What this costs you today
The processes below are the ones that consume the most hours in this sector. Work out which apply to you, and the annual figure is the budget the manual version is already spending.
| Done by hand today | Hours / week | Cost / year | After automation |
|---|---|---|---|
| Client intake and re-keying details | 3–6 hrs | €3,450–€6,900 | A structured intake writing straight into the matter record, removing the retyping step entirely. |
| Chasing outstanding documents | 3–5 hrs | €3,450–€5,750 | Outstanding items tracked with reminders sent automatically, so chasing is a system behaviour rather than a person’s task. |
| Extracting data from incoming documents | 4–8 hrs | €4,600–€9,200 | Fields extracted for a human to confirm rather than type. Confirming is far faster than transcribing. |
Annual figures are the stated weekly hours multiplied by 46 working weeks at a €25 hourly loaded cost. They are arithmetic on a typical range, not results measured at a client — substitute your own hours and rate for a figure that means something.
Where the time actually goes
Intake handled over email
Client information gathered in a thread, then retyped into whatever system holds the matter. Slow and lossy.
Documents chased manually
Someone tracking who has sent what, and following up by hand when they have not.
Follow-up depends on memory
The next contact happens when someone remembers it should, which means the quiet clients get quieter.
What gets built
Structured intake
A single intake flow that writes directly into the matter record, removing the retyping step entirely.
Document collection and reminders
Outstanding items tracked automatically with reminders sent on a schedule, so chasing is a system behaviour rather than a person’s task.
Document data extraction
Key fields pulled from incoming documents into the record, with a human review step where accuracy matters.
Scheduled follow-up
Next-contact dates derived from the matter type and enforced by the system.
Services that fit this sector
The service lines that solve the problems above, in the order they usually get built.
Visual automation that a developer can maintain and a non-developer can understand.
A client system shaped around how you actually work, not the other way round.
Language models wired into production systems that actually do useful work.
Retrieval-augmented generation systems that answer from your documents, tools, and business data.
Making the tools you already run behave as one system.
How a project runs
The same sequence every time, whichever service or market is involved. It is deliberately front-loaded: most of the risk in an automation project sits in understanding the process, not in building it.
Map the process before writing anything
The first session is spent on how the work actually happens, which is almost never how the documented process says it happens. Who touches what, in which order, and where the time really goes. Most failed automation projects failed here rather than in the build, because they automated the described process instead of the real one.
Measure the cost of doing nothing
Hours per week, error rate, and what those hours would otherwise be worth. This is what decides whether a process is worth automating at all — and it is also the number you compare against afterwards, which is why it gets recorded before anything is built rather than estimated after.
Build the smallest useful version
One process, working end to end, in production, before anything else starts. A narrow system that people actually use beats a broad one that waits on a second phase, and the edge cases that matter only surface once real work runs through it.
Run it against reality
The first two weeks of live use produce more design corrections than any amount of planning. Failures get surfaced loudly, retried and logged, because silent failure is the most expensive property a workflow can have and the one noticed last.
Hand it over properly
Documentation, credentials, and a walkthrough with whoever will maintain it. A system only one person understands is a liability regardless of how well it runs, so handover is part of the work rather than an optional extra at the end.
Ways to work together
Three arrangements cover almost every engagement. Most start with the first or the second; the third only makes sense once something is live.
Fixed-scope project
One defined process, a fixed price and an agreed definition of done. The right fit when the problem is clear and bounded — an order flow to connect, a CRM to build, a reporting pack to automate. Most first engagements are this, because it lets both sides find out how the other works without a long commitment.
Assessment first
One to two weeks mapping processes and measuring where the hours actually go, ending in a ranked list with effort and payback estimates. Useful when there is a backlog of automation ideas and no agreement on which matters. The document stands on its own and is yours whether or not you build anything with me.
Ongoing retainer
A recurring block of time for maintenance, extension and new automations once systems are live. Integrations break when the systems either side of them change, and a retainer means that gets fixed before it becomes an outage rather than after.
How the working relationship is set up
Remote, with real overlap
Work is delivered remotely. Across Europe and the Nordics the working day is effectively identical; in the Gulf it starts three hours ahead, which still leaves your full morning covered. There is no local office in any market, and none is claimed anywhere on this site.
You own what gets built
Source code, infrastructure and data stay yours. Systems are deployed on infrastructure you control — your server, a European provider, or a VPS in your own account. There is no per-seat licence and no dependency on me continuing to be involved.
Self-hosting is a first-class option
Self-hosted n8n, self-hosted databases and locally run models are all supported and, in several of these markets, preferred. Where no data may reach a third-party API, that constraint shapes the architecture from the start rather than being retrofitted.
Direct contact, one person
You deal with the person building the system. There is no account manager relaying requirements, which is the main practical advantage an independent consultant has over an agency at this size — and the main reason scope stays honest.
Frequently asked questions
Will AI be making decisions about our clients?
No. In professional services the useful automation is administrative — intake, extraction, reminders, routing. Anything touching advice or judgment stays with a person, with the system handling the paperwork around it.
How accurate is automated document extraction?
Accurate enough to draft, not accurate enough to file unreviewed. The correct design puts extraction in front of a human who confirms rather than transcribes, which is still a large time saving over typing from scratch.
What if we are not sure automation is the right answer?
Then the assessment is the right starting point, and it is designed to be able to conclude that you should not automate something. A process that is broken should be fixed before it is automated, and one that runs twice a month rarely earns the build. Receiving that answer in week one is far cheaper than discovering it after a project.
We have been burned by a failed automation project before.
That is common, and the cause is usually scoping or adoption rather than technology — a system built for the documented process rather than the real one, or one nobody was trained to maintain. Both are addressed by mapping the real process first and treating handover as part of the work.
How do we avoid depending on one person?
By owning everything: source code, infrastructure, credentials and documentation, with a walkthrough for whoever maintains it. The test is whether another developer could pick the system up from the repository and the documentation alone, and that is the standard handover is written to.
Is our data safe?
It stays where you need it to. Systems can run entirely inside your own infrastructure, including self-hosted models where no data may reach a third-party API. Where GDPR applies, data stays in the EU by default, with named access control and audit logging as standard rather than as an upgrade.
How quickly can something be running?
A first working version of a single process is typically weeks rather than months. Larger platforms are sequenced as modules so something is in production early and the rest builds on a foundation that already survives real use.