Innovation is crucial for companies to stay competitive, provide value to customers, and generate profits. Likewise, research and development (R&D) is critical for companies to sustain productivity growth. Spain has lagged behind other countries in terms of R&D investment, with only 1.4% of its GDP allocated to R&D, well below the European average. To improve this situation, the government offers subsidies to stimulate R&D in Spanish companies. This study examines the profile of subsidized companies in Spain. The aim is to provide insight into the support for companies that apply for innovation subsidies by analyzing the profile of subsidized companies and identifying key variables influencing the success of obtaining innovation grants. The study is based on advanced estimation methods. Natural language processing (NLP), artificial neural network (ANN) techniques, and clustering are used to perform rigorous and robust analysis of the profile of subsidized companies in Spain. The study thus contributes to knowledge in the field of innovation subsidies