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AI & Automation · Process automation

Process automation

Document processing, data transfer, triggering cases: the processes that run today through inboxes and spreadsheets are taken over by a system. Exceptions land visibly with a human.

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01 How you recognise it

Does this sound like your situation?

Three starting points we see regularly. One of them is enough.

  • 01

    Orders and invoices get typed in

    From email, PDF or portal into the ERP, every day, with the errors that come with it.

  • 02

    Enquiries and tickets are distributed by hand

    Classify, prioritise, assign, clarify. Until then the customer waits.

  • 03

    Onboarding runs on checklists

    Recording data, creating accounts, assigning tasks, tracking progress in Excel.

02 What you get

Three results you will notice in daily work.

  • The process as it really is

    Documented with the people who perform it, including the exceptions no manual describes.

  • A level of automation per step

    Assisted, partly or fully automated. AI only where understanding is needed, otherwise a rule.

  • Operation with a safety net

    A queue for exceptions, monitoring of errors and processing times, continuous improvement.

03 What it looks like

A document process, before and after.

Schematic example with fictitious data

Rules take over the known part, AI the unstructured part, and exceptions go to a human.

  1. Before

    An invoice arrives by email. Someone opens the PDF, types supplier, number, date and amount into the system, files the document and forwards it for approval. Around four minutes per document, spread across the day.

  2. After · Rule

    Arrival in the designated inbox, the attachment is filed and assigned to the case. Known suppliers are recognised by the sender domain.

  3. After · AI step

    Number, date, amount and line items are read from the PDF, even with a changing layout. Every value gets a confidence indication.

  4. After · Check

    If amount and order reference match the purchase order, the document continues. If something deviates or a value is uncertain, the case stops.

  5. Exception

    Unknown supplier, missing order reference or uncertain recognition: the document lands with a note in a named queue, not in the void.

  6. Approval

    Payment approval stays unchanged with the authorised people. What gets automated is the preparation, not the decision.

The benefit comes from the uniform documents. Everything that deviates should land visibly on the desk instead of in the void. That is exactly what the queue is for.

How do we start?

Ioannis and Tugce Fotiou discussing a process together at the desk
This is how every collaboration starts: with a concrete process on the table, not with a specification document.

When it fits

A case regularly passes through several hands, systems or spreadsheets.

What a first step delivers

An automated flow for one case type, usable in production and with defined exception handling.

What we need from you

Sample documents, the rules that apply and access to the target systems.

We only need these accesses and documents once we start working together. For a first conversation, a short description of your situation is enough.

04 Definition

Process automation with and without AI.

What is process automation?

Process automation is the execution of a business flow by software: recognising triggers, processing data, updating systems and involving the people concerned, following defined rules and with exceptions that go to humans.

Rules and parsers get you far: emails, PDFs and known document formats can be processed with them too, as long as structure and wording stay reasonably consistent. It gets expensive when formats vary strongly, free text has to be interpreted or content has to be classified. That is exactly where AI is the justified addition, not a replacement for clean rules.

Where does AI help in process automation?

AI takes on the steps that require understanding: reading documents, classifying content, extracting data, summarising enquiries. The execution stays rule-based and traceable.

The result is a process that can handle unstructured input without becoming unpredictable: AI at the entrance, rules in the middle, humans at exceptions and approvals.

05 Typical processes

Six flows we automate regularly.

  • 01

    Order intake

    Recognise orders from email, PDF or a portal, extract line items, check them against master data and create them in the ERP, with approval when something deviates.

  • 02

    Invoice checking

    Read incoming invoices, match them against purchase order and delivery, prepare the checking steps, payment approval stays with a human.

  • 03

    Onboarding

    New customers or employees: record data, create accounts, distribute tasks, track progress, without a checklist in Excel.

  • 04

    Creating offers

    Generate an offer from CRM data and templates, have prices and conditions checked, send after approval.

  • 05

    Complaints and tickets

    Classify incoming items, prioritise, request information, assign the case to the right team and inform the customer.

  • 06

    Report generation

    Assemble recurring reports from system data, mark anomalies, present a draft for review.

06 Level of automation

Not everything fully automatic, but everything deliberate.

The right level depends on frequency, risk and variability. We set it for each process step.

  • Level 1

    Assisted

    The system prepares, the human executes. Sensible for rare or highly variable cases.

  • Level 2

    Partly automated

    Routine cases run automatically, exceptions go to a person. The most common and most economical level.

  • Level 3

    Fully automated with control

    The process runs without intervention but is monitored and checked by sampling. Only for clearly defined, low risk flows.

07 How we work

From the flow to operation.

  1. 01

    Record the process

    We document the flow with the people who perform it, including the unofficial steps no manual describes.

  2. 02

    Variants and exceptions

    Which cases occur how often? What happens with missing data, special requests, errors? Exceptions determine the effort, not the normal case.

  3. 03

    Set the level of automation

    For every process step we decide: assisted, partly or fully automated. And where AI is needed or a rule is enough.

  4. 04

    Build

    On an automation platform, in the existing system or as a service of our own, depending on the requirements for data, security and operation.

  5. 05

    Test with real cases

    The flow runs in parallel with the current process on real cases. Only when results and exceptions are right do we switch over.

  6. 06

    Operation and monitoring

    Errors, processing times and interventions are monitored. The process keeps improving. Automation is not a state but an operation.

08 Next

Processes do not end at system boundaries.

Most flows touch several systems. That is why process automation often includes an integration between CRM, ERP and specialist applications, and for steps that require research or preparation, an AI agent.

API integrations See the examples

09 FAQ

Common questions about process automation

Which processes are suitable first?

Frequent, clearly describable flows with noticeable effort, such as order intake, invoice checking or ticket triage. They deliver measurable results quickly and build trust for more complex processes.

Does every automation need AI?

No. Many processes can be automated with rules and interfaces. AI comes into play where inputs are unstructured, meaning emails, documents or free text, or where classifying and summarising is required. We use AI when it makes the difference, not because it is available.

What happens if the automation fails?

Every process has a defined fallback: cases land in a queue or go to a person under control, visibly and not into the void. Monitoring makes outages visible and supports a fast reaction.

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Next step

Which process at your company still runs through an inbox and a spreadsheet?

Name one concrete flow. We show which level of automation makes sense and what it changes in daily work.

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