Bridge Usage Patterns for @ethena_labs: June 2025 📆 We analyzed all bridging processed through LI.​FI for Ethena last month. The goal was simple: understand how volume was distributed across bridges. Key findings: > @glacislabs: 77.94% > @RelayProtocol: 16.26% > Others: 5.7% spread across 8 other bridges Why did Glacis outperform others? No slippage and same fees across all routes, a result of mint-and-burn model. It gives it an edge when solvers either lack inventory or add markups for the same execution. But none of this was pre-set. Bridge selection is dynamic: based on cost, availability, and asset coverage at execution time. That’s what LI.​FI enables behind the scenes. Whatever the path, LI.​FI gets users where they need to go. All interop out of the box — powered by LI.​FI 🫡