The future of systematic reviews is challenging. The volume of publications is growing exponentially and the complexity of scientific research increases. Expensive expert knowledge is needed for the selection, assessment and synthesis of this research.

AI-solutions can revolutionize literature review and knowledge synthesis. The challenge for the AI remains not to miss out on relevant papers, to give reasons for inclusion/exclusion (like humans), and reduce the workload at the same time.

Our mission is to revolutionize the landscape of literature reviews with explainable AI solutions.

We envisage high-quality, transparent and trusted AI-solutions that will change the current standards for systematic literature review and guideline development. Selectical sees itself at the forefront of those developments, thus contributing to a more efficient and comprehensive knowledge synthesis.

For over two decades, Judith has navigated the landscape of literature reviews. She has conducted numerous systematic literature reviews in various settings, e.g. industry or guideline development. She’s seen firsthand the promise that AI holds for revolutionizing this field. Yet, as AI-tools entered the market the main challenge, building a transparent and trusted tool, was not solved in a satisfactory way.

Therefore, Judith teamed up with Erwin to develop a better tool. A tool that harnesses the power of AI without sacrificing transparency and reliability. At Selectical we thrive to bridge the gap between AI’s potential and practical application in literature reviews. We focus on delivering AI solutions that don’t just save time but also ensure transparency. By providing clear, auditable reasons for every decision, we aim to build tools that users can trust and rely on.