Patterns, understood as solution templates for recurring design problems, have been proven to support early phases of problem solving in many domains. In Design Science Research in Information Systems (DSR), not only activity-oriented patterns have been proposed, but also suggestions which artefact types are best suited to address certain classes of functional requirements. This study builds on the latter approach—but uses a more fine-grained classification of functional requirements and solution artefact types, and analyzes a much larger set of empirically observed designs. Pattern candidates are not only suggested for identifying suitable (or unsuitable) artefact types for certain classes of functional requirements, but also to identify suitable (or unsuitable) applications for certain artefact types. We classified 191 artefacts from 163 publications in IS publication outlets and coded their functional requirements regarding abstraction level, knowledge type, and situatedness. Using k-means clustering, we derived seven distinct classes of functional requirements and, on that basis, identified 30 pattern candidates. By elaborating existing approaches to pattern support for early phases of DSR, this study enhances conceptual clarity, expands the set of possible patterns, and provides practical orientation—particularly for novice researchers—at the interface between problem framing and artefact design.