Unirama High-Performance Reporting & CRM

A high-performance Go backend module delivering real-time reporting, large-query handling, and transaction-safe CRM workflows across distributed databases.

My role: Remote Golang Full-Stack Developer
Organization: PT Unirama Duta Niaga

Original public archiveExplore the case

Unirama enterprise reporting and CRM dashboard — Archive artifact / 01
Preserved public portfolio image. This is a historical artifact, not a live application screenshot.

01 Context

The environment

Legacy Python/Frappe backend struggled with compute-intensive reporting requests involving 4,000+ records, stalling user workflows for minutes.

02 Problem

The human problem

Business operators and finance analysts experienced severe UI lockups and timeout errors when pulling daily operational metrics.

03 System

The contribution

Migrated critical reporting pipelines to Golang with Gin and GORM, optimized database indexing across PostgreSQL/MySQL, and implemented transactional safeguards that slashed response times from 10 minutes to 10 seconds.

Unirama Go REST API and backend development workspace — Archive artifact / 02

04 Recorded technology

Tools of the trade

Golang
Gin
GORM
PostgreSQL
MySQL
MariaDB
REST APIs
Database Indexing

02 / Evidence & boundaries

What this evidence means

This page preserves a public professional or research case study. Screenshots and descriptions belong to that archive. Interactive tools and synthetic business demonstrations elsewhere on this site are newly built portfolio work; they do not recreate an employer’s internal data or independently prove historical outcomes.

Reported outcomes

Historical figures below are reported by the portfolio author and preserved from the original case study. They have not been independently validated and are not benchmarks of the new demonstrations.

Query Runtime Reduction: 10m → 10s
Records Batch Processed: 4K+
Integration Overhead: -40%

Public case study Figures: author-reported

03 / Continue exploring

Separate, portfolio-native demonstrations with synthetic data. Their behavior can be inspected directly; they are not the original employer systems.

Explore the systemOrders & fulfillment

From a draft to an actual ledger posting.

Open the toolFind the signal.

Inspect a dataset, clean the rough edges, and leave with data you can actually use.

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