Fairway Finder needed to go from a validated prototype to a production platform capable of serving golfers across the United States. Algorithmic owned the entire product build, strategy, design, architecture, engineering, and deployment, delivering a cross-platform mobile app, responsive web experience, real-time availability backend, and operational tooling in a single engagement.
Click to expand The starting point
Ryan, founder of Abyssal Digital, had already proven demand with a prototype called Tee Time Alerts. It notified golfers when cancellations appeared at saved courses. Users kept coming back because the value proposition was clear as the app helped to find an open slot and grab it before someone else does.
The prototype validated the idea. It did not have the design system, data architecture, or operational layer required for national coverage across dozens of fragmented booking sources.
Algorithmic was brought in to own the full zero-to-one build:
- Product strategy
- UX and visual design
- System architecture
- Flutter app development
- Rails backend engineering
- Admin tooling
- Release management
The engineering challenge
Golf course booking in the United States runs on a patchwork of course websites, third-party platforms, and proprietary systems. Each source structures availability data differently - dates, prices, time slots, booking rules, and course metadata vary across every integration.
A consumer product cannot expose that complexity. Golfers expect one search experience, one alert system, and one booking path. Three engineering requirements shaped the platform:
- Data normalisation at scale: Every source maps into a single canonical schema (course, date, time, price, player count, status, and booking metadata) before any data reaches the app.
- Freshness under load: Availability must stay current enough for golfers to trust it. Redis serves high-frequency reads while background poll cycles refresh entries on source-specific intervals.
- Low onboarding cost: Adding the 200th course cannot require the same effort as the 20th.
The architecture uses an adapter pattern to isolate source-specific behaviour. Each booking source connects through its own adapter, maps data into the Fairway Finder schema, and feeds a single internal contract. The application layer, search, alerts, booking, sync, runs against one data model regardless of how many sources sit behind it.
Click to expand This separation created three practical advantages:
- The product logic stays clean because every feature reads from one schema.
- A single failing source cannot break the rest of the platform.
- Courses on shared booking systems can be onboarded through configuration rather than custom code.
The low-level acquisition mechanics are intentionally kept private. The public architecture explains the system without exposing sensitive operational detail.
The product
The design objectives were focused on helping users find a tee time and book it in three taps. Every screen was built to reduce friction at the moments where bookings are won or lost.
Discovery
Golfers search through map and list views filtered by location, date, time window, price range, and availability. A golfer looking for a Saturday 7 to 9 AM slot can filter once and compare live options across nearby courses without opening each course page individually.
Cancellation alerts
Cancellation alerts are the product’s strongest retention driver. Users save course and time preferences. When a matching slot opens, Fairway Finder delivers a push notification within minutes. A passive wish becomes an actionable booking opportunity.
Technology and operations
Every technology decision served three constraints: fast iteration for a product still learning from user behaviour, simple operations for a small team, and a clear path toward national scale.
- Flutter delivered one shared codebase for iOS and Android, reducing the mobile engineering surface and keeping releases synchronised.
- Ruby on Rails handled business logic, APIs, admin workflows, and the web experience. Its convention-driven structure matched the team’s need for speed.
- PostgreSQL stored relational product data while Redis served high-frequency availability queries.
- Digital Ocean hosts the entire system. Twilio and Customer.io handle all communication protocols.
Alongside the consumer product, we built an admin dashboard that gives Ryan direct control over:
- Course onboarding
- Source health monitoring
- Market launch coordination
- Engagement analytics
This allows him to take important product-related decisions that are data informed.
That operational layer is a deliberate part of the growth model. Configuration-driven onboarding, a single canonical schema, and a shared Flutter codebase keep the marginal cost of expansion controlled as Fairway Finder scales from dozens of sources toward hundreds of courses.
Outcomes
Fairway Finder is live as a multi-market tee time discovery and booking platform. The system includes:
- A Flutter cross-platform app
- A responsive web experience
- A real-time availability backend
- An admin dashboard for day-to-day operations
Ryan’s team can onboard courses, open new markets, monitor source health, and respond to user feedback with the technical foundation in place. Once an adapter type exists for a booking platform, additional courses on that system enter through the admin workflow with no new application code required.
The strongest product signal remains cancellation alerts. Golfers return because the product solves a time-sensitive problem they face every week, and the architecture keeps availability fresh enough to deliver on that promise.
We delivered the full build under one engagement:
- Product design
- Mobile app development
- Web app development
- Data infrastructure for capturing and storing tee times
- Integrations for admin tooling and analytics
Fairway Finder is now live in every US market, rated 4.8 stars, and used by over 50,000 golfers each month. The foundation built for growth is already carrying real demand.
