Endovascular techniques have revolutionized the treatment of intracranial aneurysms (IAs), first with the advent of coiling and later with flow diverters. However, despite two decades of clinical practice, critical questions regarding procedural techniques, device selection, and optimal sizing persist, as current guidelines primarily address clinical indications rather than procedural optimization [1–2]. In this context, in silico modeling has emerged as a fundamental tool for designing optimal interventional strategies. We present a comprehensive digital framework for the virtual treatment of IAs, covering the two most prevalent minimally invasive techniques. Developed over the last decade, this measurement-supported workflow couples (a) the mechanical modeling of device deployment with (b) the prediction of hemodynamic outcomes via computational fluid dynamics. Flow diverters are modelled as a spring network reflecting the woven design structure, using a finite difference method and ray-casting for collision mechanics with the vessel wall. The model has been validated on an in vitro 3D-printed vascular model [3], achieving a comparative accuracy higher than the 0.22 mm voxel size resolution of a typical DSA image. Coil deployments are simulated using a mechanics-augmented path-planning algorithm that computes hundreds of deployment scenarios for a single patient geometry and produces the expected configuration of the first framing coil and the subsequent filling coils. Post-treatment hemodynamics are resolved using a validated in-house lattice-Boltzmann solver based on the Palabos library [4]. The flow-reducing effects of the devices are incorporated as a thin porous layer (for flow diverters) or a porous medium (for coils), calibrated using in-house hydrodynamic resistance data. We demonstrate that this semi-automatic framework is capable of handling large-scale studies (>10³ cases) through advanced database scripting on HPC infrastructures. The stability and scalability of this workflow confirm that these simulation tools are now fully operational and ready for deployment in upcoming in silico clinical trials.