The Arbitration Board for the Travel and Transport Sector (SRUV) processes tens of thousands of arbitration cases every year.
By deploying AI-supported Legal Bots built on e! by Lexemo, the SRUV transformed a slow, manual processing workflow into a transparent, rule-based system and reduced processing time from 5–7 minutes to about one minute per case.
Client Challenge (Starting Point)
Since its founding in 2009, the SRUV has helped travellers and transport companies resolve disputes efficiently and fairly and in an ever-increasing number of cases with over 45,000 cases in 2025.
However, as case volumes grew, a central bottleneck became tighter: the manual classification process.
Each case had to be read and assigned individually. Employees compared consumer submissions with company responses, corrected typos, checked data consistency, and when necessary, even verified external information such as weather conditions on the day of travel.
The process was reliable but time-consuming, difficult to scale, and dependent on subjective assessments.
The SRUV therefore sought a faster, more consistent, and more transparent way to categorise and prepare cases without losing the human sense for empathy and quality.
The Solution
To achieve this goal, the SRUV decided to rethink case analysis and sorting from the ground up.
Instead of relying on manual review, the team developed AI-supported Legal Bots using the no-code automation platform e!.
The Legal Bot reads both the traveller’s complaint and the company’s response, automatically identifies what is undisputed, what is disputed, and which case category the matter must be assigned to.
It then assigns every case to the correct category with a transparent reasoning chain that clearly shows how and why the decision was made.
Example:
If a traveller misses a connecting flight, the bot recognises whether an alternative means of transport was offered, checks possible weather-related causes (e.g., strong winds that may exclude liability), and documents the decision logic within seconds.
Based on this approach, the SRUV has now developed more than 400 automations that cover various sub-processes within the entire arbitration workflow. The goal was and remains to automate and standardise as much as possible while keeping humans involved in the crucial, evaluation-relevant steps (“Human in the Loop”).
After initial support from Lexemo’s expert team in building the bots, SRUV’s internal team is now able to create, manage and continuously further develop the automations independently.
“With Lexemo, we fundamentally transformed our case processing. What used to take several minutes now happens in about one. The Legal Bots not only save time, but also make our work more transparent and consistent and the best part: our team can now create automations on its own and continuously improve them.”
– Svenja Meier
Implementation Process
The transition from manual to AI-supported case handling was not a one-off project for the SRUV, but a gradual transformation process with full involvement of the team.
Mapping the decision logic: Together with Lexemo, the SRUV translated its expertise into structured decision and rule chains that make every AI step traceable and verifiable.
Empowering specialist departments: Subject matter experts for each process step became digital transformation contributors. Through e!’s dialogue-based interface, SRUV staff could design, test and refine their bots themselves without advanced programming skills.
Seamless integration: The Legal Bot works in the background, pre-sorts new cases, creates AI-supported notes and inserts structured summaries directly into the workflow. When arbitrators open a case, everything is already prepared.
Continuous improvement: After the initial rollout, team members took responsibility for extending and optimising the bot as new case types or patterns emerged.
Cultural shift: Through the project, AI-supported automation became part of everyday work for everyone on the team.
Measurable Outcomes & Results
The results speak for themselves: the optimisation of the classification process significantly strengthened productivity and transparency.
Processing time reduced from 5–7 to 1 minute. Employees gained time for complex and sensitive cases instead of having to work through recurring routine tasks.
Over 45,000 cases per year are now automatically analysed, linked and documented.
Greater consistency: Every case is assessed according to the same rules, eliminating subjective differences in classification.
Immediate traceability: Every decision step is documented and auditable, a key factor for trust and regulatory certainty.
Self-enabled teams: SRUV employees can develop, adapt, and improve bots themselves. Innovation has become a continuous process.
Scalable impact: The automation model can be easily applied to new case categories and use cases, creating a solid foundation for long-term digital transformation.
