI and Bland AI voice calls to handle tenant inquiry calls and update leasing pipeline states. Achieve 90% automated lead resolution within 30 seconds.

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What you are building

Develop a multi-agent orchestration pipeline using CrewAI and Bland AI API to automate tenant inquiry qualification and tour scheduling.

How work is evaluated

Evaluation

Evaluates lead qualification accuracy and tour scheduling tool calls based on call transcript evaluations.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

lead_qualification_match

Validates qualified status outcome

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

resolution_rate

Percentage of valid tenant lead queries correctly processed • target: 0.9 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Configure CrewAI agents with defined roles (Lead Qualifiers, Tour Schedulers, Leasing Knowledge Assistants)

  • Integrate Bland AI API to trigger dynamic voice calls for lead follow-ups and preference gathering

  • Parse unstructured voice call transcripts into structured guest card CRM payloads

  • Handle edge cases such as budget mismatch, move-in date conflicts, and specialized amenity requests

Resources

Dataset notes

Simulated voice phone transcripts between prospective apartment tenants and AI leasing agents.

Challenge setup

Evaluates lead qualification accuracy and tour scheduling tool calls based on call transcript evaluations.

Challenge input

JSON containing caller transcript, requested move-in, and target budget

CrewAI

Agent orchestration framework with role-based execution.

Bland AI

Telephony voice interface for automated caller interactions.

Evaluated output

JSON containing qualified_status, tour_scheduled, and preferred_unit_type

Evaluation checks
  • Validates qualified status outcome
  • Percentage of valid tenant lead queries correctly processed • target: 0.9 • range: 0-1
Configured evaluation evidence
  • Benchmark: Multifamily Lead Automation Benchmark
  • Resolution Rate target: 90%
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • Bland AI · Required
  • CrewAI · Optional
  • Aim · Optional

Evaluation contract

  • lead_qualification_match · Weight 1
  • resolution_rate · Weight 1

Metrics

  • resolution_rate · Target 0.9

Benchmarks

  • Multifamily Lead Automation Benchmark
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON containing caller transcript, requested move-in, and target budget

    Output: JSON containing qualified_status, tour_scheduled, and preferred_unit_type

    Execution harness: Python

Evaluation tools

  • CrewAI · agent_framework
  • Bland AI · voice_ai

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about CrewAI Multifamily Demand Lead Qualification & Voice Scheduling Agent with Bland AI