Automation
Less routine. More time for the work that counts.
We first understand your process and then automate what is worthwhile: data flows between your programs, requests find the right person, decisions stay with you.
- Process first, then technology
- With your existing programs
- People approve
- Trigger
Incoming request
Form or email
- Automatic
Capture data
Details into the right system
- AI
Categorize
Identify the request from free text
HumanUnclear: a person decides
with all details
- Automatic
Notify the responsible person
including confirmation of receipt
- Log
Document the case
logged traceably
Who this service is for
For recurring processes with clear inputs and outputs, where data is transferred between programs, emails or documents are sorted, or notifications are sent. Fixed rules are often enough; we only use AI where free text or documents need to be understood.
What we deliver
- Mapping the current process including exceptions and deciding what runs automatically
- Implementing the automation between your existing programs
- Error handling: retry, stop, notify
- Approval steps for people at critical points
- Log of actions
- Tests with real example cases and a pilot in daily operations
What we need from you5
- A contact person who knows the process and makes decisions
- Access to the programs involved (CRM, email, calendar, accounting, storage) with API access where possible
- Example cases and exceptions from daily work
- Decision on which steps require approval
- Feedback during the pilot
Requirements and limits5
- Rare cases, approvals with legal or financial consequences, sensitive customer conversations, and complaints remain manual.
- Processes that change constantly or are not clearly described are not suitable.
- If a program has no interface, alternatives such as an export or replacing that component are needed.
- Errors cannot be ruled out; for important results, a person checks.
- No fixed time savings are promised; whether the effort pays off is shown by the pilot.
Same process, two ways
Six manual steps in four programs become one process
On the left, the typical manual path of a request; on the right, the same process as a structured flow with automatic and manual stations.
ABefore: by hand
5 media breaksRead the request in the inbox
EmailType the details into the spreadsheet
SpreadsheetLook up or create the customer in the CRM
CRMAsk a colleague who is responsible
ChatWrite the confirmation by hand
EmailFile a note in the archive
Storage
BAfter: structured
Schematic- Trigger
Request arrives
Form or email
- Automatic
Capture details and transfer them to the CRM
- AI
Categorising requests
HumanA person reviews unclear cases
- Automatic
Confirmation of receipt and forwarding
- Human
The responsible person handles and decides
- Log
Case is logged
What it usually hinges on
- 01
Typing everything twice
The same address ends up in three programs, entered by hand each time. That costs time and causes typos that are often only noticed when the invoice goes out.
- 02
Inquiries get left behind
If nobody is explicitly responsible, the email sits in the shared inbox until someone happens to see it. The customer often notices first.
- 03
Processes aren't written down anywhere
Only the colleague in administration knows how it works. When she is on vacation or sick, people improvise, and everyone does it a little differently.
- 04
Automating without knowing the process
A Zapier flow here, a script there: eventually nobody knows what runs when and why. If something goes wrong, nobody notices until the customer asks.
Which process costs you the most time?
Describe it briefly. We will tell you honestly what can be automated and what is better left manual.
Workflow gallery
Five typical processes we automate
Choose an example. The graphics are schematic and show which stations run automatically and where a person decides.
From request to assigned case
Requests from forms and inbox land in the right system, structured. Whatever the AI doesn't clearly understand goes to a human.
- Trigger
Request arrives
Form or email
- Automatic
Capture details
CRM and customer management
- AI
Categorising requests
HumanUnclear: person reviews
- Automatic
Notify contact person
Confirmation of receipt to sender
- Log
Log the case
4 automatic stations1 with a person
Typical automations
FormCRM
The inquiry from the website lands in the right system with all its details, assigned to the right contact person, with an initial confirmation of receipt sent to the sender.
Emailstructured case
Incoming emails are read, sorted by topic, and created as a case. AI helps understand free text. Unclear emails go to a person.
Documentdata extraction
Invoices, delivery notes, or forms are read automatically and prepared. A person checks the detected values before they are processed further.
Appointmentnotification
Confirmation, reminder, and follow-up go out on their own at the right time, using the details from your calendar and your order system.
Inquiryresponsible team
Fixed rules send each case to the right place and send a reminder if it stays unhandled for too long. You set the rules, not a model.
Reportingregular overview
The figures for the Monday meeting are ready, pulled together from your systems, without copy-and-paste on Friday afternoon.
From everyday work
Inquiries at a trades business
An inquiry by form or email is captured, matched against customer data, and created as a job. The business gets back with a proposed appointment without anyone retyping anything in between.
Invoice preparation at a tax firm
Receipts are scanned, amounts and invoice numbers recognized, and handed over to the accounting software. Uncertain values are flagged, and you give the approval.
Onboarding at an agency
New clients or employees go through the same process every time: access, folders, welcome email, tasks in the project tool. Steps are forgotten less often.
Customer service in online retail
Standard cases such as shipping status or return labels are pre-sorted and answered. Complaints and special cases are forwarded to the responsible team along with the information collected.
Suitability check
Which tasks are suitable?
Five criteria decide whether automation is worthwhile. Give your process a rough rating.
How well does your process fit the criteria?
Assessment
Answer the five questions
Then we'll show you a rough assessment.
A rough guide, not an assessment of your case. The process analysis clarifies what is really worthwhile.
System integrations
Connecting systems
We work with the software you already have, as long as it offers an interface. You usually don't need new software for this.
- CRM and customer managementvia interface
- Email and calendarvia interface
- Spreadsheets and databasesvia interface
Your process
connects the programs you already use
- Accounting and document storagevia interface
- Project and task managementvia interface
- Your own software via APIsvia interface
Whether a program can be connected, we check before the quote. If an interface is missing, we discuss alternatives.
Transparency
Error handling and data protection
An automation does not always run without errors. That is why we plan from the start for what happens when something goes wrong and who is notified.
- Step is running
- Error is caught
- Retry or cancel
- A person is notified
Data protection and security
- At critical points a person gives approval, for example for payments or commitments to customers
- In case of disruptions, the automation catches the error, retries, or stops and notifies you
- Actions are logged so it remains traceable what happened and when
- Which data goes where and which service providers are involved is documented in advance
- We grant access and permissions only as far as the process needs them
Limits: what stays manual
- Rare cases, approvals with legal or financial consequences, sensitive customer conversations, and complaints remain manual.
- Processes that change constantly or are not clearly described are not suitable.
- If a program has no interface, alternatives such as an export or replacing that component are needed.
- Errors cannot be ruled out; for important results, a person checks.
- No fixed time savings are promised; whether the effort pays off is shown by the pilot.
Project process
From analysis to optimization
Six steps in which you can see at any time what runs automatically and what stays with you.
- 1
Analysis
Map out the current process together with you, including the exceptions
- 2
Analysis
Find bottlenecks and sources of error
- 3
Process design
Decide what runs automatically and what stays manual
- 4
Process design
Design the target process with error handling
- 5
Implementation and testing
Build the integration and test it with real example cases
- 6
Rollout and optimization
Pilot in daily operations, then measure and adjust
Costs
Why there is no flat rate
Every process is different. That is why we calculate only after the intro call and the process analysis, and we do not quote fixed prices up front.
- One-off
- No flat price. One-time costs cover process analysis, implementation, testing, and pilot; the quote follows after the intro call and the process analysis.
- Ongoing
- Ongoing: licenses for the services used, possibly usage-based fees for AI models, hosting, and support. Listed in the quote separately from the setup.
- Depends on
- Complexity of the processNumber of systems involvedNumber of special cases and approvalsVolume of processed cases
Result
What you get out of it
Less retyping and copying between programs
Inquiries are forwarded and don't sit in the inbox
Processes no longer depend on a single person
Traceable what happened, even when something goes wrong
Your team has more time for cases that require judgment
Actual results depend on the starting point, scope and implementation. We do not give guarantees of success.
Concept studies
Concept studies on Automation
Detailed scenarios for typical starting points and possible approaches. They are not reports on client projects.
- Scenario · not a client project
Automated reports · 14 min
Three revenue figures, a Monday morning and the question of which one is right
An automated report is only as good as the definition of its key figures: first the single truth, then the schedule, then the AI summary with source references.
Read concept study → - Expert analysis · not a client project
Reading documents · 14 min
The invoice has been read. But is it correct?
Reading is the easy part: what matters are validation rules, a queue for anything uncertain and an error rate that is measured rather than claimed.
Read concept study → - Expert analysis · not a client project
Error handling in workflows · 13 min
The workflow ran through. Only half the data never arrived
A workflow is only reliable once it is clear what happens when things go wrong: retry, set aside, report and trace instead of failing silently.
Read concept study → - Scenario · not a client project
Form to CRM · 14 min
Everything that can go wrong between clicking “Send” and the CRM entry
A contact form is only well connected when every inquiry is checked, assigned, confirmed and verifiably ends up in the CRM, even when something goes wrong.
Read concept study → - Concept study · not a client project
Process mapping · 13 min
Whoever automates the chaos gets faster chaos
Before a workflow is automated it has to be understood: a structured process mapping shows what is worthwhile, what has to change and what deliberately stays manual.
Read concept study → - Scenario · not a client project
Appointment reminders · 13 min
The empty chair at 10:15 a.m. and what it really costs
Anyone who combines reminders, cancellation via link and a waitlist into one process turns a silent no-show into a free slot that can be planned around.
Read concept study →
FAQ
Frequently asked questions
Which processes are suitable for process automation with AI?
Best are processes that occur often, follow fixed rules at their core, and have clear inputs and outputs. AI makes sense when inputs are unstructured, such as free text in emails or data in documents. Rare cases, or ones that must be weighed up each time, are less suitable. Often fixed rules alone are enough, without any AI, and then that is all we build.
Why do you start with the process and not the tool?
An unclear process does not get better through automation, only faster. In conversation it often turns out that steps appear twice, exceptions are written down nowhere, or two people do it differently. Only once the process is clear do we decide what can be automated. Sometimes the result is simply to drop a step.
Do we have to switch our software?
Usually not. We connect what you already use, as long as the programs offer interfaces. We check this before the quote. If a program has no usable interface, we discuss alternatives with you, such as an export or replacing that one component.
How much does an automation cost?
That depends on how complex the process is, how many systems are involved, and how many special cases there are. A simple connection between two programs is much more manageable than a process with document recognition and several approvals. There is no flat price. After the process analysis you receive a quote that lists the one-time setup and the ongoing costs (licenses, model usage, support) separately.
What happens if the automation makes a mistake?
We build in error handling for this: retry, stop, notify. Critical or unclear cases end up with a person, along with all the details of the case. All steps are logged so you can trace what happened. Errors can never be ruled out entirely, which is why a person checks important results.
How long does it take until an automation is running?
That depends on the process. A manageable connection can often be implemented in a few weeks; with several systems and approvals it takes longer. Most of the time usually goes not into building, but into clarifying the process and testing with real cases. We give a concrete schedule after the process analysis.
How is data protection taken into account?
We document in advance which data flows where and which service providers are involved, and choose them accordingly. Where possible, we give an AI model only the data it needs for the step. The legal assessment in each individual case, such as data processing agreements, rests with your legal counsel. We provide the technical overview for this.
How does this differ from an AI agent?
An automation follows a defined process: when this happens, that happens. It is easy to follow and reliable. An AI agent decides on its own within limits which steps to take and suits tasks with more leeway. Which is more sensible for your case, we clarify in the analysis.
Show us your process. We'll assess the automation potential.
In the intro call we walk through one process together and tell you what is worthwhile and what is not.