Myriad is a new type of prediction market built to meet users exactly where they already spend their time online. Instead of visiting a standalone prediction site, traders can interact with markets directly inside news articles, X/Twitter threads, YouTube videos, or crypto blogs. A small widget—or a browser extension—overlays real-time prediction markets on top of the content being viewed, letting users place a trade in the same moment they learn about a story.
This “media-led” design is Myriad’s biggest differentiator. It turns passive reading into active participation. If you’re reading an article about the next Bitcoin halving, a Myriad market might appear right inside the text, allowing you to instantly trade on whether BTC will reach a certain price by a given date. This lowers friction dramatically and transforms forecasting from a separate activity into a natural part of consuming information.
Under the hood, Myriad is fully decentralized. It runs on multiple blockchains—like Arbitrum and BNB Chain—to ensure low fees and fast execution. Trading happens using USDC, a crypto stablecoin pegged to the US dollar, making it a real-money prediction market similar to Polymarket. Markets are created by the community and cover everything from crypto and politics to breaking news and entertainment.
Myriad is also introducing “Automated Markets”—fast, auto-resolving markets that run on short timeframes, such as five-minute intervals for live crypto price movements. These markets offer a rapid, almost game-like trading experience for users who want to forecast high-frequency data.
Because Myriad is on-chain, all activity is transparent. Every trade, price movement, and probability adjustment becomes public data—helping researchers, analysts, and developers understand how sentiment forms around major events in real time.
Myriad matters because it merges prediction markets with the information ecosystem itself. By embedding forecasts inside media, it captures user sentiment at the exact moment news is consumed, turning prediction markets into a live, real-time layer across the internet.
The embedded model reduces friction dramatically. Instead of navigating to a separate platform, users trade the moment curiosity strikes—right inside the content they’re reading. This leads to higher participation, faster reaction times to breaking news, and a more accurate expression of crowd sentiment. By pairing information consumption with instant action, Myriad creates a feedback loop that traditional platforms can’t replicate.
Decentralization ensures transparency and trust—critical for real-money prediction markets. By operating on chains like Arbitrum and BNB Chain, Myriad benefits from low-cost transactions and fast settlement, making trading accessible and efficient. Multichain support also expands the ecosystem, allowing the platform to grow across different blockchain communities and user bases.
Because all activity is on-chain, Myriad produces a continuous stream of public, verifiable prediction data. Each market’s price reflects a real-time probability, shaped by thousands of independent traders. This creates a rich sentiment dataset for crypto events, political outcomes, macroeconomic releases, or breaking news. Analysts can use this data to understand how expectations shift, how markets react to information, and how collective intelligence forms around major events.
You’re reading a Decrypt article about whether Ethereum will hit a certain price target before the end of the month. A Myriad market appears directly within the article showing a live probability. With one click, you can buy “Yes” or “No” shares using USDC—trading instantly without leaving the page. As new information enters the conversation, the embedded market updates in real time.
FinFeedAPI’s Prediction Market API aggregate Myriad’s on-chain data. Developers can build dashboards that monitor Myriad market movements, analyze crypto sentiment in real time, or compare Myriad probabilities with other forecasting signals. Because Myriad’s data is transparent and blockchain-native, it’s a powerful source of forecasting intelligence for apps, research, and automated tools.
