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AI for manufacturing and operations: data, processes and decisions in one environment

We connect AI with the documentation and data generated on your production floor, in your warehouse and in your systems, so your team gets an answer instead of going through yet another screen, binder or file. We design and launch the environment it runs in as a general contractor.

Book a case analysis for your plant
AI dla przemysłu i operacji
Problem

You already have the operational data. The problem is getting to it.

Manufacturing, logistics and warehousing generate documentation and data faster than any team can keep in order. Orders, batches, quality reports, technical documentation, equipment logs, supplier correspondence.

The information usually exists. But it is spread across several screens, modules, folders and inboxes, and to put it together you need to know where to look and whom to ask.

In practice this means two things: decisions are made later than they could be, and the knowledge of how to get to the information stays in the heads of a few people.

Who it is for

Organizations where operational data is created faster than it can be handled manually

  • Manufacturing plants

    Technical and process documentation, process parameters, reports, design changes.

  • Logistics and warehouses

    Orders, batches, stock transfers, shipping documents, complaints.

  • Maintenance and service

    Failure history, equipment manuals, logs, documentation from equipment manufacturers.

  • Quality and compliance

    Inspection reports, certificates, product documentation, materials required by customers and auditors.

  • Multi-site organizations

    The same information in several locations, several systems and several versions.

  • Not sure?

    If your data sits in one system and your team knows it well, we will tell you so directly. In that case AI is not the first thing worth buying.

Where AI adds value in the plant and warehouse

  • Working with technical documentation

    Design and process documentation, manuals and requirements as a searchable knowledge base. An employee asks in plain language and gets an answer that points to the source document, instead of going through folders and versions.

  • Questions to production system data

    A layer on top of MES and WMS class systems where questions are asked in plain language: what stage an order is at, where a batch is, what it has gone through, what is running on a given machine. The answer combines data from several places or directs you to the right screen.

  • Support for service and maintenance

    Tickets, logs and equipment documentation analyzed for likely causes of a problem, together with the history of similar events. It shortens the path from symptom to the place where it makes sense to start looking.

  • Classification of quality documents

    Reports, certificates and product documentation organized and assigned according to rules set by your quality department. Completeness checks and flagging of gaps before a document moves on.

  • Analyses, summaries and operational reports

    Compiling material from information scattered across systems, documents and registers, such as a shift summary, a report for a customer, or material for an audit. The employee gets a working draft to review, not a finished document ready to send.

  • Transcription of briefings, audits and training

    Recordings of shift briefings, audits, on-the-job training and supplier meetings turned into text and notes. Processed inside the environment, without sending recordings outside.

Model scenario

What it looks like from the employee’s perspective

A shift manager asks about a specific order: what stage it is at, what it has gone through, whether anything has held it up. Today this means going into several system views, checking the reports and calling the person who happens to remember.

In the AI variant, the question is asked in plain language. The answer combines data from several places and shows where each element comes from, or directs you to the screen with the rest.

The scale depends on how things look today, which is why we measure the starting point in the audit instead of quoting percentages up front.

Integrations and data

A solution is only as good as the data it has access to

We define the scope of integration in the audit, before the architecture is created, not after the environment is launched. We do not build a parallel repository and we do not require you to move your documentation “into AI”.

Production and warehouse systems

MES and WMS class systems, quality systems, production registers.

Business systems

ERP, CRM, finance and accounting systems, HR systems.

Documentation and procedures

File folders, DMS and electronic document workflow systems, technical documentation, manuals, reports.

Equipment and process data

Logs, event registers, readings, batch identification.

Databases and exports

SQL databases, reports, exchange files, scans after text recognition (OCR).

How we integrate

Through APIs and connectors where the system provides them. Through exports, file folders or the database where it does not, with an agreed refresh schedule.

Environment

Technical documentation and process data are often the most valuable things a company has

Recipes, process parameters, design documentation, commercial terms with suppliers. For some plants this means the data cannot go to an external tool, and this is the point where GOTOMA General comes in.

Human oversight

What the solution does, and what remains a human decision

The solution prepares working material. Operational decisions stay with your team.

Releasing a batch, approving a report, changing the production plan, classifying the cause of a failure. These are decisions for which a specific person in your organization is responsible. The solution can prepare and document them. It cannot approve them.

Security

What we say, and what we don’t

What we do not promise

Complete security or the impossibility of a leak. No one who takes this subject seriously makes such claims.

We deliver the solution with current security standards implemented, selected for where and in what form it operates. The documentation you need to demonstrate compliance to a customer, auditor or authority is prepared as part of the project.

What we agree and put in writing before deployment
  • Where your production data and documentation are processed, and what does not leave your environment
  • Who has access and on what terms: production has a different scope, quality a different one, the technical department yet another
  • What is logged and how you can verify it
  • What the rules for using the solution are on your side
  • Who is responsible for what, including when something goes wrong

How we get to the solution

1

Audit

We identify where your team is losing time today, what data is involved and what restrictions apply to it. The result is a recommendation with a rationale.

2

Pilot

One area, one type of case, a limited scope of data. The goal is to check whether the mechanism gives answers that are useful for your team.

3

Deployment and integration

Launching the environment, connecting sources and systems, bringing the solution to operational readiness.

4

Measurement and expansion

We return to the measures agreed before the pilot. If there is an effect, we expand the scope.

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Results: what can be measured

  • Time to reach information

    How long it takes to establish the status of an order, the history of a batch or a requirement from the documentation.

  • Cases without escalation

    How often you need to involve the person who “knows where it is”.

  • Report preparation time

    From the question to finished material or a summary.

  • Manual re-entry of data

    How many times the same information is entered in two places.

  • Time to identify the cause

    From a ticket to the likely cause, where the pilot covers service or maintenance.

  • Where do the numbers come from?

    We do not quote percentages from other people’s materials. We measure the starting point at your site in the audit and return to the same numbers after the pilot. Then the result can be attributed to the change, not to the season.

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Book a case analysis for your plant or warehouse

We will start with where your team is losing the most time today and what data is involved, and then tell you what can be done about it, in what order, and whether it is worth starting with AI at all.

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