Financial markets are becoming software-defined.

Prices now feed exchange engines, collateral systems, risk models, tokenized products, AI workflows, and trading venues that operate around the clock.

That shift is changing what institutions expect from market-data infrastructure: direct access, broader coverage, lower latency, transparent sourcing, and distribution that works across traditional and internet-native markets.

Pyth is building for that environment. Its model brings market participants closer to the applications that consume their data, creating a shared distribution layer for real-time pricing across asset classes.

Pyth’s current publisher page says more than 138 leading institutions are participating in this new market-data network. In its July 2026 report, Pyth Pro reported a catalog of 3,501 feeds, including 1,901 equity feeds, with 75 net-new equity feeds added during the month.

The numbers matter because coverage is what turns a data connection into a market-data layer. The more assets and markets institutions can reach through one integration, the more workflows that integration can support.

The institutions behind the data

Pyth’s publisher network includes market infrastructure firms, exchanges, trading firms, fintech platforms, data specialists, and market-data and infrastructure providers.

The public publisher page highlights Cboe Global Markets, Coinbase, Revolut, and Virtu Financial among the institutions already publishing data to Pyth.

The wider network includes a growing set of names with distinct roles in financial markets. Kalshi brings regulated event markets, while Revolut contributes digital banking and digital-asset market data. Fenics brings dealer-to-dealer fixed-income data. Coinbase is building continuously priced thematic indices and exchange infrastructure, Jane Street contributes market-maker data, and SGX FX brings institutional currency pricing.

These are different institutions solving different data problems.

Together, they show how Pyth is expanding from crypto-native price feeds into a broader market-data network for financial applications, exchanges, prediction markets, risk systems, and other data-driven applications.

Kalshi: real-time data for regulated event markets

Kalshi is a CFTC-regulated prediction market and event exchange. In April 2026, Kalshi selected Pyth Pro as the resolution source for its Commodities Hub, a product built around event contracts tied to gold, silver, Brent crude oil, natural gas, copper, corn, soybeans, and wheat.

The problem is structural. Commodity markets trade across global venues and time zones, while many traditional pricing windows are built around markets that close overnight or on weekends.

Prediction markets that trade continuously benefit from a resolution source designed for continuous markets. Pyth Pro provides direct data access to Kalshi’s market makers and supplies pricing for contract resolution.

The earlier Pyth–Kalshi integration also made regulated event-market data available across more than 100 blockchains, extending coverage beyond asset prices into political outcomes, economic policy, sports, culture, and other events.

John Wang, Head of Crypto at Kalshi, described the infrastructure requirement this way.

“As the exchange deepens our offerings in liquid commodities, it’s important that Kalshi’s markets are backed by fast, institutional-grade data. Pyth’s price feeds are both granular and easy to consume, complementing Kalshi’s mission to make these markets accessible to a broader set of retail and institutional participants.”

Kalshi shows how Pyth’s role is expanding from pricing assets to supporting the resolution of markets built around future outcomes.

Revolut: bringing digital banking into the publisher network

Revolut joined the Pyth ecosystem as a data publisher in January 2025. The digital banking platform contributes its proprietary digital-asset price data to Pyth, helping make that information available to applications and decentralized financial markets.

Mazen Eljundi, Revolut’s Global Business Head of Crypto, said:

“By working with Pyth to provide our reliable market data to applications, Revolut can influence digital economies by ensuring developers and users have access to the precise, real-time information they need.”

The Revolut integration is an example of the two-way movement between traditional and decentralized finance.

Financial institutions can publish data into programmable markets, while Pyth gives them a route to participate in new digital financial workflows without rebuilding the entire distribution stack.

Fenics: bringing dealer-to-dealer fixed-income data into the network

Fenics Market Data is the exclusive data-distribution arm of BGC Group, a major interdealer broker. Fenics has started working with Pyth Pro to make its institutional OTC pricing accessible through a single integration. Fenics represents data from more than $1 trillion in daily OTC transaction volume across rates, credit, FX, commodities, and energy.

By joining the Pyth ecosystem, Fenics brings executable pricing from institutional dealer-to-dealer activity into a network accessible through a single integration.

Rich Winter, President of Market Data and Information Analytics at Fenics, said:

“By contributing our global OTC pricing to the Pyth Network, we’re supporting the creation of a more connected, efficient, and data-driven financial system that brings institutional-grade transparency to the digital asset frontier.”

Fenics illustrates why fixed income is an important expansion area for Pyth. Much of the world’s bond pricing is formed in over-the-counter markets, where data has traditionally been fragmented across dealers, venues, and specialist vendors.

Bringing those sources into programmable infrastructure makes institutional fixed-income pricing more useful to trading systems, risk engines, analytics platforms, and digital markets.

Coinbase: from market data to continuously priced products

Coinbase is using Pyth at two levels: as a cross-asset pricing layer and as infrastructure for new financial products.

The Pyth Pro case study describes Coinbase using Pyth across crypto, equities, and FX, with access to more than 3,000 real-time feeds and latency below 100 milliseconds.

That pricing layer supports real-time asset pricing, collateral valuation, and liquidation infrastructure across markets.

Coinbase also launched four thematic basket indices built through the Pyth and MarketVector strategic partnership: AI10, Defense10, China10, and Tech100. Each index gives traders exposure to a market theme rather than a single company, with pricing designed to run around the clock.

The division of responsibilities is clear: MarketVector provides index methodology and governance, Pyth provides the underlying data and continuous pricing, and Coinbase provides the venue and distribution.

This is a useful example of market-data infrastructure becoming product infrastructure, the value of a data network is not limited to delivering a price feed; it can also support the creation, pricing, and distribution of new financial products.

Jane Street: market-maker data at the foundation

Jane Street joined Pyth as a data provider in 2021. The firm is a quantitative trading and liquidity provider active across equities, bonds, options, ETFs, and digital assets, with offices in New York, London, Amsterdam, and Hong Kong.

Jane Street’s role connects Pyth to the market-making firms closest to live price formation. That supply-side participation is central to building data infrastructure that can serve both institutional and digital markets.

SGX FX: institutional currency data across global liquidity hubs

SGX FX, a wholly owned subsidiary of Singapore Exchange Group, joined Pyth as a data publisher and contributes composite pricing across 74 currency pairs and more than 40 tenors. Those rates aggregate institutional liquidity across Singapore, Tokyo, London, and New York to produce a market-neutral mid-rate that reflects activity across multiple financial centers.

Distributed through Pyth to more than 114 blockchains and 710+ applications via a single integration, SGX FX’s data gives developers, financial institutions, risk systems, and analytics platforms access to institutional-grade FX pricing in a broader digital market environment.

Jean-Philippe Male, CEO of SGX FX, said:

“Contributing this critical pricing data to the Pyth Network is a deliberate step towards accelerating real-time, decentralized finance, ensuring the ecosystem is built on a foundation of trusted, institutional-grade data.”

SGX FX demonstrates the geographic dimension of Pyth’s institutional strategy. Financial data is generated across time zones and liquidity centers. Distribution infrastructure needs to follow that reality.

What this shift means for market data

The institutions building on Pyth represent more than a collection of logos.

Kalshi, Revolut, Fenics, Coinbase, Jane Street, SGX FX, Cboe Global Markets, Virtu Financial, Tradeweb, Euronext FX, OpenYield, Wintermute, B2C2, and Finazon each represent a different point in the market-data supply chain.

The model is simple: institutions can contribute data from the markets, venues, and systems closest to the underlying activity; Pyth distributes that data through infrastructure built for real-time applications; exchanges, protocols, risk systems, prediction markets, and financial products use it across markets.

As financial services become more automated and more connected to always-on digital markets, market data becomes a core piece of infrastructure.

The institutions participating in Pyth are helping define what that infrastructure looks like: broader, faster, more direct, and available through one integration.

The next phase of finance will be built by systems that can access the price of everything in real time. Pyth is building the market-data layer for that world.

Explore the Pyth publisher network and learn how you can join as a publisher.