Many projects like to make big promises, but they often get exposed in the end. @OstiumLabs’s recent approach has a bit of an engineer’s touch—no slogans, first streamline the underlying data flow, then consider scaling up.

They have redesigned the traditional market data sources with a pipeline approach, separating and syncing the three core data types: price, depth, and trading volume. With this change, the latency in perpetual contract pricing is noticeably reduced, and it won't experience the awkward “on-chain lag” during high-frequency volatility. Meanwhile, they’ve applied an error damping algorithm to the price synchronization, which can automatically filter out abnormal jumps in large markets, improving the stable range of the contracts.

At the trading execution layer, #Ostium has launched a lightweight matching scheduler specifically optimized for small orders and high-frequency order placing and canceling. The common queue blocking issues on traditional on-chain contracts are significantly eased here, providing a smoother trading experience for new users.

Another noteworthy part is their monitoring plugin, used to analyze the risk pool’s exposure distribution in real time, including metrics like volatility peaks, order density, and position shifts. For on-chain risk management teams, this data can greatly improve judgment efficiency, and it’s openly available across the entire chain.

@OstiumLabs is not about superficial flashy features; it’s about refining the fundamental operations, using a solid foundation to make the derivatives environment cleaner and more controllable.
@OstiumLabs @Bantr_fun @0xMantleCN #Ostium #Bantr