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OMoS ‒ online migration advice without language barriers - Civic Innovation Platform

OMoS ‒ online migration advice without language barriers

Advice in the area of migration is extremely resource-intensive. Tür an Tür – Digitalfabrik gGmbHTU Dortmund University and the City of Munich want to use existing databases via the NLP framework Haystack to answer basic questions and to enable real-time advice provision with simultaneous AI-based machine translations in order to help refugees and migrants make informed decisions for themselves and successfully build a (new) life in Germany. At the same time, the day-to-day work of official agencies and advisory services should be made easier.

What makes you a strong team?

We bring together expertise from municipal administration, civil society and academia. Our core team consists of employees from a non-profit tech spin-off of the TU Munich, which will develop a proof of concept together with the City of Munich and TU Dortmund. We have been working together with our network partners in the area of migration and digitalisation since 2015. As a rule, we can always implement technical developments in-house, making us incredibly fast.

Explain your idea in three sentences.

Migration and referral advice for immigrants is resource-intensive. As a first step, we want to make existing information and services from local authorities more efficient and accessible in their native language for people seeking advice. In a second step, we intend to provide a technical solution for online migration advice that provides real-time translations and thus eliminates the language barrier.

What makes your idea special?

Firstly, our diverse team and, secondly, the enormous potential behind the idea. Freelancers and the non-profit sector in particular can benefit from this type of AI-based digitalisation and thus make their own work more efficient. Better referral counselling reduces the actual number of migration counselling sessions taking place, leading to shorter waiting times for a consultation appointment and thus to fewer ‘no-shows’ and wasted resources.

What’s next?

We were able to gain fresh experience from a municipal and multilingual chatbot project in 2022 that was not cost-effective. Based on these experiences, we will build the next solution. Together with the City of Munich and TU Dortmund, we will discuss the detailed requirements and then develop a prototype and map the complete user journey of the idea.

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