We automate only once the process is right
First we look at how work really gets done at your company. Then we use AI exactly where it takes work off your hands and pays off. If you already run a system, we connect to it. If you do not, we look at which system fits your use case best.
The same process, without the retyping in between
Before we talk about an AI tool, we look at what actually happens today: where data is entered twice, where a call turns into a slip of paper, where a report costs a day of work. Only then do we use AI where it removes friction.
| Process area | Today | With AI in the process | Where it flows |
|---|---|---|---|
| Sales and CRM | Calls are noted down, inquiries entered later, some are left lying | The inquiry is captured during the call, classified and summarized | Your CRM, Odoo or another system |
| Finance and Accounting | Invoices are opened one by one, read and retyped | Line items are read out and matched with the order | Your accounting, Odoo or another system |
| Warehouse and Logistics | Reorder points are estimated from experience or an Excel list | The need to reorder is recognized before stock runs out | Your warehouse system, Odoo or another system |
| Support and Service | Every ticket is read and assigned, even the ones that are always the same | Requests are classified, recurring cases answered directly | Your helpdesk, Odoo or another system |
| Reporting and Management | The monthly figures are compiled by hand before the meeting | The summary is produced from the data in the system and reviewed | Your reporting, Odoo or another system |
We think about this independently of any system. If you already use a system, we connect to it. If you do not have one yet, we evaluate together which system fits your use case and build the automation on top of it.
We developed six modules ourselves, for automation and AI in Odoo. So we do not just pick from what the market offers, we build the parts that are missing.
Which of these areas costs you the most time?
Name one. We look at what actually happens there today and tell you whether automation pays off.
Area by area, not tool by tool
No general AI lecture. Choose an area to see what we check in concrete terms and what a good result looks like.
How inquiries come in today, by phone, form or directly, who classifies them and at which point between first contact and quote something gets stuck.
A voice assistant takes incoming calls and captures the request. A second step drafts the quote according to your stored pricing logic.
Every call becomes a record in the system and not a slip of paper on a desk.
Volume and form of incoming invoices, how many of them pass through a hand before posting and where assignment errors occur.
Documents are read out, the posting is suggested and deviations are flagged for review.
Accounting reviews and approves instead of entering.
How reorders are decided today and how often shortages or overstock actually occur.
Demand patterns are observed and order suggestions are generated before stock runs out.
Reordering becomes a review step and not a feat of memory.
Ticket volume, response times and how many requests are actually recurring rather than technically difficult.
Incoming requests are classified, recurring cases answered and the rest passed on with the full history.
Your team spends its time on the cases that need a person.
Which reports are produced by hand every month and how much time that costs someone who has more important things to do.
The summary is produced directly from the data in the system and reviewed by a person.
The report is there before the meeting and not the night before.
AI speeds up every process. Including the wrong one.
A process that does not run smoothly only becomes faster and more uneven with an AI agent. That is why we go in this order every time.
Understand
What actually happens today, step by step, and not what the org chart claims.
Simplify
Cut steps that only exist because it has always been done that way.
Standardize
One consistent process, so the automation finds something reliable.
Digitize
The process moves into the system, and not just the paper around it.
Automate
This is where the AI agent comes in, only once the first four steps hold.
Measure
Check whether time is actually saved, and adjust. An agent is not something you set up and then forget.
- analyze context
- reduce process
- define rules
- automate input
- link workflows
- evaluate results
- Step 1 of 6
- Step 2 of 6
- Step 3 of 6
- Step 4 of 6
- Step 5 of 6
- Step 6 of 6
These are the workflows we implement today
It is not the vendor that counts, but what ends up running. A selection of concrete workflows. Which technology works behind them, we decide by use case and regardless of which system you use.
Call answering and appointment booking
Incoming calls are answered, the request is captured during the call and an appointment is entered directly in the calendar or the system, also outside opening hours. The caller learns at the start that they are speaking with a system.
Capturing inquiries by phone
Inquiries are taken in a structured way during the call, classified and created as a record, with a summary before anyone calls back.
Appointment and payment reminders
Reminders about agreed appointments and open payments, to existing customers who have agreed to this. Every call is logged and written back to the system. Advertising calls without prior consent are not permitted in Austria, which is why cold calling stays out.
Invoice and document processing
Incoming invoices and delivery notes are read out, matched with the order and suggested for approval, instead of being entered one by one.
Classifying and answering requests
Incoming requests are classified, recurring cases answered directly, difficult cases passed on to the right person with the full history.
Information on orders and returns
Customers get information on delivery time, status and returns, also outside opening hours and without a waiting queue.
How we choose the technology behind it: telephony and speech call for a voice platform, document-heavy processes for an extraction engine, multi-step back-office processes for an automation framework. We take this decision off your hands, with an open interface to your system.
Your process is not on the list?
The list is a selection, not a limit. Describe your case, and we will tell you honestly whether it suits automation.
A concrete plan instead of a slide about AI transformation
This is how the assessment runs up to the recommendation, with process management instead of gut feeling.
Kickoff
Conversation with those responsible: which three to five areas cost the most time today and what success means for you in concrete terms.
Process capture
Conversations with the people who do the work every day, not only with management. Step by step: where the data comes from, where it goes, which Excel lists run alongside in the background. Plus the volume figures: calls or invoices per month, handling time per case, error rate, peak times.
Assessment and ranking
Every captured step is rated by effort, meaning time multiplied by frequency, and by automation potential. A value matrix instead of a gut decision.
Target concept per candidate
Sketch the target process for each candidate: what the system takes over, what stays with the person, where the handover point is. Plus the connection to the system in which the process is meant to run.
Recommendation for the start
Selection of the candidate with the best ratio of effort, risk and visible benefit, with success criteria that are fixed before the start and not after.
Plan for the rollout
Order of the further candidates, training needs in the team and the rhythm in which results are measured. This ties in with the sixth step of our approach.
Questions that come up in almost every conversation about AI
Tell us which process costs you the most time today
We will tell you honestly whether AI is the right lever here or whether the process itself needs attention first.