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Hoptrans, European transport and logistics operator

When AI moves from pilot to coffee-break debates

Hoptrans, logistics operators with a fleet of 1,500+ trucks across Europe, was facing two challenges at once: sensitive operational data leaking into public AI tools, and business decisions bottlenecked behind IT and BI queries. A private AI platform inside their own cloud solved both - and gave managers a way to talk to their documents and data directly.

Client Hoptrans Sector Logistics & transportation Scale 1,500+ trucks, operations across 6 European countries Solution Moterra Business AI Suite - Internal Knowledge, Data Analytics (Text-to-SQL), General Assistant, Agent Builder
Results
Hours → seconds Knowledge retrieval Information scattered across SharePoint is now surfaced in seconds, with references, in the languages of every region they operate in.
Data on tap Self-service analytics Managers query a complex transport management database in plain English - no SQL, no waiting for IT, no BI backlog.
One governed platform Public AI risk removed Ad-hoc use of consumer AI tools replaced by a secure, private, auditable environment inside Hoptrans’ own AWS cloud.
Building their own From users to creators Hoptrans teams now build their own assistants on the platform - IT Help Desk, Process Manager, Analytics - without waiting for external development.
01

The situation

Hoptrans runs large asset-based transport fleets - 1,500+ trucks, subsidiaries in six European countries, and a workforce spanning different countries, languages and cultures. Two things were slowing them down every day. First, employees were increasingly using public AI tools on their own initiative, putting sensitive operational data at risk. Second, the knowledge and data needed to run the business - SharePoint documents, ERP records, and a complex transport management database - were locked behind manual processes and IT tickets. Managers who wanted a data-driven answer had to wait for someone to write the query.

02

What they tried before

Employees were experimenting with public AI on their own initiative. For a logistics operator handling customer, operational and commercial data across six countries, that was not a workable long-term posture. Existing tools also did not reach into the systems where the answers actually lived - SharePoint content still had to be found manually, and the transport management database was only queryable by a small number of technical users. The result was fragmented knowledge, slow decisions, and rising shadow AI risk.

03

What Moterra deployed

The Moterra Business AI Suite as a private AI platform inside Hoptrans’ own cloud environment, integrated with Microsoft 365, SharePoint and Entra ID so every answer respects existing permissions.

Internal Knowledge AssistantTurns SharePoint into a searchable, multilingual knowledge base with exact document references across the languages they operate in.
Data Analytics AssistantA Text-to-SQL layer connected directly to the transport management database. Managers ask in plain language and get answers, charts and insights back in seconds, without going through IT.
General AssistantA secure, private alternative to public AI tools for everyday knowledge work.
Agent BuilderLets Hoptrans teams create their own assistants on the same secure platform. They are already building an IT Help Desk assistant, a Process Manager assistant and department-specific analytics agents - extending the platform without waiting for external development.
04

The result

The change showed up first in behaviour. After the initial training rounds, AI was open on screens across the office within the same day, and managers started asking questions of the transport management database that used to require an IT ticket and a BI analyst. Knowledge retrieval dropped from hours of searching to seconds. Ad-hoc use of public AI tools was replaced by a single governed platform, with all data staying inside Hoptrans’ own infrastructure.

“After the training, I walked back to the office and saw AI open on more than one screen. There were even loud debates over coffee about how to phrase queries and interpret the answers.”

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