Model-based electron accelerator control is the maintenance of optimal parameters of an electron beam such as its orbit, size, and shape, as well as machine parameters such as tunes. It works well when the model reflects reality. SLAC pioneered this technique in SPEAR about thirty decades ago. Similar techniques are now employed in particle accelerator and synchrotron laboratories around the world. There is still an inherently complex problem related to the employment of such techniques to manage the operation and analysis of accelerators and storage rings. The problem arises from the use by those techniques of complex numerical algorithms commonly known as nonlinear solvers that are difficult to control and operate. Lessons learned at SLAC have led to the development of a new, simple-to-use, and iterative nonlinear solver that holds much promise not only in advancing the derivation of errors in accelerators and storage rings at SLAC, but also in its ability to tackle a range of complex engineering problems. A CRADA project was recently completed to build on this experience at SLAC, and to collaborate with an outside company GO AI Services to further develop and validate this nonlinear solver for robust SLAC accelerator. In this report, we present the project report submitted to DOE and SLAC. Show Partial Abstract