Summary: We present an application of the neural network technology for the assessment of pipes with interacting defects. Finite element simulations are carried out on a pipe containing two aligned and equally shaped defects of 80 $\times$ 32 mm and various defect spacing, providing a database containing the relation between the failure pressures of pipes with multiple and single defects. Neural networks are conceived by using this database, establishing interaction rules and a pipe assessment of interacting defects in the longitudinal and circumferential directions. The neural networks results are compared with those derived from the Det Norske Veritas code (DNV RP-F101).