Case study · Power BI · n8n · Local AI

GulfFix
Operations Intelligence

A two-stage operations product: first make performance visible in Power BI, then turn the verified KPIs into a concise management report automatically.

OperationsPower BIn8n automationLM Studio AIManagement reporting

11,348completed jobs analysed

AED 3.95Mrevenue in the source period

76.5%overall SLA vs 90% target

23.4 ptsDubai's gap to target

01 · The business question

Make operational performance easy to act on.

The dashboard turns service data into a management conversation. Instead of asking someone to search through rows of information, it makes the performance gap visible by location and service type.

In plain language:Which location needs attention? Which services create repeat work? Where should a manager investigate first?

02 · What the dashboard shows

Executive overview

Revenue, achievement against target, SLA performance, and a clear management-attention signal.

Operations performance

Location-level SLA comparison and service-level patterns that reveal where performance is strongest and weakest.

Decision support

The design prioritizes the story behind the KPI—not just a collection of charts.

03 · See the work

Three screens.
One clear story.

These are the actual project outputs: the two Power BI pages that surface the operational signal, followed by the n8n workflow that turns the signal into a management-ready report.

GulfFix Power BI Executive Overview dashboard — 01
**Executive Overview**Revenue, volume, SLA, CSAT, and management attention in one view.

GulfFix Power BI Operations Performance dashboard — 02
**Operations Performance**Branch performance, repeat visits, revenue per job, and comparison table.

GulfFix n8n workflow from source CSV to AI management report — 03
**AI Operations KPI Analyst**CSV → KPI aggregation → LM Studio → final management report.

04 · What the data says

Dubai is the first place to investigate.

LocationSLAGap to target

Dubai priority66.6%−23.4 pts

Ajman79.8%−10.2 pts

Al Ain81.4%−8.6 pts

Sharjah81.9%−8.1 pts

Abu Dhabi82.3%−7.7 pts

Second layer: Appliance Repair has the highest repeat visits; AC Repair combines high repeat visits with the highest revenue per job; General Maintenance has lower revenue/job.

05 · What I built

I designed the data model, KPI measures, target comparisons, month sorting, revenue mapping, SLA target line, management-attention logic, and the two-page executive/operations layout.

Data modelDAX measuresTarget mappingExecutive layoutOperations analysisManagement insight

06 · The automation layer

Evidence first.
Explanation second.

The same job-level CSV then flows through n8n. Critical metrics are calculated deterministically before the verified facts are sent to a local Llama model through LM Studio.

GulfFix CSV→Extract rows→Calculate KPIs→LM Studio→Management report

AI MANAGEMENT REPORTVERIFIED OUTPUT

Operations Improvement for Dubai

Priority: Dubai at 66.6% SLA, 23.4 points below the 90% target.

Patterns: Abu Dhabi leads Dubai by 15.7 SLA points. Appliance Repair has the highest repeat visits at 7.1%.

Actions: Review Dubai's workflow, monitor SLA weekly, and investigate Appliance Repair repeat visits.

Source: synthetic portfolio dataset · 1 Jan–30 Jun 2026

Explore the technical layer

From dashboard to
AI Operations KPI Analyst.

The finished workflow turns a static dashboard insight into a repeatable, evidence-backed management communication process.

View the AI automation project ↗

GulfFixOperations Intelligence