FAIRplus seeks to improve the level of discovery, accessibility, interoperability and reusability of IMI data through practical, pragmatic guidelines and processes. We are pursuing an exemplar-driven approach in an attempt to change the data management culture of IMI projects and support IMI data managers to produce more FAIR data. In this report, we describe the FAIRplus approach to the creation of technical FAIRification solutions. This approach has been derived from and validated by FAIRplus project personnel working collaboratively with 12 different IMI projects. We explore what we have found to be most effective and the reasons why some avenues have been less fruitful. This analysis is somewhat limited by a lack of objective mechanisms for assessing the impact of FAIRplus technical solutions, and we are working to incorporate ways to better evaluate the success of our technical solutions in future. Whilst the development of fully automated technical solutions is not a goal of FAIRplus, we seek to generate reusable collections of cookbook recipes, and to create automated components where possible. This enables FAIR workflows to be assembled from reusable building blocks, and we have started to generate several examples of this approach. The process for creating FAIRplus technical solutions is highly collaborative, bringing domain experts and FAIR experts together, but is manually intensive. We expect future improvements to yield benefits towards a more “self-serve” approach to FAIR technical solutions.