The development of magnetic micro- and nano-objects (MOs) holds significant potential in biotechnology and medicine, but there is a need for fast and efficient methods to measure a range of physical parameters. Our study proposes the use of artificial intelligence (AI) to assess the magnetization and hydrodynamic radius of MOs using a microfluidic chip. The methodology involves the use of a microfluidic chip and standard microscopy techniques to track the movement of MOs under the influence of an external magnetic field. The evaluation of cell magnetization using the AI application allows better prediction of average MOs values exceeding 105 MOs/cell than in the case of simulation using finite element analysis. Furthermore, the application of the neural network “U-Net” and the corresponding AI analysis offers the possibility to improve the evaluation of the hydrodynamic radius for MOs larger than 500 nm and for cells magnetized with MOs in the range of 10-100µg/ml culture medium.