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Training for transport

AI training in transport and logistics

We prepare training for forwarders, dispatchers and settlement employees around tasks selected with the team leader. These may include responses to transportation inquiries, forwarding a case to the next shift, or comparing data from documents. Participants work in a tool approved by the company, check their own results and receive comments from the instructor. The price of Syntalith training starts from €1,150 net per day; the program, number of groups and organization of classes require agreement.

net per day of closed training for the team
from €1,150
people in one training group
up to 15
after this time, we measure the effect on the same tasks
30 days
conversation with an engineer and a written plan within 2 business days
€0

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Statistics

How much does AI training cost for a transport company and when does it pay off?

Short answer

AI training for a transport company costs from €1,150 net per day. In our Polish cost example, a PLN 4,900 training fee pays back in 2.6 months: 10 people save an hour a week, and after the licenses they have PLN 1,905 left per month. Dispatchers and forwarders practice working with orders, transport documents and correspondence with carriers. We measure task time before the training and after 30 days.

20,2%

According to the Central Statistical Office (2025), Polish carriers performed 20.2% of road transport work in the European Union, the most out of 27 countries.

Source: Central Statistical Office, Transport – business results in 2025. (2025) ↗

Figures checked: 22 October 2026

Scope step by step

Select tasks for participants

A freight forwarder preparing a response to an inquiry needs different exercises than someone compiling documents for settlement. Therefore, before the training, we select tasks for the roles present in the group. For freight forwarders, the program can be based on extracting conditions from correspondence and preparing questions about missing data. For dispatchers, it would be useful to recreate current agreements and describe open issues for the next shift.

The settlement team can work on comparing read fields with the document and marking discrepancies to be explained. The goal of such an exercise is the ability to check the result. The decision to use the document is made by the employee according to the company's rules. During the session, there is no need to connect the tool with the accounting system or TMS.

Newcomers need time to prepare the first instruction, add allowed material, and improve the response. With people who already use ChatGPT or Claude, we can move on to more complex cases: later changes in correspondence conditions or conflicting data in attachments. The level of participants is determined before proposing the program.

Exercise: What is missing from the response to the inquiry

A sample training material may include a fictional email with the loading location, date, and cargo weight, but without pallet dimensions. The participant prepares a data summary for the freight forwarder and a question to the client with the help of AI. They check whether the response includes the dimensions the sender did not provide, and whether the tool correctly transferred the date.

The instructor discusses a specific part of the work and asks for a correction. Then the participant receives a further message that changes the loading date. They update the summary and point out the message that is the basis for the change. This allows us to see whether the participant can independently return to the source, even when the previous response was correct.

The exercise can be expanded to include correspondence in the language used by the team. Then the control also includes whether the translation preserves the conditions of the inquiry. The valuation of the transport and acceptance of the order remain outside this example. A separate article describes working with AI when passing on changes from dispatchers.

Preparing the company for the session

Before the training, we determine the available accounts and the rules for working with materials. If the company is just choosing a tool, it can order ChatGPT preparation for the team or Claude implementation earlier. Configuration of the environment and purchase of licenses are a separate scope. Exercises can start with fictional data, without connecting the company's email.

The supervisor indicates the tasks and the people who will participate in the session. Together, we determine whether we can use appropriately prepared company materials. Before sharing correspondence, it is necessary to agree on which information can reach the selected tool and who is responsible for preparing the files.

During the collaborative work, time is needed for participants to complete the exercise without simultaneously handling deliveries. Repeating the training for the next shift, shorter meetings, and discussion of work after the session require consideration in the order. We do not assume that one day will cover all roles and all shifts.

How to assess whether the team can work independently

At the end of the agreed program, it is worth allocating time for a new matter that the instructor has not previously solved with the group. The participant should prepare a response, point out the sources of important data, and name the information that is still missing. When assessing the response, we primarily check its consistency with the current agreements in the correspondence.

In further work, the supervisor may check a sample of similar tasks: whether employees return to source messages, correct added details, and know when to pass the matter for clarification. Such observation will help choose the topic of the next exercises.

If after the training it is still necessary to manually copy data between the box and TMS, it is possible to consider separately automating work in transport. Training and integration solve different parts of this task; the scope of system building is determined separately.

Ordering the training

Write which roles you want to train, in which languages the team works, and which tools they already use. It will be helpful to describe the task where it is currently difficult to assess the AI response. Based on this, we will discuss the program, group organization, and pricing. The initial rate is €1,150 net per day, according to the price list. Contact us to determine the scope for your company.

How much does the training cost and when does it pay off

The training starts at €1,150 net per day. We calculate the return on one process, without assumptions about the entire company.

Scenario: 10 people after training (Polish cost example, PLN)
Time saved
43.3 hours/month
Value of time
2,877 PLN
ChatGPT Business licenses
250 USD (972 PLN)
Remaining after licenses
1,905 PLN/month

Return on training for 4,900 PLN

2.6 months

10 people × 1 hour weekly × 4.33 weeks = 43.3 hours. We cautiously assume an hour saved weekly per person and check it by measuring the time of tasks before and after 30 days. An hour of work at 66.45 PLN is the average wage according to GUS from September 2026, including employer costs. Licenses: ChatGPT Business Standard 25 USD per place monthly, exchange rate NBP 3.8889 PLN. If the team already has licenses, the return is faster.

According to a study published in Science (2023), the time for writing tasks with ChatGPT has decreased by 40%. Therefore, the scenario adopts a cautious weekly hour and checks it by measurement.

„I already use AI.”

Your people too. Just no rules.

From our conversations with companies

5 na 10 employees paste sensitive data into private AI accounts: contracts, invoices, customer data.

In ESET survey (2026)

1 na 10 admits this in the survey.

Customer data pasted into a private AI account without an data processing agreement is a violation of the GDPR.

Don't worry, we won't tell anyone :)

What do we see in companies that "already use"

  • Only ChatGPT or Claude accounts, without plugins, skills, integrations and MCP servers with company tools.
  • Company programs are not connected to AI. People still click through systems and Excel, and enter chat data manually.
  • Lack of company standards: everyone writes instructions in their own way, no one shares what works.
  • No rules for personal data, GDPR and company secrets.
  • No limits and no visibility: no one knows who uses AI, how much and for what.

62% Polish employees use AI at work · 27% companies have written rules for working with AI.

Source: ESET and DAGMA, Cyberportrait of Polish business 2026 (March 2026, 1,026 people) ↗

ChatGPT or Claude space review

Accounts, permissions, rules for working with data and 5 tasks set for the team. 1 day.

€450 net

ChatGPT rollout →Claude rollout →

Training on your team's tasks, from €1,150 net per day.See range and price →

Scope and price

From €1,150 net per day

The program is tailored to the participants' roles, experience and shift work.

Claude Partner Network member

Denotes membership in Anthropic's partner program for Claude. Not an endorsement of Syntalith's services by Anthropic.

1:1 course participants

People we've trained one-on-one.

Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗
  • „A large stream of documents passes my desk every week. I now review, draft and prepare them with Claude in a fraction of the time, and research that used to eat an afternoon takes minutes. It is wired into the services I already work in, so the documents reach me instead of me hunting for them.”

    Hlib Utkin, public administrationHlib UtkinPublic administration
  • „I came in using coding agents ad hoc and left orchestrating them: loops, an agent kanban, a full development cycle that ships. What stayed with me is running context and cost on purpose, and building my own harnesses instead of waiting for a tool to ship one. It changed how I work day to day.”

    Ivan Chepurin, Senior Software Engineer at ImmutableIvan ChepurinSenior Software Engineer, Immutable
  • „I run a design studio, not an engineering team, and I still left with something working. We built an agent loop that pulls in leads and keeps an eye on the competition, and I put my own site together with Claude. It was hands-on, on my real work, not a talk about AI.”

    Oleksandr Usyk, co-founder and art director at jakotako.designOleksandr UsykCo-founder & Art director, jakotako.design

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
You buy accounts directly from OpenAI or Anthropic and receive an invoice from them. We do not add anything to the license.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.