A new prediction market exchange applicant has entered the Commodity Futures Trading Commission’s regulatory pipeline, with PMEX Markets listed as a pending Designated Contract Market (DCM) in a filing dated Feb. 9 on the agency’s trading organization portal. The filing is tied to Pluto, a venture-backed startup aiming to build financial markets around artificial intelligence infrastructure costs, according to CEO Ronit Jain.
Jain confirmed to DeFi Rate that PMEX Markets is the regulated exchange entity for Pluto, formerly known as Strike, and that the company is also pursuing approval for PMEX Clearing, a related clearing organization.
DCM status would allow Pluto to run a regulated derivatives exchange, list markets and self-certify contracts with the CFTC. A Derivatives Clearing Organization (DCO) approval from the CFTC would allow the company to clear trades, manage collateral and serve as the middle party between buyers and sellers. Together, those approvals would let Pluto keep much of the trading process in-house, a structure similar to what major U.S. prediction market operators like Kalshi and Polymarket US have.
But unlike Kalshi and Polymarket, which built much of their early momentum around retail event contract trading, Pluto is emphasizing institutional hedging use cases from the outset, particularly around AI infrastructure risk.
Jain confirmed to DeFi Rate that “the focus of the exchange will be on commoditizing AI infrastructure, starting with GPUs/Compute.”
Pluto striving to turn AI compute into financial assets like oil, gold commodities
Pluto is positioning AI compute resources as tradable financial assets. Jain framed the ambition explicitly in commodity-market terms.
“The aim of the exchange is to turn compute into a financial asset just like oil, gold, (or) other commodities,” he told DeFi Rate, adding that this would involve participants from across the ecosystem, including lenders, speculators and enterprises, as well as neoclouds and hyperscalers.
Neoclouds generally refer to newer cloud computing providers focused heavily on artificial intelligence workloads, often leasing large volumes of graphics processing units (GPUs) to AI developers and startups. Hyperscalers, by contrast, are the dominant global cloud platforms like Amazon Web Services, Microsoft Azure and Google Cloud, which operate massive datacenter networks and supply much of the world’s commercial AI compute capacity.
Treating AI compute as a commodity reflects how important processing power has become to the tech economy. Demand for GPUs, datacenter capacity and the electricity needed to run AI systems has surged in recent years, leading to price swings, supply constraints and new financial risks across the sector.
AI infrastructure focus draws investor attention
Pluto was recently highlighted this week in a Forbes feature examining the surge of venture capital into prediction market startups. The article describes Pluto as a platform for markets tied to AI infrastructure economics rather than traditional political or sports prediction markets.
Jain told Forbes that the platform will act as a kind of insurance for AI companies, as well as banks and other firms who’ve invested millions in datacenters.
“We want to be that financial layer to help people hedge, trade and speculate on a commodity that’s arguably the most important commodity of the next 10 years,” Jain told Forbes.
According to the report, Pluto raised roughly $3 million in seed funding last year and has been seeking additional capital while awaiting regulatory approval to launch. Sources close to the project told Forbes that the company is seeking $7 million in a forthcoming funding round that would value Pluto at around $60 million.
Public startup directories list Jain and co-founder Aarav Patel as participants in Y Combinator’s Winter 2025 cohort under the earlier Strike brand. Y Combinator is a well-known Silicon Valley startup accelerator that provides early funding, mentorship and investor connections to young companies. Participation in Y Combinator, whose alumni include companies like Coinbase, DoorDash, Airbnb, Reddit, and Kalshi, often signals early investor interest and can help startups secure additional funding and industry partnerships.
According to Forbes, Jain previously worked on algorithmic trading research connected to early Kalshi weather prediction markets while studying engineering at UC Berkeley.
Jain had previously emphasized institutional use cases for the Pluto project. In a LinkedIn hiring post late last year he wrote, “We’re working on a prediction market that will revolutionize how enterprises manage risk.”
What the PMEX CFTC filings show
The CFTC submission does not reference Pluto by name, but the documents align structurally with an event-contract exchange rather than a traditional commodity futures venue.
The draft rulebook describes binary-style contracts settling based on whether specified outcomes occur. That framework is commonly used for prediction market derivatives, including contracts tied to economic indicators, weather events or technological developments.
No specific market examples are included in the filings. But potential Pluto markets could include contracts tied to AI infrastructure costs and availability. Examples might include whether GPU prices exceed certain thresholds, whether datacenter buildouts meet projected capacity targets, or whether AI compute demand will outpace supply over a defined period.
Regulatory path ahead for PMEX
CFTC approval timelines for new exchanges vary widely. Some DCM applications have taken six to seven months to gain approval, while others have stretched into multi-year reviews depending on contract complexity and regulatory concerns. Recent filings and approvals, however, suggest the process may be moving faster under the agency’s current leadership as the number of prediction market platforms seeking approval continues to grow.
If approved, markets tied to AI compute infrastructure would add a new dimension to prediction markets. Some newer entrants are exploring whether prediction markets can support financial risk management tied to both established and emerging industries, while established platforms are also making a push toward institutional trading.
The timing of PMEX’s filing is notable. Investment in AI infrastructure is accelerating rapidly, while prediction markets themselves are drawing increasing institutional attention. Bringing those two trends together reflects a growing view that market-based forecasting tools may play a role in managing uncertainty around technologies that are still evolving but are already starting to reshape major parts of the economy.
