Case Studies

How we solve real business problems

No hype, no jargon. Each study below walks through the problem, what we did, and what changed for the client.

AI IntegrationStackLyne·6 min read

MediFlow: Cutting a Diagnostics Lab's Admin Work by 40%

The problem

The lab network processed thousands of reports a month, but every appointment was booked by phone, every report was printed and filed, and doctors spent their mornings sorting routine results from urgent ones.

What we did

We spent the first week inside the lab, mapping how a report travels from machine to patient.

We built appointments and patient records first, then digital reports, then the AI layer.

The AI triage model flags only clearly routine results; anything uncertain goes straight to a doctor.

The results

Administrative workload dropped about 40% within three months.
Report turnaround for routine results went from two days to same-day.
Doctors now start each morning with a pre-sorted queue instead of a paper pile.

“Our staff focus only on the cases that need them. The team performs exceptionally well.”
— Medical Director, diagnostics network client

Digital TransformationStackLyne·5 min read

FleetPulse: Moving 150 Vehicles Off WhatsApp and Into One Dashboard

The problem

The operator ran more than 150 vehicles through WhatsApp groups and Excel. Every morning a planner spent three hours drafting routes by hand.

What we did

We started with proof of delivery so drivers could photograph and confirm each drop.

Dispatch, live tracking, and payouts followed in monthly releases.

An AI routing assistant now drafts the daily dispatch plan from live orders and vehicle positions.

The results

Fuel costs down roughly 28% from smarter routing.
Morning dispatch planning went from three hours to under thirty minutes.
Delivery disputes dropped sharply once photographic proof became standard.

“Would recommend them to any growing business.”
— General Manager, logistics client

AI IntegrationStackLyne·4 min read

Fraud Assist: Turning an All-Day Review Queue Into a Morning Task

The problem

Every flagged transaction landed in one queue that analysts worked through manually. Genuine fraud sometimes waited hours behind harmless flags.

What we did

We analysed a year of past review decisions to find patterns analysts resolved the same way every time.

The AI layer only auto-clears cases where confidence is very high; everything else keeps a human in the loop.

We shipped in shadow mode first before allowing automated decisions on clear cases.

The results

Daily fraud review went from hours to minutes.
Genuine fraud cases now reach an analyst dramatically faster.
Every automated decision has a full audit trail for compliance.

“Skilled, reliable, and easy to work with. Strongly recommend.”
— CTO, fintech client

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