Semantic Search Engine for Technology Scouting in a Digital Innovation Platform

In the context of open innovation, technology scouting has become a critical activity for identifying strategic partnerships and emerging technological solutions. Conventional keyword-based search mechanisms used in most digital innovation platforms are inherently limited in their ability to capture the semantic complexity of innovation needs and offerings.This paper presents a semantic search engine integrated within a Digital Innovation Platform to support intelligent technology scouting and recommendation tasks.The proposed approach leverages transformer-based language models to encode natural language descriptions of corporate initiatives and innovation profiles into dense semantic embeddings to enable retrieval based on contextual similarity rather than lexical overlap.A case study in the domain of application modernization demonstrates the effectiveness of the semantic matchmaking engine in generating accurate and strategically valuable recommendations.