Comparing and merging complex kinetic models developed by different teams is a delicate operation, prone to errors, not least because of the multiplicity of usages for naming and describing chemical species. However, the modelling of combustion systems calls for increasingly complex kinetics, especially for mixtures, which can often be built from different mechanisms developed for single components. The TIRAMISU automatic fusion code, written in Python, has been developed for an efficient automatic merging of large mechanisms. This new code proceeds in several stages. A preliminary reading and cleaning of each mechanism is followed by an automatic translation step based on the comparison of the Gibbs energy of the isomers to be matched, as well as the reactions involving them. Two analyses of possible matches between isomers from the two mechanisms are proposed, based on thermodynamic properties. When the matches are not sufficient for a confident translation, the system uses the similarities of the reactions involving the species. Finally, a model merging step is proposed to the user, which can be total or limited to the sub-mechanism of a species taken from one mechanism to be added to another. These two objectives are illustrated by the construction of a TRF model (toluene, n-heptane, isooctane blend surrogate of gasoline) by total fusion of two models from the literature. The possibility of choosing thermochemical and kinetics data from either of the parent models is illustrated, as is the impact on simulations of auto-ignition times. This TRF model is then extended with TIRAMISU to a TRF-iB by including the sub-mechanism of a bio-fuel, isobutanol, from other models in the literature. The impact of the user's choice of the size of the sub-mechanism on simulation fidelity and the size of the resulting model is discussed, illustrating the power and versatility of this new software.