Embodiments relate to systems and methods for generating interpolated data sets converging to optimized results using iterative overlapping inputs. A database can store sets of operational data, such as financial, medical, climate or other information. For given data, a portion of the input data can be known or predetermined, while for a second portion can be unknown and subject to interpolation. The interpolation engine can generate a conformal interpolation function and interpolated input sets that map to a set of target output data. In aspects, to attempt to drive the set of interpolated input data and/or other results to an optimized and/or steady-state value or values, the interpolation engine can generate a set of shifts or alterations to the set of combined input data as that data exists, to create a set of iterative overlapping input data. That iterative overlapping data can be used to execute successive interpolation runs, and determine whether the interpolation results converge to a set of steady-state and/or optimized results. When convergence is detected, the interpolation results can be assumed to represent optimized, steady-state, and/or best-available values for the conditions of the original combined input data.