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Elastics Raises $2M Pre-Seed to Build AI Trading Infrastructure for Prediction Markets

The Warsaw-based startup is building AI-driven trading tools for prediction markets as investors shift attention toward automation infrastructure and event-based financial platforms.

Ilampirai Arivazhagan by Ilampirai Arivazhagan
May 6, 2026
in VC & Funding
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Elastics Raises $2M Pre-Seed to Build AI Trading Infrastructure for Prediction Markets
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A Warsaw-based startup developing AI tools for prediction-market traders has raised $2 million in pre-seed funding, joining a growing number of companies attempting to build software around the recent expansion of event-driven trading platforms.

The company, Elastics, said the round was led by Frst, with participation from individuals associated with ElevenLabs, XBTO, RedStone and the Andreessen Horowitz scout network.

The funding comes as investors increasingly target infrastructure startups linked to prediction markets, a sector that has grown rapidly alongside rising retail participation in political, economic, and sports-related event trading.

Elastics was founded by Szymon Pawica, a former Goldman Sachs employee, and mathematician Mateusz Brodowicz, who previously worked on quantitative models tied to prediction-market trading strategies. The startup is developing software intended to automate parts of the trading process, including market analysis, trade execution, and portfolio monitoring. The company’s platform remains in private beta.

Elastics raised $2M pre-seed for AI agents for prediction markets.

Led by @frst_vc, with angels from @ElevenLabs, @xbtogroup, @redstone_defi and @a16z.

Building AI-native operating system for prediction markets where you trade with words, and agents automate your trading. pic.twitter.com/AbgB4yjdXx

— Elastics (@ElasticsAI) May 5, 2026

Prediction Markets Draw More Capital

Prediction markets, once viewed as a niche corner of crypto trading, have gained broader visibility over the past two years. Platforms such as Polymarket and Kalshi have benefited from growing user activity tied to elections, central bank decisions, geopolitical conflicts, and major sporting events. A notable example of their expanding media footprint is the recent collaboration where Kalshi partners with Fox News for prediction market data, reflecting how event-based trading insights are entering mainstream news ecosystems.

Research firms tracking the sector estimate that prediction-market trading volumes increased sharply during 2024, fueled by election-related speculation and expanding retail participation. Investors have increasingly treated these platforms as an emerging financial category rather than a temporary crypto trend.

The growth has also attracted traditional market participants. Intercontinental Exchange, the parent company of the New York Stock Exchange, has shown interest in the broader event-contract market through investments and partnerships connected to the sector.

Despite that momentum, prediction markets remain controversial in several jurisdictions because regulators continue to debate whether event contracts should be treated as financial instruments, gambling products, or derivatives. Liquidity also remains concentrated around a relatively small number of high-profile events, making the market difficult for smaller traders to navigate consistently. Prediction market aggregator startup Fireplace is also emerging in this ecosystem as part of the growing infrastructure layer around event-based trading.

AI Firms Target Retail Traders

Elastics is part of a wider trend in which AI startups are targeting financial trading workflows. Rather than building exchanges directly, many newer firms are attempting to provide software layers that automate research, execution, and risk monitoring.

The company’s product centers on what it calls conversational trading. Users describe trading positions in plain language, while AI systems interpret those instructions and attempt to execute strategies automatically. The startup argues that traditional trading dashboards and order-entry systems may eventually be replaced by natural-language interfaces.

The idea reflects a broader push across financial technology firms to integrate large language models into investment software. Similar tools have emerged in equity trading, crypto analytics, and portfolio management over the past year, although most remain early-stage products with limited real-world testing during volatile market conditions.

Critics of AI-assisted trading systems argue that automation can amplify poor trading decisions if users rely too heavily on machine-generated outputs without understanding underlying market risks. Others question whether conversational interfaces can reliably handle the speed and precision required in fast-moving event markets.

Elastics said it plans to expand integrations with platforms including Polymarket, Kalshi, and Limitless, while using the new funding to hire AI engineers and quantitative researchers in Poland.

The company’s fundraising reflects a broader shift in venture capital activity toward infrastructure and automation startups after a prolonged slowdown in speculative crypto funding. Investors appear increasingly focused on companies attempting to build operational tools around trading markets rather than launching new tokens or exchanges.

AI Disclosure: Cryip uses AI-assisted tools to help refine language — correcting spelling and grammar and simplifying complex terms for readability.

We do this to make crypto topics easier to understand for readers at all experience levels. AI does not draft facts, sources, or conclusions. Every article is reviewed and approved by a human editor before publication. Read our full AI Use & Content Policy.

Disclaimer: Cryip’s content is strictly for informational purposes and does not constitute financial, legal, or investment advice. Asset references are not endorsements, and readers assume full responsibility for any financial decisions.
Ilampirai Arivazhagan

Ilampirai Arivazhagan

Ilampirai Arivazhagan is a data journalist and Web3 funding analyst at Cryip, covering venture capital activity, tokenomics, and crypto market data across global blockchain ecosystems. Her reporting applies IFCN and OSINT-based verification methods to blockchain claims, drawing on certifications in data journalism, journalism fundamentals (NBC Universal Academy), and AI for cybersecurity. Her research has been cited by Coincu and BlockEden.xyz.

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