Chainalysis, the leading blockchain analytics company, is adding artificial intelligence agents to its platform, reducing the technical knowledge required to launch plain language investigations into crypto-financial relationships.
“This is a really important time to lower the barrier to entry for blockchain intelligence,” Chainalysis co-founder and CEO Jonathan Levin told CoinDesk in an interview. Not only law enforcement officers, but also more people in traditional finance increasingly need to understand the movement of digital assets through blockchain transactions.
“We’re in this moment where you need to be able to access that intelligence without all the history of working in cryptocurrency for a long time,” Levin said. The new tool for assembling custom AI agents will integrate into your company’s platform and enable non-technical requests to create custom investigations backed by the depth and breadth of approach necessary for serious investigation, including audit trails and standards of evidence.
The agents, which are said to be rolled out over the summer, can help users identify what analysis they will need and what transactions may be relevant, Levin said, and the work will be based on about 10 million investigations conducted within the Chainalysis Reactor software. This is not just a chatbot, he emphasized.
Chainalysis’ announcement comes on the heels of competitor TRM Labs’ similar announcement that its users now have agent support, suggesting that a new era of AI for blockchain analysis is beginning. The criminal operations they analyze have already begun to use AI.
Chainalysis is the leading analytics partner for law enforcement agencies that increasingly need to uncover how criminals move assets across blockchains and borders.
“People can create their own agents so they can produce a custom workflow for whatever they’re doing,” Levin said. “Every company is different. Each law enforcement agency may have different tasks to perform, so we are building a platform for them to create those agents.”




