CipherOwl raises $15 million to advance AI-driven crypto compliance

Founded by Coinbase and Cruise veterans, CipherOwl plans to bring artificial intelligence to blockchain monitoring and risk detection

by Blockworks /
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CipherOwl, a crypto compliance startup founded by former Coinbase and Cruise engineers Leo Liang and Ming Jiang, has raised $15 million in seed funding led by General Catalyst and Flourish Ventures, with participation from Coinbase Ventures and Enlight Capital.

Originally reported by Fortune, the San Francisco–based firm develops artificial intelligence-driven tools to help financial institutions monitor blockchain transactions for suspicious activity as traditional banks and fintechs expand into digital assets.

Liang and Jiang, who previously worked on Coinbase’s internal compliance systems, launched CipherOwl in 2024 to address what they describe as the “dark forest” of crypto — the web of pseudonymous and cross-chain transactions that challenge conventional anti-money-laundering tools.

The company’s software uses generative AI to automatically flag risky transactions and generate plain-language reports explaining why an alert was triggered, streamlining manual reviews and lowering compliance costs.

Despite competition from established firms such as Chainalysis, Elliptic, and TRM Labs, CipherOwl has already onboarded clients including Coinbase, OKX, and several undisclosed law enforcement agencies.

With only eight employees, the startup aims to differentiate itself as “AI-native,” embedding machine learning into every layer of its detection process. According to General Catalyst managing director Marc Bhargava, this approach could give CipherOwl an edge as the compliance landscape matures and global regulators tighten oversight of crypto markets.

The company has not disclosed its valuation. The new capital will fund hiring and product expansion amid growing institutional demand for crypto risk and compliance infrastructure.

This is a developing story.


This article was generated with the assistance of AI and reviewed by editor Jeffrey Albus before publication.


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