Stay connected with KayaToday, follow us on Instagram and Facebook for the latest news and reviews delivered straight to you.
Tracing stolen or suspicious crypto has long required either expensive specialist software or a forensics firm willing to take on your case. AMLBot, a crypto compliance and forensics company, is betting that the barrier is too high and that most people who need answers simply cannot clear it. Its newly launched AI Tracer is designed to change that equation by letting anyone with a transaction hash map where funds went, without needing to hire an expert first.
The tool, announced in a press release shared with Cointelegraph, automates the graph traversal that blockchain investigators normally perform manually. A user submits a transaction hash, and the system follows the movement of funds from the originating address through intermediate wallets to wherever the money ultimately landed, matching known entity labels such as exchanges, flagged addresses, and other services against every wallet it encounters along the way.
What the Tool Actually Does Under the Hood
The core mechanism is transaction graph analysis, a technique that treats every wallet address as a node and every on-chain transfer as a directed edge connecting them. Investigators have used this approach for years to reconstruct fund flows in hacks, scams, and ransomware cases. The manual version is time-consuming and requires familiarity with block explorers, clustering heuristics, and entity databases. AI Tracer automates the traversal and layers AMLBot’s own entity labelling on top.
Critically, the tool also follows funds across bridges, the protocols that move assets between different blockchain networks, and tracks splits where a single source wallet fans out into multiple destination wallets. Cross-chain tracing has historically been one of the harder problems in crypto forensics because the asset effectively changes form as it moves from one network to another, breaking the on-chain thread that investigators rely on. Whether AMLBot’s bridge coverage is comprehensive or limited to the more popular protocols is not specified in the announcement.
Supported networks at launch include Bitcoin, Bitcoin Cash, Litecoin, TRON, Ethereum, BNB Chain, Ethereum Classic, Polygon, Arbitrum, Base, Optimism, Solana, Cardano, and Ripple, covering the chains where the majority of retail crypto activity and a large share of illicit flows occur.
Honest About the Limits, Which Matters
The more interesting part of the announcement is what AMLBot explicitly says the tool cannot do. AI Tracer cannot see transfers between internal exchange accounts, meaning that once funds reach a centralised exchange and move between users within that platform, the trail goes dark. It cannot determine why a payment was made, freeze assets, or guarantee recovery of lost funds. The reports it generates are described as a starting point for investigations, not a substitute for a formal audit or legal process.
That transparency is worth noting because the forensics space has a history of overselling what on-chain analysis can prove. Courts in several jurisdictions have pushed back on blockchain tracing evidence presented as more definitive than the underlying methodology supports. By framing its output as investigative starting material rather than conclusive proof, AMLBot is positioning the tool more responsibly than some competitors have in the past.
The free tier allows basic checks, with paid plans unlocking higher volumes of automated queries, making it accessible to individual researchers or journalists while still monetising heavier institutional use.
Who This Is Actually For, and Why It Arrives Now
AMLBot lists journalists, independent researchers, traders, law enforcement agents, and compliance teams as its target users. That is a deliberately wide net, and it reflects a genuine gap in the market. A retail investor in Kuala Lumpur or Singapore who has been scammed through a pig-butchering scheme or a fake investment platform currently has very limited options for understanding where their funds went before engaging law enforcement or a recovery firm. A tool that can at least map the visible on-chain path gives that person something concrete to bring to a police report or a lawyer.
For compliance teams at smaller crypto businesses, particularly those operating under the regulatory frameworks set by Malaysia’s Securities Commission or Singapore’s Monetary Authority, the cost of enterprise-grade forensics tools from firms like Chainalysis or Elliptic can be prohibitive. A self-service option with a free entry point lowers the floor for basic transaction screening, though it would not satisfy the more rigorous requirements of a formal AML audit.
The timing also connects to a broader trend. AMLBot’s own research, reported separately, found that social engineering drove 65 percent of the crypto cases it investigated in 2025, a figure that suggests the volume of individual victims seeking to trace funds is growing. Tools that democratise the first step of that process serve a real need, even if they cannot complete the journey on their own.
The honest ceiling on what AI Tracer delivers is also its most important feature. Blockchain forensics has always been a discipline where visible on-chain data tells only part of the story, and the parts that matter most, who controls a wallet and whether a recovery is legally actionable, still require human expertise and institutional cooperation. What AMLBot has built is a more accessible front door to that process, not a replacement for what lies behind it.
Read More: Luno’s 20% Headcount Cut Signals a Deeper Shift in How Crypto Companies Are Built
