Segment 02 / 04
AI Automation · Cloud & localAI that reads along and thinks ahead.
AI understands documents, emails and requests and makes decisions or prepares them. Used above all where rule-based workflows reach their limits. With powerful cloud models, or locally when data must not leave the building.
- Documents & emails
- Cloud or local
- Built into workflows
- People decide
What is AI automation?
AI automation takes over the steps where fixed rules fail: understanding emails and documents, classifying cases, making decisions. To do this, we combine language models with decision models (System 1). Embedded in a workflow, not as a chat window on the side.
Content needs to be understood.
Free text, changing layouts, concerns and tone. Wherever a fixed rule reaches its limits.
The path is always the same.
Then a workflow or a software robot is enough, more reliable and cheaper to run.
Read.Understand.Prepare.
Where AI really helps.
Wherever someone reads, classifies and summarizes today before the actual work begins.
Extract documents
Invoices, delivery notes and contracts: recognize and assign data, even in unfamiliar layouts.
Classify inquiries
Recognize topic, urgency and responsibility and route them to the right place.
Prepare replies
Drafts in your company's voice. Your team reviews, adjusts and sends.
Summarize & analyze
Condense long texts, minutes and reports to the essentials and flag anything unusual.
Unlock knowledge
Answers from your own documents, manuals and archives, instead of searching for ages.
One workflow, told twice.
Example incoming invoice. Once the way it is processed by hand today. And once the way it runs when every tool takes on the step it does best.
- Invoice arrivesby handWorkflow
- Recognize supplier, amounts and line itemsby handAI
- Match against the orderby handAI
- Book in the legacy systemby handRPA flow
- Approve above an amount thresholdby handYour team
Cloud & local
For language and complex tasks, we use powerful cloud models, for example Claude by Anthropic or GPT by OpenAI. If data should not leave the building, models run locally on your own hardware, without ongoing per-request fees.
One tool alone is rarely enough.
AI is one of four segments. Only together do they create processes that run end to end: AI for content, robots for programs, workflows for APIs, Extensions & Tools for everything missing in between.
Not every step needs AI.
AI is powerful, but not always the best choice. We use it where rule-based workflows reach their limits or where it genuinely makes a step better, and keep fixed rules where they are more reliable and cheaper.
From the first conversation to a running workflow.
Understand
You show us the process and the systems involved. We work with what you give us.
Implement
We build the automation with the right tools and connect it to your systems.
Support, on request
Automation is a marathon, not a sprint. If you wish, we keep looking after your workflows and adapt them when something changes.
Frequently asked questions.
Cloud AI or local AI?
Cloud models, for example Claude or ChatGPT, are strong at language and complex tasks. Local models score on data protection and running costs. Which route fits depends on your data and requirements. We work that out together.
Where is our data processed?
Wherever you want. In the cloud, on your servers or with local AI entirely in-house.
Can AI make mistakes?
Yes. That is why a person stays in the loop for important decisions. The AI prepares, your team decides.
Do we need our own hardware for local AI?
Yes, a suitable computer or server. What is needed depends on the model and the volume of requests.
Which models does aeovi use?
For example cloud models from Anthropic (Claude), OpenAI (GPT) and Google (Gemini) as well as local models. Which one fits depends on the task and the data.
What does an automation cost?
That depends on the process: what exactly it looks like, how complex it is from an automation perspective, how many systems are involved and how often it runs. You get a reliable estimate once we have aligned and clarified all points together.
Which workflow should run on its own next?
Describe it briefly. You will get a concrete proposal for what it could look like automated.