Selected cases from engineering, finance, purchasing, sales, marketing, support, legal and content.
Three workflows in daily use, each from analysis to operation. The two largest took around three months of work each.
In regulated environments, experts transfer long, approved PDF documents with thousands of measurements, criteria and judgments field by field into a database that then counts as the binding source.
Code with the harness completes 70% of the fields, the human confirms 20% by choosing, 10% remain rework. Around 80% less working time per document.
An article needs research, reliable sources, text in German and English, metadata and images in four formats.
Around 93% less work per article. The agent takes over research, writing, translation, metadata and images; the human keeps the approval.
Writing the right post for X and LinkedIn for an article, checking link and preview image and publishing takes around half an hour and often gets left undone.
One post on X and LinkedIn every 48 hours, with no manual work per post. The rules stay with a human: tone, platforms, cadence and the accounts.
In subject matter, the cases have little in common. In structure, they are the same: AI and software take the steps, and the decision lands with a human.
AISoftwareHumanOne mark: one work step, in workflow order.
Case 02
Not every draft has to succeed. Only what passes the review gets published.
Case 03
Nobody writes posts anymore. A human decides what a post may do.
Case 04
A form asks what it knows. A workflow rarely fits into the first sentence.
Case 05
The standard case is rarely the problem. The effort comes from the deviations.
Case 06
The information for a quote already exists. It is just scattered.
Case 07
The review takes expertise. Finding the evidence does not.
Case 08
The bottleneck is not the technical analysis, but the missing context.
Case 09
Every offer arrives in a different format. Comparison starts once they all look alike.
Case 10
The goal is not to approve contracts automatically, but to find deviations reliably.
Case 11
One company, three spellings, two IDs. An exact match will not find it.
AI understands what arrives unstructured. Software checks what is unambiguous. A human gets what needs a decision.
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