About
ValCtrl is building an intelligent prediction market where users type public, resolvable beliefs about the future, which the platform structures, prices, and enables them to trade. Its differentiation is a world model that maps beliefs to market signals and basis risk, while its intended signal customers include insurers, funds, corporate-development teams, and supply chains.
Market
ValCtrl competes in prediction markets, event contracts, and the emerging prediction-finance market, positioning itself as an intelligent market where users type any belief, receive a price, and trade. Its intended differentiation is a world model that maps beliefs to market signals, evaluates basis risk, reprices correlated markets, and provides model-priced fills rather than relying on a conventional listed-contract order book. It also plans to monetize the resulting information through signal subscriptions for insurers, funds, corporate-development teams, and supply chains.
ValCtrl appears to target individual users and informed traders who want to price and trade arbitrary beliefs about future events, as well as institutional risk and strategy teams at insurers, investment funds, corporate-development groups, and supply-chain organizations that may buy cross-market information signals. The public evidence does not specify a target company-size segment.
At a Glance
Problem
Prediction markets are constrained by the questions exchanges choose to list. Users begin with beliefs about future events, while exchanges require hand-written contracts with fixed wording, rules, and settlement criteria; as a result, many valuable, tradeable questions never exist in a usable market. ValCtrl points to Kalshi’s roughly 8,000 live questions and the fact that about 80% of its volume is sports as evidence of the gap: outside sports, informed trading can dominate, order books remain thin, and the exchange model becomes economically difficult to sustain.
The killer use case is a user who has a specific, public, resolvable belief—about geopolitics, politics, markets, deals, rates, or another future event—but cannot find an exact contract to trade. ValCtrl aims to turn that otherwise unpriced belief into a market and, in doing so, make prediction-market information useful beyond the heavily subsidized sports segment.
Product / Service
ValCtrl is building an intelligent prediction market in which a user types any public, resolvable belief about the future. The system structures the belief, finds related market signals, evaluates basis risk, prices the claim, and moves toward model-priced liquidity in which ValCtrl can take the other side subject to risk and compliance controls. Its initial live product, Kassandre, is a belief-search interface that maps a typed question to existing markets and exposes gaps between them.
The market itself is fully built on ValCtrl’s internal testnet, while public launch is gated on regulatory clearance. The intended business model combines per-trade fees with subscriptions to proprietary cross-market signals for insurers, funds, corporate-development teams, and supply chains; those signals are generated from trades and are intended to sharpen pricing and help fund winning payouts.
Market
ValCtrl competes in prediction markets and the emerging “Prediction Finance” category, positioning itself against listed-contract exchanges such as Kalshi by making the market itself responsive to user beliefs rather than limiting users to prewritten questions. The company was founded in 2025 by Sarth Garg and Gaurav Paliwal, is a Spring 2026 Y Combinator company, and is based in New York City with a two-person team. PitchBook reports $500,000 of funding and identifies Y Combinator as an investor.
Traction is currently product and infrastructure traction rather than demonstrated public-market revenue. Kassandre’s search product is live, with the company reporting 2.4-times daily belief-query growth from its first week, about 10,000 markets mapped, roughly 260 daily queries, and more than 100,000 correlations mapped on its internal testnet. Because the tradable market remains gated on regulatory clearance and the available evidence does not report customers or revenue, ValCtrl is best characterized as pre-public-launch rather than an established revenue-generating exchange.
Founders & Leadership
Funding History
Y Combinator
Recent News
Returner.fund lists ValCtrl among its startup profiles and identifies it as a YC Spring 2026 company, with an evidence score of 8.
Y Combinator’s New York startup directory describes ValCtrl’s product as an intelligent prediction market where users submit public, resolvable beliefs that ValCtrl structures, prices, and enables them to trade.
Extruct’s YC P26 dataset highlights ValCtrl’s Kassandre product, which turns typed claims into market matches, proxy markets, missing legs, source records, and match confidence.
ValCtrl’s official product site presents Kassandre as its live pre-market wedge. The site says the market is built on an internal testnet, with public launch gated on regulatory clearance.
Chris Lu’s analysis identifies ValCtrl as one of six Spring 2026 YC companies building infrastructure for prediction markets rather than a consumer-facing product.
Jaisal Rathee’s roundup lists ValCtrl in YC’s Spring 2026 batch and characterizes it as building a world model for prediction finance.
Y Combinator’s company profile says ValCtrl lets users type public, resolvable beliefs about the future, then structures, prices, and enables trading on them. The profile lists ValCtrl as an active Spring 2026 company founded by Sarth Garg and Gaurav Paliwal.
Dealroom’s company record describes ValCtrl as a world model mapping beliefs to prediction markets and lists $125,000 in 2026 Y Combinator funding.
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Get notified when they postBusiness Model
ValCtrl plans to earn per-trade fees on instant, model-priced fills and subscription revenue from proprietary cross-market signals sold to insurers, funds, corporate-development teams, and supply chains. The company says these fees and subscriptions will fund payouts to winning traders.