Build 02 — AI Workflow Automation

Hours back in your
team's week, in 8 weeks.

Agent-driven automation for the repetitive, rules-based work eating your team's time — invoice processing, document triage, supplier coordination, status chasing, report generation. Built fast. Maintained from launch.

Who this is for

Built for teams
buried in repeat work.

01

Your team is brilliant — and buried.

Skilled people spending hours every week on admin, processing, lookups, reformatting outputs. Expensive time spent on cheap work. Margin you can't recover.

02

The work follows clear rules.

Even when it spans multiple systems and needs occasional judgement, the underlying logic is documentable. If a human can explain the steps to a new hire, an agent can learn them.

03

You need impact in weeks, not quarters.

You're not signing up for a 12-month transformation programme. You want hours back this quarter and a clear ROI by next.

What you walk away with

Repeat work running on autopilot.
Senior time recovered. Margin restored.

Live automation flows.

Running end to end across your existing systems — no rip-and-replace. Built on proven agent platforms (n8n, Make.com, agent frameworks) with AI inside where it earns its place.

A team that has its week back.

20–40 hours per week recovered, depending on scope. Senior people focus on the 20% that needs them; the agents handle the 80% that doesn't.

Integration with your existing stack.

Designed to fit how you already work — your CRM, your email, your document store, your reporting layer. The agents slot in.

A partner who stays.

Application Maintenance keeps the automations running, handles edge cases, and adds new flows as your team's needs evolve.

What you might automate

Common patterns we've delivered.

Invoice and document processing

Incoming PDFs parsed, classified, and routed; data extracted into your accounting or operations system.

Email triage and response drafting

Incoming queries categorised, prioritised, and drafted with proposed replies for human review.

Supplier and client coordination

Automated status chasing, scheduled check-ins, structured data captured back into your records.

Report generation

Operational and compliance reports compiled from multiple data sources, delivered on schedule, with exception handling.

System-to-system data flows

Replacing manual rekeying between tools that don't natively talk to each other.

Compliance paperwork

Drafted from structured inputs, routed for sign-off, archived to your records system.

How we build this

The Science of AI Automation™.

Standard composition: 1× R&D Sprint + 3× Dev Sprints. Typical 6–8 weeks elapsed.

Hypothesis
Stage 01 — Hypothesis

R&D Sprint — 5 days

Workflow mapping, automation scoping, integration plan. Output: a build brief showing exactly which flows get automated and what they'll cost to run.

Experiment
Stage 02 — Experiment

Build the highest-leverage flow first

One flow built end-to-end and run alongside the human process. Real data. Real conditions. Edge cases surface early.

Formulation
Stage 03 — Formulation

Refine + extend

Edge cases handled, exception paths designed, team-review checkpoints embedded. Additional flows built and integrated.

Execution
Stage 04 — Execution

Hand-over and maintenance

Your team trained on supervising the agents. Application Maintenance keeps the flows running and handles edge cases as they surface.

Ready to put repeat work on autopilot?

Start with the diagnostic.
Or book your R&D Sprint.

5 minutes for a personalised shortlist. Or 5 days for a costed build plan.