Reactive renewal management, driven by calendar alerts, creates costly last-minute scrambles and suboptimal outcomes. This workflow automates the ingestion of historical tenant behavior, current lease economics, market rent comps, and tenant industry health signals to model renewal probability. The output is a prioritized, probabilistic forecast that enables asset managers to allocate retention resources efficiently, negotiate from a position of strength, and model future cash flows with greater accuracy for valuations in systems like Argus or internal DCF models.




