Enterprise Portal Stabilisation & File Matching Enhancements

A mission-critical ECU tuning portal refinement focused on correcting file-matching logic and aligning system processes. The project resolved issues where user-uploaded vehicle files were not accurately matching the existing tuning database, causing processing failures and inefficiencies. By refining system logic, correcting data handling flows, and rectifying underlying code issues, the platform was stabilised to ensure reliable, accurate file matching and smoother end-to-end operations. This improvement restored system confidence, reduced manual intervention, and enabled the portal to support high-volume tuning workflows with consistency and precision.

Enterprise Portal Stabilisation & File Matching Enhancements

The Client

Viezu Files is a leading global provider of engine tuning and ECU remapping file services, specialising in performance optimisation solutions for the automotive tuning industry. Founded to support professional tuners, garages, and dealerships worldwide, the platform delivers high-quality, tested tuning files that enhance vehicle performance, fuel efficiency, and driving experience. With a focus on technical excellence and comprehensive vehicle coverage, Viezu Files has established itself as a trusted partner for automotive professionals seeking safe and effective engine optimisation. The platform offers an extensive database of custom tuning files across multiple vehicles and models, supported by expert technical assistance and rigorous quality control. As the industry evolves, Viezu Files continues to incorporate the latest tuning technologies while maintaining its commitment to delivering professional-grade solutions that help businesses succeed in the competitive performance tuning market.


The Challenge

The client approached us with an existing ECU tuning portal facing critical operational issues. The platform was unable to consistently match user-uploaded vehicle files with the corresponding data in its tuning database, resulting in processing errors and increased manual intervention.

The challenge was to identify and correct underlying logic, process flow, and code-level issues within a complex live system. The portal required accurate data alignment and reliable file matching to support high-volume ECU tuning workflows. Our task was to refine system logic, correct faults, and stabilise the matching process to restore accuracy, efficiency, and confidence in the platform’s core functionality.


The Solution

To resolve the file-matching issues within the ECU tuning portal, we focused on simplifying and correcting the system’s core logic. The platform processes two types of ECU files, Master and Slave, with Slave files containing the critical data required for tuning. The existing logic was overly complex and failed to consistently retrieve the correct files from the database.

We redesigned the matching workflow by simplifying decision paths and correcting data flows between systems. File metadata and user-related data were aligned and matched using PostgreSQL, while ECU file storage and retrieval were handled through BigQuery for performance and scalability.

This refined architecture ensures accurate, reliable file retrieval, faster processing, and a cleaner foundation for future enhancements, while maintaining system stability in a live production environment.


The Results

The system refinement delivered a stable, accurate, and high-performance ECU tuning portal. By correcting the core file-matching logic, the platform can now reliably match user-uploaded ECU files with the correct records in the tuning database, significantly reducing processing errors and manual handling.

The introduction of BigQuery for ECU file storage and PostgreSQL for structured user and metadata storage improved data separation, query performance, and long-term scalability. This resulted in faster processing, better data integrity, and a more resilient architecture.

The portal is now positioned to handle higher file volumes with confidence, providing a reliable foundation for future optimisation, automation, and AI-driven enhancements.

THE DETAILS

Company: VIEZU Performance Tuning

Website: https://www.viezu-files.com/

Location: UK

Industry: Automotive Performance & Aftermarket

Duration : 6 weeks

WHAT WE DID

System Refinement

Process Alignment

Logic Correction

Code Rectification

TECHNOLOGY WE USED

Django REST Framework

AngularJS

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