Case studies
What we built, and what changed.
Each of these ran in production. Where a number appears, it came from the system rather than from an estimate. Where we cannot evidence something, it is not here.
These are live production systems. Client names are withheld under non-disclosure agreement.
78% reduction in manual processing time
Delivered in 6 weeks
The situation
An operations team managing complex programme delivery was spending over 60% of staff time on manual data entry, report compilation, and cross-referencing records across multiple spreadsheets. The process was error-prone, slow, and preventing the team from focusing on core delivery work.
What we built
We deployed a document processing AI pipeline that automatically extracts, validates, and categorises incoming reports and records. An n8n workflow routes data into the correct Airtable bases and triggers summary reports for programme managers, without any manual intervention.
What changed
£14,000/month saved in operational costs
Delivered in 4 weeks
The situation
A mid-sized consulting firm was manually processing client invoices, reconciling expenses, and generating monthly financial reports. Three members of the finance team spent an average of 2 days per month solely on invoice reconciliation. With a growing client base, this was becoming unsustainable.
What we built
We built a fully automated invoice processing system that ingests invoices via email, extracts line items using document AI, validates against purchase orders in their ERP, and posts approved invoices directly to Xero. A Slack notification alerts the finance lead only when human review is required.
What changed
Invoice cycle: 3 days → 4 hours
Delivered in 8 weeks
The situation
A logistics operation was losing competitive advantage due to a slow invoicing cycle. Invoices were manually compiled from multiple driver reports, fuel logs, and delivery confirmations, a process taking 3 full working days per billing cycle. Late invoices were causing cash flow problems and client dissatisfaction.
What we built
We integrated all data sources, driver apps, GPS systems, fuel cards, and delivery confirmation data, into a unified pipeline. An AI agent compiles draft invoices automatically, flags exceptions, and sends approved invoices to clients via the existing billing system. The entire cycle now runs overnight.
What changed
Next step
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