Engineering & delivery
Automate the work nobody should be doing by hand
Automation that takes out the repetitive work and the mistakes that come with it, so your team spends its time on the things only people can do.
What actually changes
Automation is mostly unglamorous, and that is the point
Demos are easy. What matters is whether it still works on a bad Tuesday when the input is messy and someone is on holiday. Here is the shape of a real process before and after.
A process before we touch it
Typical of what we find in a first engagement
- An order arrives by email and someone re-types it into the system
- A second person checks it against a spreadsheet that lives on a desktop
- Exceptions get resolved in a chat thread nobody can find later
- The monthly report is assembled by hand over two days
The same process afterwards
What we would typically automate first
- The order is parsed and written to the system automatically
- The check runs on every order, not the ones someone had time for
- Exceptions route to a named person with the context attached
- The report builds itself and is ready when the month closes
- 1 week
- Typical pilot length
- 2
- Processes in a first engagement
- 100%
- Customer-facing output reviewed
One process, measured before and after
Deliberately small. Breadth comes later
A person signs off anything a client sees
Where we deliberately leave a person
Anything that reaches a customer, moves money, or would be expensive to get wrong keeps an explicit human review step. A model that is confidently wrong is worse than a slow process, and we have seen enough projects fail on exactly that to build the checkpoint in from the start rather than after the first incident.
What we do
AI and automation capabilities
Workflow automation
The handoffs, approvals and re-keying between systems that quietly consume a day a week.
AI integration
Language models applied where they genuinely help, with a person accountable for anything a customer sees.
Data processing
Extraction, cleaning and routing of documents and records that currently move by hand.
Decision support
Surfacing the numbers your team needs to decide, rather than another dashboard nobody opens.
Human checkpoints
Explicit review steps wherever a wrong answer would be expensive. Automation should not mean unsupervised.
Measurement
Before and after numbers on the process itself, so you can see whether it actually worked.
How we work
Measure first, automate second
Most automation projects cannot say whether they worked, because nobody wrote down what the process cost beforehand.
See how we build the systems underneath- 01
Watch the work happen
We sit with the people doing the task. What the process document says and what actually happens are rarely the same.
- 02
Measure it before
How long it takes now, how often it goes wrong, and what going wrong costs. Without this, nobody can tell if the project worked.
- 03
Automate the boring middle
Start with the steps that are repetitive and low judgement. Leave the ones that need a person, because they usually still do.
- 04
Put a human at the risky edge
Anything that reaches a customer or moves money gets an explicit review step.
- 05
Measure it after
The same numbers as step two. If it did not move them, we say so rather than claiming a win.
Where it pays off
The work this suits
Operations and back office
Order processing, invoice handling and the re-keying between systems that never quite got integrated.
Customer service
Triage, routing and drafting, with a person approving anything that goes out under your name.
Reporting
Recurring reports that currently take someone two days and are out of date by the time they land.
Document handling
Extracting structured data from contracts, forms and PDFs that arrive in inconsistent formats.
Not sure which process to start with? The Automation Readiness Audit exists to answer exactly that before you commit to a build.