Klarvo.

AI training for logistics

Operations teams see trip, delivery and warehouse data every day but can't take it beyond Excel. Route and capacity decisions rest on experience.

▶ The solution

AI literacy for executives; Python, data analysis, statistical thinking, machine learning and deep learning for technical teams. Hands-on, and tailored to your team's level and your own data.

▶ Use case

Teams learn to analyze delivery times, delay causes and warehouse efficiency in Python, working on their own operational data throughout.

▶ Data you need

Trip and delivery records, warehouse movements and delay logs.

The industry's data landscape

In logistics, data comes from transport management systems, warehouse management systems, vehicle telematics and customer order records. There's plenty of it, but it's usually kept to run operations, not organized to support decisions.

Corporate training gives your team the knowledge to do data and AI work without depending on outsiders. There are two audiences: executives, who need to tell what is possible from what is hype, and technical teams, who will do the work themselves.

The math behind it

Precision = TP / (TP + FP) · Recall = TP / (TP + FN)

  • TP: cases the model correctly flags
  • FP: cases it flags by mistake
  • FN: cases it misses
A model that is "95% accurate" tells you little on its own [1]. The first thing teams learn in my trainings is to ask which error costs the business more, and to pick the metric accordingly.

How I work

  1. Before

    Level and goal.

    The participants' current level, and what they should be able to do afterwards, is made clear. Executives and technical teams get separate goals.

  2. Preparation

    Content and examples.

    The programme is shaped around the team's level. Examples and exercises are chosen close to the company's real problems.

  3. Training

    Hands-on sessions.

    More practice than lecture: participants write code, work with data and interpret results. Questions are answered through the company's own work.

  4. After

    Back to work.

    A concrete task or project proposal the team can apply right after. Where the learning will be used is clear from the start.

Full service details: Corporate trainings →

▶ Questions and answers

AI training for logistics — what data do you need?

Trip and delivery records, warehouse movements and delay logs.

When is this the wrong choice?

The training is just a line in the annual plan. A training nobody will apply afterwards produces nothing but certificates. You actually need a project. If the work needs to get done soon, doing the project may be faster than training the team.

How does this work start?

With a short intro call. I listen to what you need and tell you plainly whether your data is enough for the job and what the first step should be. I reply to every message within 24 hours.

▶ Concepts

Linked to Wikipedia and Wikidata.

▶ Sources

  1. [1]Wikipedia, Precision and recall, 2026-10. en.wikipedia.org/wiki/Precision_and_recall

▶ Intro call

Let's talk about your situation.

In a 30-minute call I listen to what you need and tell you plainly how I can help.

Book an intro call

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