Mobile operators still decide network investments using sparse drive-tests, siloed OSS data, and slow manual analysis. The result is delayed fixes, overspending on CAPEX where it doesn’t lift customer experience, and OPEX tied up in fieldwork. Our Catalyst introduces a DePIN-powered, AI- driven loop that turns customer devices into a privacy-preserving sensing network and converts insights into immediate action. With explicit consent, users contribute quality-of-experience (QoE) and radio metrics via a lightweight app and receive on-chain token rewards. This creates a high-resolution, low-cost data fabric with transparent incentives and verifiable provenance. We then use the crowdsourced data with OSS/KPI, probes, and site parameters to build a network digital twin. ML models perform root-cause analysis, predict congestion weeks ahead, simulate “what-if” scenarios, and recommend zero-touch parameter changes or targeted build-outs ranked by CX gain per dollar. Operators cut drive-test costs, accelerate time-to-detect/repair, and direct CAPEX to the neighborhoods and venues that matter most—boosting NPS and revenue while reducing OPEX. End users see faster, more reliable service precisely where they live, commute, and attend events.