Elliptic Launches Crypto Detection AI for Police: A New Threat to Money Launderers?

London-based blockchain analytics firm Elliptic has introduced an artificial intelligence (AI) product called Pulse, designed to help law enforcement officers in the field understand cryptocurrency transactions without needing blockchain expertise. The tool lets police enter a wallet address or transaction hash, then receive a plain-language financial summary in just seconds.

The launch of Pulse marks an important shift in modern law enforcement: crypto crime is no longer handled only by specialized units, but is beginning to touch the daily duties of ordinary police officers. According to Elliptic, the tool can be used when crypto is found on a suspect's phone, in fraud evidence, or even at an overdose scene—situations that demand quick decisions on whether a case needs to be escalated.

If a deeper investigation is needed, one click forwards the full analysis, including reasoning and officer field notes tagged with a case number, to Elliptic's forensic screening and tracing tools or the relevant agency's workflow. The detective receiving the report does not need to be a blockchain specialist.

"We built Pulse because we're seeing crypto in every law enforcement agency now, not just specialized units," said Jackson Hull, Chief Technology Officer of Elliptic.

Pulse runs on the same intelligence platform as Elliptic's investigative tools, which the company claims monitor more than 99% of crypto trading volume and cover more than 65 blockchains. The company also highlighted the agentic AI governance framework it published this month, emphasizing human oversight, model transparency, and final decisions remaining in the hands of officers, not AI.

For Indonesia, Elliptic's move is an important mirror. Authorities such as Bareskrim Polri and PPATK face similar challenges: rising fraud and money laundering cases that use crypto assets. The presence of tools like Pulse could speed up investigations, but it also demands readiness in human resources and clear regulation. Without adequate training, the risk of misinterpreting data could lead to unfair criminalization.

Moreover, the adoption of AI in law enforcement raises ethical questions. Although Elliptic emphasizes human oversight, concerns remain about algorithmic bias and accountability when decisions are made based on machine recommendations. In Indonesia, where digital literacy is still uneven, the use of such tools must be accompanied by transparency and appeal mechanisms.

Looking ahead, will technology like Pulse become standard in police forces worldwide, including Indonesia? Or will it instead widen the gap between developed and developing countries in their ability to combat cyber crime? The answer will depend heavily on infrastructure readiness and government commitment to invest in this field.