The real bottleneck. Markets don’t lack apps they lack an accessible source of truth. Prices live behind terminals, wrapped in opaque bundles, and delivered late. Each venue sees only its own book; aggregators stitch fragments together while value leaks to intermediaries. The result: decisions made with a partial radar, execution that degrades when volatility rises, and swelling costs for… less useful signal.
Pyth’s simple idea. Instead of buying black boxes, plug directly into the source. Phase Two introduces an institutional “pure data” subscription: price feeds published by exchanges, market makers, and trading firms that your systems can pull at your execution engine’s cadence. Think universal power outlet: one integration and your risk models, clearing and settlement, trading screens, and reporting tools are fed clean, continuous, near–real-time data. Payments are flexible: USD, stablecoins, or $PYTH.
Why this is different. First, access is direct no unnecessary middle layers, no expensive “re-packaging.” Second, the subscription powers a clear incentive loop: revenues flow back to the Pyth DAO, which can fund token buybacks, reward data publishers and users, and support stakers and holders. In other words, you’re not paying just to “watch”; you’re investing in infrastructure that improves as it’s used. Finally, the approach is multi-asset and multi-chain crypto, equities, FX, commodities, rates spanning 100+ networks while keeping the integration experience unified.
Tangible benefits, right away.
Less slippage, healthier spreads: you cut down on stale quotes at send time.
Cleaner execution: timely updates accelerate decisions; fills match intent not hope.
Controlled costs: you pay for useful data, not the packaging.
Faster product roadmap: one connection to expand asset coverage, backtest on clean histories, and launch new markets without renegotiating a maze of licenses.
What this changes for a builder. You replace multi-provider duct tape with a coherent API. Your perps, aggregators, or on-chain MM desks gain speed and stability. Your quant and risk teams wire the same price truth into models, P&L, and reporting. Support stops explaining latency-induced discrepancies; your product’s perceived reliability climbs. And because the DAO recycles revenue into the ecosystem, every new subscriber strengthens the quality of the feeds you already depend on.
Beyond the “micro” of prices. Phase Two also opens to macro data (employment, inflation, growth, current accounts…). These indicators, finally on-chain, become native signals for your smart contracts: indexed instruments, vaults that reweight on macro surprises, CPI/NFP hedging, fully-coded “trade-the-print” strategies. You move from DeFi centered on crypto spot to programmable finance wired into economic reality.
A word on speed. When every millisecond counts, the ultra-fast option (think Pyth Lazer) pushes sub-second updates and brings your UX up to CeFi standards without giving up on-chain benefits. For perps, synthetic books, or automated MM, that’s the difference between paying a latency tax and enjoying a fair edge.
The vision, now. Phase Two isn’t “monetization” as usual; it’s the economic model needed to scale a global price layer. More subscribers ⇒ more revenue ⇒ a stronger DAO ⇒ better incentives for publishers and users ⇒ richer data ⇒ more products ⇒ adoption. Then comes the expansion to thousands of new symbols (more venues, permissioned and permissionless DeFi, OTC). Like a streaming platform except contributors share the value.
In short. Pay for the data that matters, earn in the loop that creates its value, and build on a common price truththat’s what Pythnetwork’s Phase Two unlocks. If you build, trade, arbitrate, or manage risk, the best time to wire your systems in is now.
Pay the truth, earn the loop.
#PythRoadmap $PYTH @Pyth Network
