TaxiGO System Architecture

TaxiGO is a WordPress-based system developed to operate as a deterministic
backend for a real-world taxi service, where reliability, performance,
and call conversion are primary concerns.
Instead of relying on plugins, visual builders, or ad-hoc configurations,
the system is structured as a controlled environment with explicit behavior.

The project evolved through more than 30 structured stages, focusing on
removing uncertainty from the platform. Core functionality is implemented
through custom MU plugins, allowing business logic, tracking, and routing
to exist independently of the theme and interface.
This shifts WordPress from a content editor into a predictable system layer.

Deployed in a real environment at

taxigobg.com
.

What was solved

• Reliable call tracking through deterministic event handling.
• Custom sitemap engine for structured indexing and AI discoverability.
• Enterprise-grade JSON-LD knowledge graph for consistent semantic output.
• Removal of non-essential plugins and reduction of system complexity.
• Stable performance through controlled asset loading and minimal dependencies.

Why this approach

Standard WordPress setups often rely on multiple plugins and UI-driven
configuration, leading to unpredictable behavior and hidden dependencies.
For a service where user actions translate directly into phone calls,
this level of uncertainty is unacceptable.

TaxiGO demonstrates how WordPress can be used as a controlled backend,
where behavior is encoded explicitly and executed consistently.
By moving logic into MU plugins and reducing reliance on external systems,
the platform becomes easier to maintain, debug, and scale.

The result is a system that prioritizes determinism over flexibility,
and real-world outcomes over surface-level metrics.
It operates with minimal overhead while maintaining a clear separation
between logic, presentation, and content.