The idea of the project was brought up by Toyota, one of our key customers, at the beginning of the coronavirus pandemic in March 2020. Many confined people were alone and needed help to get through these difficult times.
Together with one of the German regions, Toyota was looking for a solution that would match those who need help and those who can provide it . The elderly needed a hand with the grocery shopping and small household chores, and at the same time, they had to stay home as much as possible to minimize the risk of getting COVID. It was also important to help people stay in contact with others, as many felt lonely during the quarantine.
That's how we came up with the idea of Lokalhelfer, a service that matches people asking for help and volunteers.
This project involves German public institutions, meaning the data privacy question is a number one priority. We needed not only to have full control but full ownership of data. Moreover, this platform contains personal information like people's addresses, photos, and needs. This sensitive data should be treated safely.
We have already made a matching functionality using Contentful for another project, but it was impossible to use proprietary software when working with the public sector. We needed an open-source and self-hosted solution, and since we already did some projects using Strapi, the choice was easy.
Other factors are the general transparency of the company and roadmap and huge community support. We see Strapi as a solid blank foundation to start with; it's always a plus for a developer.
We migrated everything from Contentful to Strapi and rebuilt the matching functionality on a new technological platform. We also used Node.js and React to build this project. The website is responsive and works for mobile and desktop devices, and to make it more accessible, we developed a PWA (progressive web app) as well.
We're currently working on a backend side to let cities access the platform and verify local volunteers. We plan to extend this project to other German regions so that each city can independently manage local volunteers. In the future, we'd like to go international and expand to other African and European countries.
The project is scalable because all the processes are automated thanks to Strapi's data-centric approach. We developed a simple data structure with several collection types (people requesting help and providing it) and an authorization process. Doing it with a traditional CMS or a custom-built solution would take a lot of time.
It's also important that Strapi provides different roles and permissions, as many city administration employees will need to access the admin panel to manage volunteers.
In the context of COVID-19 pandemic, we needed to ship this project very quickly as it's created to help people who experience some difficulties and loneliness during the quarantine. With Strapi, we could develop the whole project in only 6 weeks. It was surprising for public institutions to see that something can be shipped so quickly. We can also provide them with full ownership and control of data thanks to Strapi.
Strapi gives us a data-centric approach so that we can automize 100% of processes on the platform. It's a great tool to develop centralized data hubs which serve content to different channels.