Leading blockchain analytics firm Chainalysis is adding artificial intelligence agents to its platform, lowering the technical know-how needed to launch mainstream investigations into crypto-economic matters.
“This is a really important moment to reduce the barrier to access to blockchain intelligence,” Chainalysis co-founder and CEO Jonathan Levin told CoinDesk in an interview. Not only law enforcement agencies, but also more people from traditional finance increasingly need to understand the movement of digital assets over blockchain transactions.
“We’re at this moment where you have to be able to access that intelligence without the whole history of working with crypto for a long time,” Levin said. The new tool for assembling custom AI agents will be embedded in his company’s platform and allow non-technical requests to build custom investigations supported by the depth and breadth of approach needed for serious investigation, including audit trails and standards of evidence.
The agents, said to be rolled out over the summer, can help users identify what analysis they need and what transactions might be relevant, Levin said, and the work will be informed by about 10 million studies conducted in the Chainalysis Reactor software. This is not just a chatbot, he emphasized.
The Chainalysis announcement comes hot on the heels of competitor TRM Labs’ similar announcement that its users now have agent support, suggesting a new AI era is starting for blockchain analytics. The criminal operations they analyze have already started using AI themselves.
Chainalysis is the best analytics partner for law enforcement agencies that increasingly need to figure out how criminals move assets across blockchains and across borders.
“People can actually build their own agents to be able to produce custom workflows for whatever they’re doing,” Levin said. “Every company is different. Every law enforcement agency may have different pieces of work that they need to do, and so we’re building a platform for them to build those agents.”



