AI agents · Documents
Processing documents
with AI agents
Documents arrive as PDFs, scans, emails or office files and have to be sorted, read and transferred into systems. Agents can take over a large part of this groundwork. What matters is where a person deliberately checks.
From file to structured record
The flow has five stages. Which of them run automatically and where a person checks, we decide per document type.
01 Intake
Documents enter processing by email, upload, folder or from a business system.
02 Classification
The agent recognises the document type and assigns it to the right process or the responsible person.
03 Structured extraction
Relevant details are transferred into a fixed schema, such as fields, amounts, dates or tables.
04 Validation
Plausibility rules, a comparison with existing master data and flags on uncertain passages check the result.
05 Approval and handover
A person checks anything unusual. Then the record goes to the target system.
What it suits
Suitable are document types that occur in large numbers and in a recurring form.
Incoming mail and enquiries
Sort incoming documents, summarise them and pass them to the right person.
Quotes and contracts
Read key data such as parties, terms and amounts. The legal assessment stays with specialists.
Invoices and receipts
Read and check the details. Posting stays in the business system.
Technical documentation
Make extensive material searchable and summarise it selectively.
Internal knowledge collections
Make policies, manuals and project documents usable for questions and research.
Search and summaries in internal knowledge systems
Besides processing single documents, an agent can make bodies of knowledge searchable. It finds relevant passages, answers questions and names the source so the answer can be checked. The source's access rights stay in place: whoever may not see a document does not get an answer drawn from it.
Summaries point to the original passage. A short version then does not replace the document but leads into it.
Validation and human approval
For every detail, an agent gives an estimate of how sure it is. Together with fixed rules, this decides whether a record runs through or lands on a review list. Corrections from the review flow back and improve the rules.
Fully automatic processing only makes sense where an error is tolerable or easy to spot. Everything else gets human approval.
- Confidence values and plausibility rules
- Review list for anything unusual, spot checks for the rest
- Corrections improve the rules
- The target system only receives approved records
Limits
Poor scans, handwriting and strongly varying layouts lower the hit rate. There is no error rate of zero, and an agent does not replace expert review for decisions with legal or financial weight.
How well it works in your case only shows with real documents. That is why we start with a prototype on your material and measure the result before anything is rolled out. For an overview of agents in general see AI agents for business.
Our service for this
We deliver the topics on this page in the following service areas.
Frequently asked questions
Which file formats can be processed?
Typically PDFs, scans and images, emails and office files. Which formats work reliably in your case we check in the prototype with your real documents.
How accurate is the extraction?
It depends on document type, quality and layout. A universal figure would be misleading. In the prototype we measure accuracy on your material and decide which cases need a check.
Where are the documents processed?
In the EU cloud or on your own infrastructure, depending on the requirement. We define the data flows per project, see Data-sovereign generative AI.
Can an agent assess contracts legally?
No. It can read key data and summarise content. The legal assessment stays with specialists.
How is quality monitored in operation?
Through spot checks, metrics such as correction rate and processing time, and a log of every run. Notable changes lead to adjustments of the rules.
Related topics
AI agents for business
Basics, control and limits of agents.
Learn moreAI agents for CRM and HubSpot
Research and data upkeep in the CRM.
Learn moreIntegrating generative AI into existing systems
How results reach target systems.
Learn moreData-sovereign generative AI
Where documents are processed and who has access.
Learn more
Ready for your next project?
Tell us briefly what you want to achieve with generative AI. We advise you on content production, digital twins, AI workflows and integration, and get back to you within 24 hours with an initial assessment.