If a task happens more than once,
it should not require a human.
We map every repetitive process your team runs and automate it permanently. Emails, reports, approvals, data entry, removed from the workload.
Start a project →Why this matters
Most businesses automate nothing because they do not know where to start. We start with a workflow audit, identify the highest-cost manual processes, and eliminate them one by one.
- Workflow mapping and audit
- Email and notification automation
- Report generation and scheduling
- Cross-platform data sync
- Trigger-based actions
How to tell what is worth automating
The honest filter, before anyone quotes you anything. Automation pays when a task is frequent, identical every time, and currently done by a person reading one screen and typing into another.
It happens often enough to matter
Twenty minutes a day is eighty hours a year. Twenty minutes a month is not worth anybody building anything. Count it honestly before deciding, because the irritating jobs feel more frequent than they are.
It is the same every time
A task with four genuine exceptions is still automatable; the exceptions get handed to a person. A task that is different every time is a judgement, and automating a judgement badly is how businesses end up emailing customers nonsense.
Somebody is retyping
The clearest signal in any business is data being read off one screen and typed into another. Every instance of that is both a cost and a source of errors nobody is counting.
The cost of getting it wrong is survivable
Automate the invoice chaser before the invoice itself. Start where a mistake is an apology rather than a refund, and move inwards as confidence grows.
Nobody is defending it
If a process exists because one person likes it that way, the software is not the problem and building something will not fix it. That is a conversation, not a project.
What usually gets automated first
In rough order of how often we are asked, and how quickly each pays back.
| The job | What it looks like now | What it becomes |
|---|---|---|
| Chasing invoices | Someone remembers, looks up what is outstanding, writes a polite email. | A sequence that fires on its own, escalates on a schedule and stops the moment payment lands. |
| Getting an enquiry to the right person | An inbox everyone half-watches. | Routed by what was asked, logged against the company, with the clock running on a reply. |
| Reports | An hour every Monday exporting and pasting into a spreadsheet. | Built and sent before anyone is in. |
| Two systems disagreeing | Someone reconciles the website against the till on a Sunday. | One record, updated once, read by both. |
| Onboarding anything | A checklist in somebody’s head, performed differently each time. | The same steps every time, with the ones that need a person flagged to a person. |
| Documents | Copying the same details into a template and hoping the last edit was saved. | Generated from the record, filed automatically, same format every time. |
Where automation goes wrong
We have been called in to unpick each of these, so they are worth saying out loud.
It was built on a free tier that quietly stopped
A no-code automation hits its monthly run limit mid-month and simply stops. Nothing errors loudly. The first anyone knows is a customer asking why they never heard back.
It lives in one person’s account
Automations built under a personal login die when that person leaves, and nobody else can even see what existed. Anything that matters belongs in a company account with more than one person who can reach it.
It is fast and wrong
The entire value of a manual step is sometimes the half-second where somebody notices the number looks odd. Automating that away means the mistake goes out at scale. Thresholds and a human check on anything unusual are not optional.
Nobody can tell whether it ran
An automation with no log and no alert is a thing you have to trust. It should tell you when it ran, what it did and when it failed — and failure should be noisy.
It automated a bad process faster
The step before building is asking whether the task needs doing at all. A surprising number do not, and deleting a process beats automating one.
What a job looks like
| Stage | What happens | What we need from you |
|---|---|---|
| Week 1 | We watch the task being done, by the person who does it, at the speed they really do it. | An hour, and no tidying up beforehand. |
| Week 1 | A number: how often, how long, what it costs now, what is left after automating. If that number is not worth it we say so and stop. | Honesty about volumes. |
| Weeks 1 to 3 | Build, running alongside the manual process rather than replacing it. | Access, and someone to confirm the output matches what a person would have done. |
| Switch | The manual version stops. The log and the alerts stay. | A fortnight of somebody spot-checking. |
| After | 30 days on call, then a look at whether the saving was real. | Tell us if anyone has started working around it. |
If the arithmetic in week one says it is not worth building, that is a fine outcome and you will not get an invoice for the discovery.
Before you ask.
How do we know which processes are worth automating?
Will this put our staff out of a job?
What if the automation gets something wrong?
Do we have to replace the software we already use?
Ready to get started?
Tell us what you need. We will scope it, price it and build it.
Start a project →