Case 01

Data capture from approved documents

Models propose, code decides.

Today

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.

Result

Before~6 weeks

After~1 week

One mark: one working day.

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.

The workflow

Comes in
Approved PDF documents, thousands of values
AI understands
What the code leaves open
- Narrow, individually checked tasks
- Every answer with its source down to the word
- A second, independent reading
Software checks
Reliable reading and checking every answer
- Words with position, tables, chapters, domain terms
- Rereads every source location and rejects mismatches
- Done only when two readings agree
Lands with a human
Only what is uncertain, with source and reason
- Confirm, choose between candidates or search
- Deviations from the database as findings

Code reads what it can read reliably. AI fills in the rest. The human reviews instead of typing.

Case 02
Articles from Researched Sources
Not every draft has to succeed. Only what passes the review gets published. AI writes. Rules decide what moves on. Humans set the rules.
Case 03
Social Media Posts for Every Article
Nobody writes posts anymore. A human decides what a post may do. AI picks and writes. Code checks and posts. A human sets the rules.
Case 04
Inquiries Captured in Conversation
A form asks what it knows. A workflow rarely fits into the first sentence. The agent asks. Software checks the brief. Only what a human approves is sent.
Case 05
Invoice and Purchase Order Verification
The standard case is rarely the problem. The effort comes from the deviations. Automate the standard. Give humans the exceptions.
Case 06
Quote Preparation from Customer Inquiries
The information for a quote already exists. It is just scattered. AI prepares the quote. The expert makes the decision.
Case 07
Technical Document and Compliance Review
The review takes expertise. Finding the evidence does not. AI prepares the compliance review. The decision stays with the responsible human.
Case 08
Customer Support → Engineering
The bottleneck is not the technical analysis, but the missing context. Engineering gets the relevant context before the actual analysis begins.
Case 09
Supplier Comparison in Purchasing
Every offer arrives in a different format. Comparison starts once they all look alike. AI structures the comparison. The purchasing decision stays with the human.
Case 10
Contract and Order Review
The goal is not to approve contracts automatically, but to find deviations reliably. AI finds, structures, compares and escalates. Humans decide and take responsibility.
Case 11
Master Data Cleansing and Entity Resolution
One company, three spellings, two IDs. An exact match will not find it. AI finds candidates. Rules limit the matching. Humans decide when in doubt. Only then does the system write.