Elastics, a Warsaw-based startup building an AI-powered platform for prediction markets, has raised $2 million in pre-seed funding to give individual traders access to tools that have historically been available only to institutional investors. The company was co-founded by Szymon Pawica, who previously worked at Goldman Sachs, and Mateusz Brodowicz, a mathematician from the University of Houston who built quantitative models for a prediction markets fund. Their core argument is straightforward: the infrastructure that gives hedge funds a trading advantage can now be built with AI and made accessible to anyone.
Prediction markets have grown quickly into a serious corner of finance. On these platforms, traders buy and sell contracts tied to the outcomes of real-world events, such as elections, sports results, or economic decisions. The price of each contract reflects what the market collectively believes the odds of that outcome to be. The two dominant platforms, Kalshi and Polymarket, generated more than $44 billion in trading volume in 2025, with sports-related contracts driving much of that year's growth. The Block Total industry volume for the year exceeded $63 billion, with monthly figures peaking near $25.7 billion in March 2026. Crypto News Most retail traders on these platforms, though, are still operating without any meaningful automation or analytical tooling. That is the gap Elastics is trying to fill.
The pre-seed round was oversubscribed and led by Frst, the Paris-based venture firm with over $200 million in assets under management. Angel investors include the co-founders of ElevenLabs, partners from XBTO, a16z Scout Fund, and a co-founder of RedStone.
Kalshi and Polymarket together account for an estimated 85 to 95 percent of total prediction market industry volume. Crypto News Institutional money has taken notice. Polymarket received a $2 billion strategic investment from ICE, the parent company of the New York Stock Exchange, which valued the platform at $9 billion. MEXC Kalshi closed at a $22 billion valuation. Both platforms have moved well beyond their early, niche audiences, yet retail traders on them still largely lack the kind of systematic tools that professional funds use as standard.
"Prediction markets are emerging as a new asset class in finance, and we believe the industry is still in its very early innings. Elastics is building the AI layer that this market needs and we're excited to back Szymon and Mateusz as they democratize access to quantitative trading tools that were previously out of reach for most participants." — Pierre Entremont, Co-Founder and Partner at Frst.
Most of the $2 million will go toward hiring AI and quantitative talent in Poland. Both founders view Poland as one of the strongest talent markets in the world for this type of technical work, and building that team early is a deliberate priority.
On the product side, the roadmap focuses on expanding Elastics AI, the agent builder, and Elastics OS. All three are in private beta, with early access available on application. The platform is built around the idea that trading should be conversational, meaning users give instructions in plain language rather than filling out order forms. Future development will deepen that capability across more markets and use cases.
Pawica has been direct about what he sees as a closing window for traders who rely on manual methods. As automation spreads through financial markets, he argues, the disadvantage for those without it will only grow.
Pawica's experience at Goldman Sachs shaped the company's founding premise. Working there, he observed quantitative funds operating with resources most individual traders will never have: teams of engineers and analysts building models, processing large volumes of data, and automating strategies around the clock. When he left and began trading on his own, the gap between what he had seen and what was available to him was hard to ignore.
Brodowicz came to the project from a different angle. His background is in mathematics, and he had already spent time building quantitative models for a prediction markets fund before co-founding Elastics. That experience gave him a working knowledge of exactly the kind of infrastructure the platform is designed to democratize.
Together, they built Elastics as what they describe as an AI-native operating system for prediction markets, a platform that handles automated research, trade execution, and portfolio management for individual users.
The most visible product feature so far is called "Trade with Words." Instead of navigating order forms, users describe what position they want to take in plain language, and the platform executes it automatically. Pawica has been clear about where he thinks this points.
"The old interface was designed for a world before AI. Every platform that hasn't rethought that from the ground up will have to." — Szymon Pawica, Founder and CEO of Elastics.
The round was led by Frst, a Paris-based early-stage venture firm with over $200 million in assets under management. Alongside Frst, a group of angel investors from the AI and crypto sectors joined the round, among them the co-founders of ElevenLabs, partners from XBTO, a16z Scout Fund, and a co-founder of RedStone. The round was oversubscribed.
