Warsaw-Based Elastics Raises €1.7 Million to Build AI Agents for Prediction Markets

Why It Matters

By automating quantitative strategies with conversational AI, Elastics could level the playing field between retail participants and hedge‑fund quants, accelerating adoption of prediction markets as a mainstream asset class.

Key Takeaways

• Elastics secured €1.7 million ($2 million) pre‑seed round.
• AI agents aim to democratize quantitative trading in prediction markets.
• Funding led by French VC Frst, joined by notable tech angels.
• Platform’s ‘Trade with Words’ lets users execute trades via plain language.
• Prediction‑market valuations nearing $9‑$22 bn highlight growing market opportunity.

Pulse Analysis

Prediction markets have moved from niche betting platforms to a burgeoning asset class, with valuations such as Polymarket’s $9 billion and Kalshi’s $22 billion underscoring investor confidence. The rapid inflow of capital reflects a broader shift toward data‑driven speculation, where participants bet on outcomes ranging from election results to macroeconomic indicators. Yet the infrastructure remains fragmented, and most retail traders lack the sophisticated models and automation pipelines that institutional funds deploy. This gap creates a fertile environment for technology firms that can translate complex quantitative strategies into accessible tools.

Elastics positions itself at the intersection of AI and finance, delivering an operating system that abstracts away code in favor of natural‑language commands. Its "Trade with Words" interface allows users to describe a position—such as "buy a long contract on US inflation expectations"—and have the system generate signals, manage risk, and execute orders automatically. Backed by a €1.7 million seed round led by Frst, the startup is hiring AI researchers and quantitative analysts in Poland to refine its large‑language‑model agents and expand the platform’s predictive capabilities. The involvement of high‑profile angels from ElevenLabs, a16z and Alven signals strong belief in the commercial viability of AI‑driven market participation.

If Elastics succeeds, the competitive dynamics of prediction markets could shift dramatically. Retail traders equipped with AI agents would gain near‑institutional speed and analytical depth, potentially increasing market liquidity and price efficiency. Conversely, traditional broker platforms that cling to legacy order‑ticket interfaces may lose relevance as conversational AI becomes the norm. For the broader fintech ecosystem, Elastics exemplifies how generative AI can democratize complex financial services, opening new revenue streams while reshaping how markets are accessed and traded.