When we think about the future chemistry laboratory, we often envision a fully automated system: scientists enter a molecule they want to create, advanced software suggests a synthetic route, which is then executed by a robot. This is followed by a purification step to prepare the sample for analysis by a range of analytical instruments. Finally, an automated process determines the structure of the molecule based on the spectral data collected. Achieving this vision requires advancements in multiple areas, from route predictions to synthesis and purification automation. A critical component of this pipeline is the automated interpretation of spectroscopic data for molecular structure elucidation. In this work, we describe our contribution to solve automatic structure elucidation by proposing a flexible model that can translate spectroscopic data directly into molecules, while addressing several limitations of current Computer-Assisted Structure Elucidation (CASE) programs. CASE programs use Nuclear Magnetic Resonance (NMR) and/or Infrared (IR) data to elucidate molecular structures. H and C NMR are the most widely used spectroscopic techniques for characterizing molecules and provide detailed insights into hydrogen and carbon atoms. Furthermore, 2D techniques such as COSY (Correlation Spectroscopy) and HSQC (Heteronuclear Single Quantum Coherence) provide connectivity information. Mass spectrometry (MS) offers molecular weight and formula information, crucial for confirming molecular structures. IR spectroscopy is cost-effective and non-destructive allowing for quick identification of functional groups. The fingerprint region (400-1500 cm -1 ) of IR spectra contains complex, molecule-specific absorption patterns that are challenging to interpret using traditional methods. This region holds detailed molecular information often underutilized in traditional analysis due to its complexity. However, modern machine learning algorithms show promise in extracting and interpreting this rich structural information from the fingerprint region. Together, NMR, IR, and MS provide complementary information essential for structure elucidation.