How SRUV Reduced Case Processing Time from
7 Minutes to 1
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, SRUV has helped travelers and transport companies resolve disputes efficiently and fairly—in an ever-growing number of cases (2025: over 45,000).
However, as case volume grew, a central bottleneck became tighter: the manual classification process.
Each case had to be read and assigned individually. Staff compared consumer inputs with company responses, corrected typos, checked data consistency, and when necessary verified external information—such as weather conditions on the travel day.
The process was reliable but time-consuming, difficult to scale, and dependent on subjective assessments.
Pain Point
5–7 minutes per case
Scalability Issues
Manual process couldn't keep up with volume
Inconsistency Risk
Subjective assessments varied between staff
AI-Powered Legal Bots
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.
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-powered Legal Bots using the no-code automation platform e! by Lexemo.
The Legal Bot reads both the traveler'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 each case to the appropriate category, with a transparent reasoning chain that clearly shows how and why the decision was made.
Example: If a traveler misses a connecting flight, the bot identifies whether alternative transportation was offered, checks possible weather-related causes (e.g., strong winds that might exclude liability), and documents the decision logic within seconds.
On this foundation, SRUV has now developed over 400 automations covering different 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.
Step 1: Input Analysis
Read complaint + company response
Step 2: Classification
Identify disputed vs. undisputed elements
Step 3: Categorization
Assign to appropriate case category
Step 4: Documentation
Generate transparent reasoning chain
With Lexemo, we fundamentally changed 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 best of all: our team can now create and continuously improve automations themselves.
Svenja Meier
Schlichtungsstelle für den Reise- und Verkehrssektor (SRUV)
A Step-by-Step Transformation
The transition from manual to AI-supported case processing at SRUV was not a one-time project, but a gradual transformation process, with full team involvement.
Mapping Decision Logic
Together with Lexemo, SRUV translated their expertise into structured decision and rule chains, making 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-sorting new cases, creating AI-supported notes, and adding structured summaries directly into the workflow. When arbitrators open a case, everything is already prepared.
Continuous Improvement
After initial rollout, team members took responsibility for expanding and optimizing the bot as new case types or patterns emerged.
Cultural Transformation
AI-supported automation became part of daily work for everyone on the team.
Measurable Outcomes
The results speak for themselves: Process optimization of the classification process 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.
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