Industrial Logic

Green Horizons operates a route-based lawn care service model with clear opportunities for AI-driven optimization across customer acquisition, service delivery, and billing.

Core Business Processes

Fully Mapped

End-to-end workflow documentation

Automation Opportunities

Identified & Prioritized

Ready for implementation

Data Architecture

Documented

Entity relationships defined

Core Business Model

Understanding Green Horizons' operational flow from customer acquisition to payment

Green Horizons operates a multi-region lawn care service with operations across Minnesota, Connecticut, and Michigan. The business model centers on converting one-time estimate requests into recurring service contracts, delivered through geographically optimized routes.

STEP 1

Lead Generation

Customer

STEP 2

Estimate Creation

Sales Team

STEP 3

Service Scheduling

Office Staff

STEP 4

Route Execution

Field Crews

STEP 5

Invoice Generation

System

STEP 6

Payment Collection

Automated

Current Operational Bottlenecks

•Manual Estimate Creation: 1-2 hours per estimate, 24-48hr turnaround

•Route Planning: Daily manual optimization, weather disruptions

•Customer Service: High call volume, repetitive questions

•Data Entry: Multiple systems, manual transfers

•Churn Detection: No predictive analytics, reactive approach

•Billing Errors: Manual invoice review, delayed corrections

Business Process Flows

The complete customer journey from initial request to payment collection, showing how work flows through the organization. Green nodes indicate AI-enhanced processes that are already improving efficiency.

React Flow

AI Enhanced

Manual Process

Data Architecture & Flow

Core data entities and how information moves through the system. Understanding data relationships is critical for building effective automation and ensuring seamless integrations between AI widgets and existing systems.

React Flow

Core Entities

Customer, Estimate, Service, Route, Invoice

Data Relationships

Fully mapped and documented

Stakeholder Responsibilities

Clear delineation of who does what in the organization. This swim lane view shows handoffs between teams and identifies where AI can reduce manual work and improve coordination between customer, office, field, and system roles.

React Flow

Customer

Request, review, approve

Office Staff

Estimate, schedule, invoice

Field Crew

Execute, complete, report

System/AI

Automate, optimize, assist

AI Automation Opportunities

Strategic mapping of pain points to AI-powered solutions. Each opportunity represents a chance to reduce manual work, improve accuracy, and deliver better customer experiences through intelligent automation.

Flow Status

Live (Active)

Demo Ready

Concept

Pain Points → AI Solutions

Live Solution

AI Chatbot already deployed

Demo Ready

Interactive prototypes available

Concepts

High-value future opportunities

Business Process to AI Automation Mapping

Clear alignment between existing business processes and AI automation opportunities. This unified view shows how each manual workflow maps to specific AI-powered solutions.

Business Process	Data Flow	Person/Role	AI Automation
Customer Request	Web form → CRM	Customer	AI Chatbot LIVE
Estimate Creation	Property data → Pricing	Sales Team	AI Quote Estimator DEMO
Service Scheduling	Calendar → Routes	Office Staff	Predictive Scheduling DEMO
Job Execution	Route sheet → Crew	Field Crew	Work Summary Generator DEMO
Invoice Generation	Services → Billing	System	Invoice Reconciliation DEMO
Customer Communication	Inquiry → Response	Office Staff	Email AI Assistant DEMO