Long Distance Traffic 2022
Deutsche Bahn is looking for solutions for DB Fernverkehr, our long distance department, within special fields of interest.
Develop your prototype and business model with us and open up new digital solutions for our long distance travellers as well as for the operation of DB Fernverkehr.
This 100 day signature program gives startups the chance to customize and live-test their solution to real challenges that DB is facing. What is in for you?
- Access to DB experts and data
- The opportunity to test your solution at a real, capacity-critical station during the DB mindbox program – rent-free!
- Access to a network of selected coaching and mentoring experts
- EUR 25,000, no equity taken.
You will be supported by a dedicated DB mindbox startup manager and will have 24/7 access to our coworking space.
This is a great opportunity to lay the foundation for joint projects and successful long-term collaboration with Deutsche Bahn AG, Europe’s largest mobility and infrastructure provider.
Questions? Check out our FAQs.
01
Automated Testing
When using the WiFi network in our ICE trains, passengers get access to the WiFi portal (so called “ICE Portal”, see iceportal.de) which runs locally on the long distance trains. The challenge is to make sure that it’s running properly on every train (the ICE Portal is running on 1000+ IT systems in the trains!) and indicate if there is a problem on one of them. We’re looking for solutions that cover the topics below:

Establish an automated testing strategy
You are able to translate existing manual testing strategies into an automated testing strategy on each train.

Testing of User Interface and functionalities
With the testing strategy created, you have a solution that can run locally on the train IT and can detect deviations from the target UI and functionalities.

Analysis of errors
Furthermore, your solution is ideally able to analyze errors that might be detected and send out notifications to a central IT for starting the incident process.
02
Analysis of Customer Dialogues
Although we’re always doing our best, a lot of customer feedback or customer dialogues include hate speech. We’re looking for solutions that apply a profanity filter to feedback and detect hate speech context-based.

Identification of inappropriate feedback
Your solution can identify if a comment or feedback is inappropriately worded, ideally in German and English? We’re all ears!

Extracting hate speech from comments
On top of that, you' re able to analyze feedback context-based for hate speech and flag insults and inappropriate words in order to block these parts?

Adaptable to all sorts of written feedback
If your solution is also able to extract hate speech from social media comments, conversation documentation and more written feedback, you're a perfect fit!
03
Energy Consumption Prediction
When a train is between train rides, e.g. in maintenance, preparation for the next journey or just in the depot, it consumes energy. We’re eager to predict this energy consumption as detailed as possible.

Compilation and analysis of recorded data from the past
Various data sets that have an impact on the energy consumption are available. If you can link them and identify the influencing factors regarding the energy consumption, get in touch!

Inclusion of additional, external data
Energy consumption of course also varies depending on external factors, e.g. on very hot or cold days more energy is needed in order to run the AC or heating system. We're very eager to include those external data in the analysis.

Prediction of future energy consumption
It's not only relevant to analyse past data, but to predict the energy consumption in the future, taking into account the various influencing factors. If your solution is able to offer that, apply now!
Timeline
Application Deadline
Last day to apply for the program
Announcement of Candidates
Invitation of selected teams
Selection Day
Pitch your idea on stage to a jury and audience
Start of Program
Start of the 100 day PoC phase to test a prototype in cooperation with DB
End of Program
End of 100 day PoC and presentation of results