Artificial intelligence

AI process automation

AI works inside your processes, not alongside them: it reads documents, extracts data, classifies issues and proposes the next action. You keep the decision and the traceability.

Where the AI comes in, and where it does not

Automating with artificial intelligence inside a process means the model does the mechanical work — reading a document, extracting its data, classifying an issue, proposing the next action — while the decision with consequences stays with an identified person. That separation is not a design preference: Regulation (EU) 2024/1689 classifies certain employment uses as high risk and requires effective human oversight over them.

Content reviewed on 25 August 2026

European framework: Regulation (EU) 2024/1689 In force since 1 August 2024, with staggered application
Prohibited practices: Applicable since 2 February 2025 Including emotion inference in the workplace (art. 5)
High-risk systems: Employment and worker management Annex III: recruitment, promotion, task allocation and evaluation
Human oversight: Art. 14 of the Regulation Must allow understanding, monitoring and disregarding the system output
Traceability: Every proposal is logged With who accepted it, who rejected it and on what input

Document reading

Invoices, delivery notes, certificates and contracts turned into usable data.

Automatic classification

Issues, emails and non-conformities routed to the right owner.

Suggested actions

Suggests root cause and corrective action based on your company's history.

Natural-language search

Ask for what you need and the platform finds the record and its evidence.

Where it applies

Use cases already running

Reading supplier invoices and delivery notes
Classifying client issues by type and severity
Summarizing audits and spotting recurring findings
Validating subcontractor coordination documents
Extracting data from receipts and expense claims
Drafting report summaries from process data

Real examples

Automations that hold up

Property management

Classifying incoming issues

Before Two hundred emails a day that somebody reads to decide whether they are a fault, a complaint or an administrative query.

After The model proposes type, urgency and owner. The person confirms or corrects, and that correction feeds the next classification.

Industrial procurement

Reading delivery notes from many suppliers

Before Every supplier has its own layout. Extraction templates break each time somebody redesigns theirs.

After The model interprets the document without a prior template and checks what it extracted against the purchase order. Only what does not match goes to review.

Quality

Drafting a new procedure

Before Starting each new procedure from scratch, or copying the one from another standard and adapting it by hand.

After The process is described in plain language and the AI proposes flow, fields and approvals. What gets published is reviewed and signed by a person.

Vocabulary

Applied AI, without the hype

Information extraction: Obtaining specific fields — amount, date, reference — from an unstructured document. Different from OCR: OCR transcribes, extraction interprets.
Human in the loop: A design where the machine proposes and the person decides. It is what art. 14 of the AI Regulation requires for high-risk systems.
High-risk system: A category in the European regulation covering uses with significant impact on rights, including recruitment and performance evaluation. It carries documentation, logging and oversight obligations.
Hallucination: A model output that sounds plausible but is false. In a business process it is countered by grounding the input in the real document and requiring human verification wherever there are consequences.
Decision traceability: A record of what data went in, what the model proposed and what the person decided. Without it the automation cannot be audited or sensibly corrected.

Frequently asked questions

What people ask us before getting started

Does my data train third-party models?

No. Processing runs on controlled infrastructure and your data is never used to train external models.

Does the AI decide on its own?

It proposes; approval is still made by a person and is logged like any other step in the workflow.

Does it work with our specific documents?

It's tuned to your own document types during setup.

What does the European AI Regulation say about this?

Regulation (EU) 2024/1689 has been in force since August 2024 and classifies certain employment uses — recruitment, promotion, task allocation and evaluation — as high risk, with obligations on documentation, logging and effective human oversight.

Are any AI uses prohibited at work?

Yes. Among the prohibited practices in art. 5, applicable since February 2025, is inferring the emotions of people in the workplace, save for narrowly defined medical or safety exceptions.

What does human oversight actually mean?

That the person can understand what the system proposed, monitor how it behaves, and disregard the proposal. An accept button nobody looks at is not oversight, and art. 14 of the Regulation frames it in those terms.

Is there a record of what the AI proposed?

Yes: what data went in, what the model proposed and what the person decided. Without that record the automation cannot be audited or sensibly corrected when it fails.

What if the model gets it wrong?

The person corrects it, as with any proposal. What matters in the design is that the error is cheap: the AI never executes on its own a step with contractual, financial or employment consequences.

Bring us your most repetitive process

We'll show you the module running with data similar to yours.

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Keep exploring

Sources

Where each figure comes from

References to the official text in force. If a standard is revised, this page is updated and the review date says so.

Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence EUR-Lex · 13 June 2024
Spanish Agency for the Supervision of Artificial Intelligence (AESIA) Government of Spain · Official portal
Regulation (EU) 2016/679 (GDPR), art. 22: automated decisions EUR-Lex · Applicable since 25 May 2018

AI-powered process automation

Kimobox includes AI process automation: document reading and data extraction, automatic classification of issues and documents, suggested corrective actions, and natural-language search across the platform's records.

AI runs as just another step in the workflow, with human oversight, full traceability of every decision, and data processing on its own GDPR-compliant infrastructure.