Chainalysis launches no-code investigation tools for non-technical teams

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Yaroslav Dmytrenko

20.01.2026

Chainalysis launches no-code investigation tools for non-technical teams — Chainalysis expands blockchain analytics access with new Workflows feature

Blockchain analytics company Chainalysis is making some of its analytical tools accessible to non-technical users, as the automation of on-chain investigations responds to a growing number of blockchain-related incidents.

Chainalysis’ new feature, called Workflows, enables non-technical teams to conduct blockchain investigations and compliance analysis without writing custom code. The tool reduces reliance on custom SQL or Python queries and expands blockchain investigation capabilities beyond a narrow group of developers.

Chainalysis told Cointelegraph that the tool is designed to standardize common investigative processes through pre-built templates, making them easier to replicate and apply across multiple cases as the company adapts its data products for a broader user base.

“What previously required deep technical expertise and significant time can now be done by any user in minutes,” said Ekim Buyuk, senior product manager at Chainalysis.

Instead of requiring users to understand data schemas, the system asks investigation-level questions such as which entities, wallets, or timeframes are relevant, Buyuk explained.

AI helps scale crypto theft

Buyuk noted that fraud and scam networks are often quick to adopt new technologies to scale their operations, citing Chainalysis research showing that AI-enabled scams extract 4.5 times more funds from victims than traditional schemes.

One of the challenges in fraud investigations is that losses from individual victims may appear small in isolation. However, blockchain analysis can uncover large-scale fraud networks involving hundreds or thousands of victims, with total losses reaching billions of dollars.

According to a recent Chainalysis report, crypto scams and fraud resulted in approximately $17 billion in losses in 2025, driven by a rise in impersonation schemes and the increasing industrialization of fraud operations using artificial intelligence, deepfakes, and professional money-laundering networks.

Several incidents at the end of the year highlighted these risks. On January 2, an attacker drained hundreds of wallets on Ethereum Virtual Machine–compatible networks, stealing less than $2,000 from each address. According to blockchain investigator ZachXBT, the incident was a large-scale but low-value attack that may be linked to a Ledger compromise.

As we wrote, Chainalysis challenges Binance crypto crime risk analysis methods

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