AI integration

AI that works on your own technical data

The hakapesy™ AI module works from your company’s work orders, reports and machine history. It takes admin off technicians and the office, while decisions stay with people.

In production

From dictation to a work order draft

On site, the technician describes what they found and did. The system transcribes the recording and fills in the work order fields: diagnosis, work done, materials used. The technician reviews, corrects and approves.

  • No typing, works with gloves on
  • Structured output, split into fields
  • Nothing reaches the work order without approval
  • Trade vocabulary in Hungarian
Closed work order with diagnosis, work done and total

AI modules

Where AI development is heading

AI modules are built on the technical data asset. The more work goes into the system, the more accurate the results.

Available

Dictation to work order

The technician describes the job. AI fills in diagnosis, work done and materials.

In development

Report interpretation

Fault category, urgency and likely cause suggested from the reporter’s text and photo.

Planned

Maintenance forecasting

Suggested maintenance dates based on risk estimated from history.

Builds on your data

Technical knowledge search

Ask your own work orders: what did we replace last time on this model, and what fixed it?

Builds on your data

Machine history analysis

Recurring faults, frequently replaced parts and deteriorating machines highlighted automatically.

Builds on your data

Quote suggestions

Replacement or upgrade proposals when repair costs stay high.

Data-driven features already work technically. Their results come from the work orders and history collected in the system, so their accuracy grows with the length of our collaboration: the longer you record your jobs, the more they give back.

How it works

Data, model, human approval

  1. Your data

    Work orders, reports, machine history and photos within your company.

  2. AI processing

    Transcription, classification, search and summarisation.

  3. Suggestion

    A draft or suggestion appears for the user.

  4. Approval

    The technician or office accepts, corrects or rejects it.

Principles

Responsible use of AI

People decide

AI suggests, the user approves. There are no automatic changes.

Stays within the company

One company’s data never ends up in another company’s AI results.

No training on your data

We do not train our own or third-party models on customer data.

Switchable

AI features can be turned on or off per company and per role.

Transparent

Data processors are named in the privacy notice.

EU data storage

Stored data stays in the EU.

30-day trial with your own data

We import machines and customers from your existing spreadsheets and print the first QR labels.