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AI Voice AgentsAutomationSaaSReal EstateVoice Calling

Seller Genius AI

Automating Real Estate Sales Calls with AI Voice Agents

Seller Genius AI

Seller Genius AI helps solo realtors and small brokerages eliminate manual cold calling by using AI-powered voice agents to qualify leads, book appointments, and follow up automatically, at scale.

Key Outcomes

  • 1–2 hours saved per agent per day
  • 15–35% increase in booked appointments
  • 10–30% reduction in lost leads
  • Early-stage predictable SaaS revenue ($99–$299 / agent / month)

Quick Facts

  • Industry: Real Estate / PropTech
  • Platform: Web-based SaaS (Multi-tenant)
  • Users: Solo Realtors & Small Brokerages
  • Core Tech: AI Voice Agents, Workflow Automation
  • Stackup Services: Product Strategy, AI Architecture, Full-Stack Development, Integrations

Background

Real estate professionals live and die by speed of follow-up. Yet most solo agents and small brokerages still rely on manual cold calling, spreadsheets, CRMs, or virtual assistants to manage outbound sales, resulting in missed calls, inconsistent follow-ups, and lost opportunities.

Seller Genius AI was created to solve this gap with a fully automated AI voice calling platform that works around the clock, qualifies leads consistently, and books appointments without human intervention.

The Challenge

Business Challenges

  • Low daily call throughput per agent
  • Missed follow-ups leading to lost deals
  • Inconsistent lead qualification across agents
  • High cost of virtual assistants and manual dialing

Operational Pain Points

  • No centralized system to track calls, leads, and appointments
  • Manual scheduling and calendar coordination
  • Poor visibility into call outcomes and performance metrics

Technical Challenges

  • Building reliable outbound AI calling at scale
  • Managing call state transitions and retries
  • Preventing AI hallucinations during live conversations
  • Handling time zones, working hours, and compliance constraints

The Solution

Stackup Solutions designed and built Seller Genius AI as a multi-tenant, production-grade SaaS platform centered around AI voice automation and intelligent workflows.

Architecture & Tech Stack

  • Frontend: React.js + Tailwind CSS
  • Backend: Node.js
  • Database: PostgreSQL
  • Hosting & Infra: AWS
  • Voice Calling: SignalWire
  • AI / LLM: GPT-4 for transcript summarization
  • Payments: Stripe (subscriptions + invoices)
  • Calendar: Google Calendar (OAuth-based sync)

SignalWire was chosen based on client preference and call reliability, while GPT-4 powers structured, readable call summaries stored directly in the database.

AI Voice Agent Design

Each user configures a personalized AI agent during onboarding:

  • Agent name and greeting message
  • Tone of voice (professional, friendly, empathetic, etc.)
  • Working hours (weekday + weekend logic)
  • Buying and selling preferences

The AI agent operates using a hybrid rules + AI model, ensuring:

  • Script consistency
  • Controlled responses
  • Reduced hallucinations through strict prompting and temperature controls

Lead Management & Automation

  • Manual lead entry via a 2-step structured form
  • Bulk lead import via Excel templates
  • Lead types supported:
    • Buyer
    • Seller
    • Investor
  • Rich contextual data fed into AI calls for accurate conversations
  • Once added, leads automatically enter the AI call workflow

AI-Powered Call Flow

  1. Lead added → status set to Pending
  2. Cron job checks pending calls every minute
  3. Call moves to Active and is placed via SignalWire
  4. Status updates in real time (Answered, Not Answered, Failed, etc.)
  5. GPT-4 generates a concise transcript summary
  6. If an appointment is agreed:
    • Event is automatically created in Google Calendar
    • Full call history, transcript, and outcomes stored and visible in the dashboard
  7. Unanswered calls trigger automated follow-ups and retries, ensuring no lead falls through the cracks

Dashboard & Analytics

Users get a centralized dashboard with:

  • Total leads
  • Conversion rate
  • Appointments booked
  • Scheduled calls
  • Monthly lead trends

Additional modules include:

  • Call History with transcripts and rescheduling
  • Appointments with calendar views and status tracking
  • Subscription & Usage Management
  • Profile, Agent, Buying & Selling Settings

An internal Admin Dashboard allows platform operators to monitor users, usage, subscriptions, and system health.

Implementation Process

Stackup Solutions handled the project end-to-end:

Product & Workflow Design

  • Defined AI call flows, lead schemas, and onboarding logic

AI Architecture & Prompt Engineering

  • Built safe, controlled AI conversations
  • Implemented GPT-4 summarization pipelines

Full-Stack Development

  • Multi-tenant SaaS architecture
  • Real-time call state management

Integrations

  • SignalWire for voice
  • Stripe for subscriptions
  • Google Calendar for appointments

Scalability & Reliability

  • Queue-based call concurrency
  • Cron-driven automation
  • Usage tracking and billing alignment

Results & Impact

Operational Efficiency

  • 1–2 hours saved per agent per day
  • 20–40 hours saved per month per agent

Sales Performance

  • 15–35% increase in booked appointments
  • 10–30% fewer lost leads

Business Impact

  • Early-stage predictable SaaS revenue
  • Paying customers across solo agents and small brokerages
  • 5–15% trial-to-paid conversion rate
  • Clear path to break-even at ~100 paying agents

Qualitative Wins

  • AI never misses follow-ups
  • Consistent qualification across all leads
  • Agents focus on closing, not dialing
“Seller Genius AI replaced hours of manual calling every day and made our follow-up process consistent and predictable.”
— Early Adopter (Real Estate Agent)

Why It Matters

Seller Genius AI demonstrates how AI voice agents can be production-ready, safe, and revenue-generating when paired with the right architecture and workflows.

For Stackup Solutions, this project showcases deep expertise in:

  • AI-driven automation
  • SaaS product engineering
  • Real-world LLM deployment
  • Complex third-party integrations

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