In the summer of 2021, Tanika contacted Panenco to talk us through her research and the option of building a digital product around it. After an intensive product definition phase with deep dive workshops on the workings of her model, we started working towards a minimum lovable product (MLP).
AlterEdu directly stems from the Academic Research Tanika has been working on for the past years and aims at addressing the skills gap that companies are facing. AlterEdu maps the puzzle pieces that together form competences. By laying this puzzle, you can measure which competences are are currently present and which could be easily developed towards the future at the level of the individual, thereby reducing the risk of skilling efforts.
In our journey towards a marketable product, we kicked off with a design phase in which we worked out different concepts for the application. In parallel, our back-end developers started setting up the database model and architecture for the backbone of the web application. After all lights were set on green by Tanika and Michel (the co-founder of AlterEdu), we gathered a dedicated product team and started iterating towards the MLP.
In parallel, we collaborated with ML2Grow to identify in which areas machine learning could be of assistance in the model of scoring and mapping candidate's responses on the cognitive test. This parallel track allowed us to already incorporate the first phase of machine learning into the application.
While currently being tested at large corporations as well as within the public services sector, we are looking forward to the next development phase of AlterEdu in which we will further focus on iterating towards a product-market fit based on user feedback. Check out https://alteredu.be/ for more info on AlterEdu.
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