BUILD · Delivery Challenge

Process Automation

"Too much manual work, not enough people." - We hear this often. We build AI agents that handle the repetitive tasks, freeing your people for the work that matters.

The Problem

What this looks like

  • Staff spend hours on repetitive data entry across multiple systems
  • Reports assembled from five different sources every week by hand
  • Approval workflows managed through email chains
  • The same questions answered repeatedly by senior people
  • Bottlenecks at specific people who hold institutional knowledge

What it costs you

  • 20-40% of knowledge worker time on tasks that add no strategic value
  • High error rates from manual data handling
  • Decisions delayed waiting for information that should be instant
  • Staff frustration and turnover - good people leave repetitive roles
  • Cannot scale operations without hiring proportionally

The real risk

Manual processes do not scale. As you grow, you either hire proportionally (expensive) or quality degrades. Competitors with automated operations serve more customers with fewer people.

Our Approach

Our approach is sequenced by pillar:

1

THINK

Not every manual process is worth automating. Before building anything, we map your operations to identify where automation generates the highest return - not the most interesting problem technically, but the one that frees up the most time or eliminates the most error. One focused session. The output is a scoped brief for the automation with the strongest business case.

2

BUILD

We build the automation for your specific workflow. Not an off-the-shelf integration that requires your process to fit the tool. Purpose-built for how your business actually operates, with the data sources you have and the outputs your team actually uses.

3

TEACH

Once the automation is running, your team needs to understand AI well enough to extend it, maintain it, and identify the next opportunity. The AI Foundations Programme gives every relevant team member an accurate mental model of AI - not just of the specific automation we built, but of the category of capability, so they can make good decisions about what to do next without depending on us for every change.

Expected Outcomes

50-70% reduction
Time savings on automated tasks
Industry benchmark (RPA and intelligent automation adoption)
80-95% reduction in manual data handling errors
Error rates
Industry benchmark (automation vs manual processing)
5-10x faster for rule-based workflows
Processing speed
Industry benchmark (workflow automation)
Demonstrated within 4-6 weeks
ROI timeline
Fognini engagement model

Free Your Team From Manual Work

Let's identify your highest-impact automation opportunity. Start with one process, prove value in weeks.

Frequently Asked Questions