Overview
Chaos Labs is a risk management, oracle and AI-model platform securing DeFi protocols and on-chain financial markets [1]. The company maintains main offices in New York and Tel Aviv, with additional hubs worldwide [2]. Chaos Labs describes itself as turning complex, fragmented data into decision-ready, institutional-grade intelligence under the tagline "Clarity Through Chaos" [3]. The platform has processed 5 trillion in transactions [4]. Its customer base includes Circle, PayPal, Kalshi, Paradigm, Kraken, Aave, Ethena, Tether, LayerZero, Galaxy, Lightspeed, Jupiter, Agora, Uniswap and Coinbase Ventures [5]. The company has received backing from PayPal Ventures, Coinbase Ventures, OpenAI, Lightspeed and Bessemer Venture Partners, along with angel investors Balaji Srinivasan and Naval Ravikant [8]. Chaos Labs is hiring for roles including Forward Deployed Engineer, Senior AI Data Scientist and Senior Full Stack AI Engineer, with positions available in the United States and remotely [7].
Company website states "Our main offices are in New York and Tel Aviv, with additional hubs worldwide" [2]
Chaos Labs states on its careers page: "Our main offices are in New York and Tel Aviv, with additional hubs worldwide." [6]
Growth & traction
Chaos Labs' homepage displays the figure "5 TRILLION in transactions processed." [4]
Customers
Chaos Labs lists Circle, PayPal, Kalshi, Paradigm, Kraken, Aave, Ethena, Tether, LayerZero, Galaxy, Lightspeed, Jupiter, Agora, Uniswap and Coinbase Ventures as customers on its homepage. [5]
Funding history
Chaos Labs' about page lists PayPal Ventures, Coinbase Ventures, OpenAI, Lightspeed and Bessemer Venture Partners among its backers, along with angel investors Balaji Srinivasan and Naval Ravikant. [8]
Alumni
Recent developments
- Chaos Labs' careers page listed three open roles, all in the United States and Remote: Forward Deployed Engineer (Business), Senior AI Data Scientist (Data Science) and Senior Full Stack AI Engineer (Engineering).[7]
Focus
- Chaos Labs describes itself as building "infrastructure for organizations adopting AI at scale," helping enterprises understand AI work, capture organizational knowledge and improve how intelligence is created across the organization.[9]
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