Impact
Brands
19
Brands
19
Franchise locations
5,500
Active households
12M
TL;DR
- Shipped a fully operational prototype with AI-powered booking, intelligent recommendations, past jobs, and push notifications.
- Delivered magic link, passkey, and legacy access management plus API surfaces for mobile app integration.
- Produced a complete go-to-market strategy and board deck proposals alongside the prototype.
- Built reusable UX, expansive database architecture, and a comprehensive GA via GTM implementation.
- Services delivered: Product delivery, Product launch, Go-to-market strategy, Forward-deployed engineering, Creative staffing.
Situation
Neighborly runs 19 home-service brands across 5,500 franchise locations, 12M households, and $4.6B in annually recurring revenue.
The Problem
A homeowner who used Neighborly brands could appear in multiple different systems. Franchisees lacked a shared view of prior work on the home, customers lacked a way to book multiple services, and regular maintenance became the customers problem.
Neighborly had the opportunity to do something never done before, to make fixing, maintaining, or enhancing your home feel effortless in a single platform.
What WYN Shipped
- Fully operational prototype with AI powered booking, intelligent recommendations, past jobs, push notifications, and an external mapping solution that dynamically maps to 194+ systems Neighborly currently uses.
- AI accessible product documentation for each production level surface.
- Magic link, passkey, and legacy access management for integration to existing legacy systems.
- API documentation and surfaces for mobile app integration.
- Complete go-to-market strategy and board deck proposals.
- Reusable user experience including dynamic paths across all 19 trades and entire customer lifecycle.
- Expansive database architecture across multiple privacy and system layers.
- Comprehensive Google Analytics implementation via Google Tag Manager.
How We Worked
One forward-deployed, one design hire, one video editor embedded with Neighborly's product, project, and mobile teams.
Utilizing proprietary workflows for AI prompting and agentic use, including integration of LLM tools including Codex, Claude, and Langsmith + Langchain with fully automated AI coding, Neighborly development teams reviewing.
Why WYN
WYN was selected because of its extensive experience working with highly fragmented systems in the automotive industry, and proven experience forward deploying / rolling up sleeves to rapidly prototype. They differentiated themselves by providing next day prototypes, dynamic functionality in the first 30 days, and reusable API and components in the first 90.