Chainalysis has launched a new feature dubbed Workflows, which aims to automate on-chain analyses and enhance the detection of vulnerabilities within various blockchain networks. This innovation is designed to streamline the investigative processes for both researchers and security teams who actively monitor blockchain activities.
The introduction of Workflows is positioned as a significant advancement in reducing the necessity for manual analysis. By simplifying these processes, organizations can respond more swiftly to emerging risks in an increasingly intricate on-chain landscape. This feature allows users to initiate pre-configured investigative actions without the need to write any code, thereby alleviating the reliance on custom-built databases or scripts that often require expertise in languages like SQL or Python.
According to Chainalysis, the new solution emphasizes the standardization of frequently utilized investigative procedures. This is achieved through a collection of pre-built templates that guide users through established analytical workflows. The aim is to promote consistency across investigations while minimizing the potential for human error, which can frequently occur during manual analysis.
The Workflows feature integrates no-code, interactive tools that facilitate detailed blockchain analysis via an intuitive interface. These tools enable users to examine transaction histories, behavioral patterns, and network relationships without necessitating advanced programming skills. Chainalysis has highlighted that this user-friendly design empowers a broader spectrum of professionals to conduct thorough investigations more effectively.
At its launch, Workflows supports several essential analytical processes commonly employed in blockchain investigations. One such capability is time and amount analysis, which helps analysts narrow down potential transaction matches when funds are deposited into or withdrawn from platforms. This function allows for quick tracking of pertinent transactions based on timing and value thresholds.
Another integral function is common counterparties analysis, which identifies interaction patterns among blockchain users by analyzing shared transaction counterparts. This type of analysis can unveil coordinated behaviors, recurring relationships, or hidden networks that may suggest illicit activity. Notably, Workflows are now live within Chainalysis Data Solutions.
Additionally, the feature includes targeted searches for wallets and clusters, aiding investigators in pinpointing addresses that closely resemble known behavioral patterns associated with malicious actors. By focusing on these identifiable traits, analysts can more effectively flag and monitor potentially harmful entities operating within the blockchain.
Chainalysis has indicated that the current offerings represent just the initial phase of the tool”s development. Plans for future expansion include the addition of hundreds of workflows and mini-applications aimed at addressing a broader range of investigative and compliance needs as blockchain ecosystems continue to evolve.
The company believes that scaling the number of available workflows will enable security teams to adapt swiftly to new threats and investigative demands. Automation and modular tooling are regarded as vital components for managing the increasing volume and complexity of blockchain data.
This release of Workflows comes at a time when concerns are rising regarding the prevalence of blockchain-related crime. Earlier reports from Chainalysis experts estimated that losses from hacks in 2025 reached approximately $3.4 billion, with a significant portion exceeding $2 billion linked to activities associated with North Korean hacking groups.
In light of these challenges, Chainalysis has positioned Workflows as a pragmatic solution to escalating security issues. By automating core investigative tasks and enhancing accessibility to advanced analysis, the company aims to assist organizations in detecting threats more rapidly and bolstering defenses across the blockchain ecosystem.
