For SMEs
Less manual work in your business. Systems your team can maintain.
No big programme and no yet-another-tool: we start with the process that hurts most and leave it running at your scale.
For businesses and teams that keep the day-to-day running on WhatsApp, calls, notes, spreadsheets or an ERP — and too much manual effort. Any starting point is fine.
Typical projects
How it usually starts.
Four common starting points for an SME or a small business. None requires a big programme: each piece works on its own and prepares the next.
Before you decide
When automation is worth it. And when it isn't.
Half of our job is saying no.
This is the test we apply before proposing anything.
Worth it when…
- The process repeats every week and eats hours.
- The rules can be written down: if this happens, do that.
- The data it needs already exists, even if scattered.
- There is a real bottleneck, not an occasional annoyance.
- An error can be caught and fixed with human review.
Not worth it when…
- The process changes every week: stabilise it first.
- The volume is so low it takes minutes by hand.
- Nobody can write the rule: the problem is definition.
- The only reason is that “everyone is doing it”.
- The process is broken: automating chaos only speeds up chaos.
How we start
Small, useful and maintainable by your team.
We look at the business with you
How you work today and where the time goes.
We start with one concrete need
A single process, actually working, in weeks.
We test it with you
You review it before it goes live; nothing runs unchecked.
We leave you the documentation
And show the team how to carry on alone.
The same way of working as our projects, at SME scale.
See projects in detailWhere the work gets stuck
What we usually find when we arrive.
- Buying the tool before defining the process.
- Automating a process nobody has stabilised.
- AI pilots with no owner, no data and no way to measure them.
- Systems that depend on a single person (or a single vendor).
- Measuring cost in licences only, not in the team's hours.
- Trying to do everything at once instead of starting where it hurts.
How we work
What we do to keep the solution useful and maintainable.
We automate the repetitive work; a person still makes the calls that matter
AI goes where there is repetitive text or data and a person who reviews: classifying, extracting, drafting, answering from your documentation. Not deciding on its own.
We size the system to the process, not the other way round
The controls match the process: an internal classification doesn't need the same checks as something that reaches a customer. No over-engineering, no fragile pieces.
We measure before we talk about results
Before we start we count how many hours that process takes and how many errors it produces; when we finish we look again. That way we know whether it worked instead of assuming it.
We choose the first piece with you: the one that gives back the most hours with the least risk.
Where to go next
Where you can start.
Four ways in, depending on what is on your table today. If you are torn between two, write to us and we will look at it together.
You don't know where to start
Assessment
A 30-minute call to size up the starting point.
A map of your systems and a phased roadmap.
You know which process to improve
Data, automation and AI projects
When a system needs to be built and implemented.
The process running and documented for your team.
The team needs to learn how to use it
Practical AI training
When the team needs to start using it well, now.
A team working from a shared base, on cases of their own.
Leadership needs context to decide
Executive talks
When leadership needs context before deciding.
A session that leaves the priorities and the questions on the table.
Common questions
Questions SMEs ask us.
Are we too small for this?
If a process repeats and eats hours, no. Projects are sized to the real problem; many useful pieces are deliberately small.
Do we need our data in order before starting?
No. Ordering the essential minimum is part of the work. Starting with one concrete process is usually the best way to order the data that process needs.
How much does it cost?
It depends on scope, and we don't make that up: the assessment exists precisely to size it. You start with small pieces that carry their own value, not a big closed programme.
What if we already use AI on our own?
Even better: there's experience to build on. The usual step is ordering that use — who uses it, within what limits and with what data — and turning what works into a system.
How do you avoid us depending on you forever?
We document what we build and train the team to run it. The pieces are deliberately small and maintainable: if you stop working with Dateliers tomorrow, the system keeps running and someone else can pick it up.
How are you different from an automation agency?
Before building anything we check whether the process is worth automating, and half our work is saying no. Then we implement, keep human review where it matters and hand the system over to your team. We don't resell licences or charge per tool.
Does this replace people?
That's neither the goal nor the usual outcome. It removes repetitive work and keeps review and the final say in the team, which gets its time back for what actually needs people.
If the day-to-day runs on manual effort, tell us where it hurts.
A 30-minute call, no commitment and no sales pitch. If an assessment is what you need, we'll say so; if it isn't, we'll say that too.
Tell us about your case