Real projects. Measured results.
Every engagement includes a before-and-after view of hours, output and cost where the data is available. Here is one example.
SHOPFEVER: business development from 40 hours to 6 hours a week
The starting point
Shopfever, an e-commerce business, was spending about 40 hours a week on business development. That included prospect research, outreach, follow-ups, listing updates and reporting. Most of it was manual.
The work mattered, but it was repetitive and took time away from growth.
What we built
We mapped the existing tools, data flows and manual processes, then designed a set of bespoke automations around the stack Shopfever already used.
The workflows covered prospect identification and enrichment, outreach sequencing, response handling and internal reporting. The team was trained on each workflow, and the operating procedures were updated so the automation became part of the normal way of working.
The result, measured
- Business-development workload fell from 40 hours to 6 hours a week. The remaining time is spent on judgement and conversations rather than administration.
- Overall operational workload fell by more than 30% against the pre-project baseline, according to the project measurement.
- In the covered workflows, 90% of routine tasks now run automatically. Monitoring and alerts flag failures when they occur.
What happens after go-live
These systems only keep delivering value when someone owns them. Shopfever’s automations are monitored and maintained through our Care programme, with alerts, fixes and a monthly health report covering uptime, volume and hours saved.
That ongoing work matters because APIs change and models drift. Without an owner, results can quietly erode.
Want to see what this could look like in your business?
Start with the free AI Act self-assessment, or book a full diagnosis of your operations and current AI use.