Where do AI tools actually fit in a logistics workflow?
Sanimud workshops answer that question step by step — through assignments built around real freight, routing, and warehouse scenarios. Not theory. Applied practice.
Learn about the program
Most transport teams are already surrounded by AI — and mostly ignoring it
Route optimisers, demand forecast modules, and anomaly detection systems are embedded in the tools logistics professionals use every day. The problem is not access — it is knowing what to adjust, what to question, and when to override. These workshops close that gap without requiring a data science background.
Logistics companies using some form of automated routing
Yet fewer than a third of operations staff can interpret the outputs those systems produce, according to sector surveys across Eastern European freight operators.
Typical weeks between a tool rollout and real staff adoption
Structured practice shortens that lag. Each workshop session ends with a concrete task — not slides, not discussion, an action with a defined output.
How AI in logistics has shifted — and where workshops fit in
Each stage below changed what logistics professionals actually need to know. The curriculum is built around where things stand now.
Rule-based automation
Fixed routing rules and warehouse triggers. Predictable but brittle — any deviation needed manual handling.
Predictive demand models
ML-based demand forecasting entered mid-market freight. Required staff to act on probability ranges, not certainties.
LLM-assisted dispatch
Language models began surfacing in carrier communication and exception handling. New errors, new decisions.
Integrated AI layers
Platforms like Trimble, project44, and SAP TM now ship with AI defaults on. Understanding the settings is no longer optional.
Familiar problems, different context
Participants arrive with different job titles but similar frustrations — systems that make decisions nobody can explain, tools that were "implemented" without any training, and pressure to do more with the same staff. These sessions are remote and self-paced enough to fit around shift patterns and regional time zones.
Olesya Marchuk
Fleet dispatcher, Kharkiv region"I wanted to understand why our routing software was giving suggestions I had to override constantly. After the second module it started making sense."
Taras Bondarenko
Warehouse ops lead, Vinnytsia"Remote format was the deciding factor for me. I did the assignments between shifts. The exercises used scenarios close enough to our actual setup to feel relevant."
Built with field references in mind
Workshop content is reviewed against actual implementation cases from Ukrainian and Central European freight operators. Where the field changes, the curriculum follows. Sanimud does not repackage vendor documentation — every module is built around what decisions practitioners actually face.
Curriculum tied to real platforms
Assignments reference Trimble TMS, project44 visibility tools, and SAP TM AI modules — software logistics professionals already encounter at work.
Exercises updated quarterly
Each new cohort gets revised scenarios that reflect recent changes in AI tooling and regional logistics regulation — not exercises built two years ago.
No vendor affiliation
Sanimud does not represent any software provider. Tool comparisons in the curriculum are based on operational characteristics, not partnership agreements.
Route optimisation module — live scenario exercise
Demand forecasting — group assignment session
What stays useful after the workshop ends
Skills from a one-week course fade without reinforcement. These workshops are structured to leave behind habits and frameworks, not just familiarity.
A repeatable process for evaluating AI recommendations
Participants leave with a structured method for questioning automated outputs — applicable to any tool, not only the ones covered in the workshop.
Faster onboarding to new AI tooling
Staff who completed the program onboarded to a new TMS module significantly faster than colleagues who had only vendor training — based on feedback from three companies across Kyiv Oblast.
Shared language across teams
When dispatchers and planners use the same vocabulary for AI errors and edge cases, problem-solving across a shift takes minutes instead of a meeting.
"Six months after the workshop, I still use the decision checklist from module three. It is the first thing I go to when a routing suggestion looks wrong but I cannot immediately explain why."
— Halyna Kovalenko, logistics coordinator, Poltava