Process mapping & automation audit
Every step listed, with the ones worth automating separated from the rest.
AI Integrations & Automation
Connecting the tools you already pay for and automating the work between them — with AI handling the steps that used to need a person to read something.
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Automate the reading, not just the copying
Classic automation moves data between systems when the shape is fixed. It falls over the moment a step requires judgement: reading a supplier invoice, sorting an inbox by intent, summarising a call, extracting the details from a WhatsApp order.
Those steps are exactly where AI earns its cost. We map your process, automate the mechanical parts conventionally, use models only where reading or classifying is genuinely needed, and put a human check on anything that touches money.
What's included
System integrations
CRM, accounting, e-commerce, email and WhatsApp connected properly.
Document & message extraction
Invoices, purchase orders and chat orders turned into structured records.
Classification & routing
Inbound email and enquiries sorted by intent and sent to the right person.
Human review & audit log
A checkpoint on anything financial, and a record of every automated run.
How we work
Map it, split it, automate the right half
Map
Document the process as it actually runs, including the exceptions.
Pilot
Automate one step end to end and measure the time it actually saves.
Expand
Roll out to the rest, with fallbacks for when a model or an API is down.
Monitor
Alerts on failure, a cost dashboard and a monthly review of exceptions.
What you get
- Process & automation map
- Live integrations
- Extraction & routing rules
- Monitoring & cost dashboard
- Runbook & handover
The outcome
A week of admin that stops happening
Invoices, orders and enquiries processed without anyone retyping them, systems that agree with each other, and a clear log of what ran, what it cost and what it flagged for a human.
Related work
Frequently asked questions
What if the AI extracts something wrong?
Anything financial goes through a human confirmation step, and low-confidence extractions are flagged rather than committed. The automation is built to escalate, not to be brave.
Do we need new software for this?
Usually not. Most of the value comes from connecting what you already pay for. We tell you when a new tool is genuinely needed and what it costs.
How do you prove it saved time?
We measure the manual baseline before automating, then report against it. If a step turns out not to be worth automating we say so and stop.
What happens if the model provider goes down?
The automation queues the work and alerts someone rather than dropping it silently. Silent failure is worse than a delay, and it is the failure mode we design against first.
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Team retyping data between systems?
Describe the process end to end, and we will tell you which parts are automatable today.
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