Evolve is a cross-platform social cohesion analyser that applies the Chronoflux hydrodynamic framework — originally developed in theoretical physics by Roy D. Herbert as a unification model treating time as a conserved five-dimensional flow (governed by the continuity equation ∇_μ(ρ_t u^μ) = 0) — to sociophysics and computational social science. The tool maps key Chronoflux constructs (Continuum, Flow, Shear, Resistance, Vortex) onto observable proxies of collective human will and consciousness, such as narrative density, discourse clustering, sentiment trajectories, and behavioural patterns. Users pose scenario questions (e.g., probability of civil unrest, electoral outcomes, or governance interventions) in two modes: Percent Chance or full Social Cohesion Score (SCS). The local, offline pipeline computes a weighted overall SCS (with categorical interpretation), a calibrated regressive/progressive continuum split (typically in the realistic 50–60% range), and five actionable governance recommendations grounded in the detected dynamics. Optional Grok construal assists with field population and narrative URL processing without overwriting user inputs, while region-specific historical outcome registry calibration enhances relevance. This open-source implementation (available at https://github.com/rgsneddon/evolve and https://rgsneddon.github.io/evolve/) emphasises transparency, privacy, and actionability for researchers, policymakers, and communities exploring pathways toward higher progressive cohesion states. It distinguishes the sociophysical application from the original physics theory while highlighting productive parallels in continuity and emergence. The work includes detailed theoretical mapping, mathematical formulation, software architecture, illustrative case studies (e.g., by-elections, unrest risk, local governance optimisation), and discussion of strengths, limitations, and future directions in decentralised community governance.