Case Studies

What we have built — and what it returned

Anonymised engagements from South African businesses across financial services, logistics and wholesale.

Case Study 1 · Financial Recovery Services

From 40 hours to 30 minutes per client

The challenge

A specialist financial recovery firm processed client data manually using Excel-based analysis. Each client engagement required approximately 40 hours of analyst time for a process that ran repeatedly.

What we built

A fully automated data intake and analysis pipeline. Client data uploads trigger an automated restore procedure, an optimised analysis script executes automatically, results populate a connected reporting layer, and output feeds directly into downstream calculation software.

The result

The same process now takes 30 minutes per client. The team handles significantly more clients with identical headcount. No SQL knowledge required from any staff member.

Case Study 2 · Transport & Logistics

Loss-making routes, identified and repriced

The challenge

A transport operator with a large fleet across multiple depots had no visibility into which routes and vehicles were profitable once fuel costs, maintenance schedules and toll fees were properly allocated against load revenue.

What we built

A real-time fleet profitability model pulling data from their fleet management system, cross-referenced against maintenance histories and fuel reconciliation data, visualised in a live dashboard accessible to operations and finance leadership.

The result

Loss-making routes identified within 30 days. Contracts repriced. Fleet deployment decisions based on actual margin data for the first time.

Case Study 3 · Wholesale Distribution

Every quote captured. Zero process change.

The challenge

A high-volume sales team managed customer quotes entirely through email. No system tracked which quotes had been sent, followed up on, or converted. Revenue was being lost to forgotten follow-ups.

What we built

A Copilot AI agent deployed into the sales team's Outlook environment. The agent reads outgoing emails, classifies potential quotes, extracts line items, cross-references the product catalogue in Sage, flags items not in current inventory, and logs everything to a SharePoint tracking list with automated follow-up reminders.

The result

Zero missed follow-ups. Full quote pipeline visibility. Sales team works exactly as before — the system captures everything automatically in the background.

Your business has at least one of these problems.

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