AI challenge

Process documents, messages, emails or requests automatically

A lot of administrative work starts with the same pattern: something comes in, someone reads it, pulls out the important information and enters it somewhere else. That is where AI and regular automation can work well together.

Does this sound familiar?

This fits especially when employees spend a lot of time on recurring reading and data entry.

  1. A lot of information comes in as free text

    Emails, forms and documents don't have a fully fixed structure.

  2. Employees keep extracting the same data

    Names, amounts, categories, dates or other attributes are copied by hand.

  3. A predictable workflow follows

    Information is entered, assigned, answered or forwarded.

  4. Not every case can be fully automatic

    Some documents are incomplete, exceptional or too important for automatic processing.

Where do you want to be?

You want to process faster without uncertain AI output automatically ending up in your systems as the truth.

Recognise information automatically

Important fields, topics or intents are extracted from unstructured input.

Pass it on automatically where possible

Reliable cases move to the next step without manual retyping.

Exceptions go to a person

Doubtful cases are deliberately set aside for review.

Why does this happen?

Document processing looks like a single AI task at first sight, but a reliable solution consists of several technical steps.

See how we approach this

Input varies

Layout, writing style and completeness differ per sender or document.

AI output has to be validated

A plausible answer is not automatically correct data for an administrative system.

Processing ends somewhere else

The extracted information usually has to go on to a CRM, ERP, tickets or other software.

Why 9to5 for this?

In document automation, the difference between a demo and a usable system lies in everything around the model output.

View cases

Validation is part of the design

Extraction is not blindly treated as correct data.

Human-in-the-loop for exceptions

Doubtful cases can be reviewed without making the whole flow manual.

The chain gets finished

We connect the output to the systems where the work continues.

What else fits your situation?