Crypto forensics and compliance company AMLBot has launched its AI Tracer, described as a self-service blockchain analysis tool that maps visible fund movements from a transaction hash across blockchain networks.

AMLBot said the tool aims to address the current need for specialist software and knowledge to trace transactions. The company said the tool also traces through bridges that move assets cross-chain or when the assets are split among multiple wallets.

“The process is automatic: the AI traverses the transaction graph, follows the movement of funds from the starting address through intermediate wallets toward whatever endpoint the money reached, and matches known entity labels — exchanges, services, flagged addresses — against every wallet it encounters,” the company said in a press release shared with Cointelegraph.

According to the announcement, AI Tracer cannot see transfers between internal exchange accounts, determine why a payment was made, freeze assets or guarantee recovery. Its reports are intended as a starting point for investigations and do not replace an audit or legal process.

The tool offers a free check and offers paid plans with higher limits on the number of automated checks. Currently supported networks include Bitcoin, Bitcoin Cash, Litecoin, TRON, Ethereum, BNB Chain, Ethereum Classic, Polygon, Arbitrum, Base, Optimism, Solana, Cardano and Ripple.

AMLBot said the tool is suitable for journalists, researchers, traders, and crypto user who want to read transaction paths, as well as law enforcement agents investigating crypto crime and independent investigators or compliance teams.

Related: AMLBot says social engineering drove 65% of crypto cases it probed in 2025

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At the time the platform’s website showed only a landing page, and CoinDesk could not verify whether it was operational or whether any cargo owners had used it. Fars claimed at the time the model could generate more than $10 billion without explaining how it arrived at that figure.

The policies were approved by the Persian Gulf Strait Authority, an IRGC-backed body Treasury designated in May. Both firms were sanctioned under an executive order covering Iran’s petroleum and petrochemical sectors.

Designation means U.S. persons are barred from dealing with the two companies, and foreign firms that transact with them risk sanctions themselves. Payments in bitcoin carry the same exposure as payments through banks.

“With its economy in freefall and inflation in the triple digits, the regime is desperate for cash,” Treasury Secretary Scott Bessent said in the statement.

The Strait of Hormuz is one of the world’s most important energy chokepoints, and traffic through it has thinned during weeks of U.S. strikes on Iran that have kept oil prices elevated.

AMLBot, a crypto compliance and forensics company, has introduced AI Tracer—an automated, self-service blockchain analysis tool that follows the trail of funds from a given transaction hash across multiple networks.

The company positions AI Tracer as a way to reduce the reliance on specialist tracing software and deep internal expertise, enabling users to map visible movement on-chain from a starting transaction through intermediate wallets to the eventual endpoint.

Key takeaways

• AI Tracer is built to trace fund movements from a transaction hash across supported blockchains.
• It can follow cross-chain transfers through bridges and handle flows where assets are split across multiple wallets.
• Reports rely on matching known entity labels (such as exchanges and flagged addresses) but are not a substitute for legal or audit processes.
• The tool offers free checks and paid plans with higher limits on the number of automated analyses.
• Initial support covers major networks including Bitcoin, Ethereum (and several L2s), Solana, TRON, and Ripple.

How AI Tracer maps transaction paths

In a press release provided to Cointelegraph, AMLBot described AI Tracer as “self-service” analysis that automatically traverses a transaction graph. The stated workflow follows funds from the starting address, through intermediate wallets, and toward whatever endpoint the assets reached.

A key part of the system is entity labeling: AMLBot says the tool matches known labels—such as exchanges, services, and flagged addresses—against wallets encountered during tracing.

This matters for investigators and compliance teams because manual graph reconstruction across complex transaction histories can be time-consuming, especially when transfers involve many hops, multiple wallets, or routing patterns typical of illicit movement attempts.

What the tool can’t do

AMLBot also emphasized limits that users should understand before relying on outputs. According to the announcement, AI Tracer cannot:

• See transfers occurring between internal exchange accounts.
• Determine the reason a payment was made.
• Freeze assets.
• Guarantee recovery of funds.

The company further noted that AI Tracer reports are intended as a starting point for investigations and do not replace audit procedures or legal processes. That framing is important in practice: blockchain tracing can reveal address-to-address movement, but it cannot by itself establish intent, contract context, or operational control over funds.

Cross-chain tracing and split flows

AMLBot said AI Tracer is designed to trace through bridges used to move assets cross-chain, as well as situations where assets are split among multiple wallets. These are two areas where transaction tracing often becomes harder than a simple “send and receive” pattern.

Cross-chain movement can obscure the path of value when assets are wrapped, bridged, or reconstituted on a different network. Meanwhile, split flows can require tracking multiple branches of a transaction graph to understand where value ultimately consolidated. By explicitly calling out these scenarios, AMLBot suggests AI Tracer is meant to handle more realistic transaction structures rather than only single-line transfers.

Coverage, access model, and who it’s for

AMLBot’s announcement says AI Tracer currently supports these networks: Bitcoin, Bitcoin Cash, Litecoin, TRON, Ethereum, BNB Chain, Ethereum Classic, Polygon, Arbitrum, Base, Optimism, Solana, Cardano, and Ripple.

The tool includes a free check, while paid plans provide higher limits on the number of automated analyses users can run. AMLBot described the product as suitable for a range of users, including journalists, researchers, traders, and crypto users who want to read transaction paths, as well as law enforcement and independent investigators or compliance teams.

That target audience reflects a broader trend in the industry: as regulators, exchanges, and institutional participants increase expectations around transaction monitoring and provenance checks, more tools are being built to make on-chain analysis accessible beyond specialized forensics teams.

Why the launch is timely for on-chain investigations

AI Tracer’s “from transaction hash to endpoints” approach addresses a practical bottleneck in crypto investigations—turning raw blockchain data into a readable path that can be acted on. While it still cannot explain intent or replace legal review, AMLBot’s positioning suggests it is designed to speed up early-stage work: triage, mapping routes, and narrowing down where further diligence should focus.

As cross-chain activity and multi-hop transaction structures become more common, users are likely to judge tools less on whether they can follow basic transfers and more on how well they handle routing complexity—particularly bridge interactions and wallet splits, both of which AI Tracer is explicitly meant to cover.

Going forward, the main questions for users will be how consistently AI Tracer’s entity labeling reduces ambiguity across different networks, and how the product’s limits and supported chains expand over time—especially as investigations increasingly span L2s, bridges, and liquidity-driven flows.

Circle Internet Group, Inc. (CRCL), the issuer of USDC, the world’s second-largest stablecoin, announced Friday that it secured a limited purpose trust charter from the New York Department of Financial Services (NYDFS).

The trust charter is an official state banking authorization that allows the holder to legally provide fiduciary, custody and asset-management services under the New York Banking Law.

“Earning a New York trust charter has been a longstanding objective for Circle given the regulatory clarity that comes with it,” said Jeremy Allaire, Co-Founder, Chairman, and CEO of Circle.

Circle’s stock price remains flat Friday morning at $64.24 and its stablecoin USDC has a market capitalization exceeding $71.8 billion.

Earlier this month, Circle received approval from the U.S. Office of the Comptroller of the Currency (OCC) to establish a national trust bank.

National trust banks are authorized to provide users with custody and fiduciary services but do not accept consumer deposits or make loans like traditional commercial banks.

The stablecoin issuer said the national bank would “enhance the safety and regulatory oversight of the USDC Reserve, while enabling Circle to offer fiduciary digital asset custody and related services to institutional customers.”

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New York has filed a lawsuit against prediction market platform Kalshi, arguing the company operates an illegal, unlicensed gambling business in the state by offering contracts tied to outcomes such as sports events and elections. The case seeks to halt Kalshi’s alleged activity, recover money described as illegal gains, and impose civil penalties.

New York Attorney General Letitia James said in a statement that “no matter what they call themselves, prediction markets like Kalshi are gambling platforms, plain and simple,” adding that the state is acting to enforce its laws and protect residents. The complaint also follows regulatory action by the New York State Gaming Commission, which previously issued a cease-and-desist order.

Key takeaways

• New York is suing Kalshi to stop what it characterizes as unlicensed gambling conducted through “event contracts” tied to outcomes including elections and sports.
• The lawsuit seeks forfeiture of alleged illegal gains, restitution to users, and civil penalties stated as three times those gains.
• The dispute reflects a wider U.S. jurisdiction fight over whether states can enforce gambling laws against event contracts listed by federally regulated exchanges.
• The CFTC has argued—through emergency court filings in connection with the case—that it holds exclusive authority under the Commodity Exchange Act.
• Regulatory pressure on prediction markets comes as the segment grows, including through blockchain-based products and large-scale event-driven trading activity.

New York’s claims against Kalshi

According to the lawsuit, New York’s core position is that Kalshi’s prediction products amount to gambling under state law because they allow users to wager on outcomes. The state is asking the court for multiple remedies: an order stopping the alleged illegal operation, forfeiture of illegal gains, restitution to affected users, and civil penalties equal to three times those gains.

New York’s filing also follows earlier enforcement steps. The New York State Gaming Commission issued Kalshi a cease-and-desist order in October 2025. Kalshi responded by suing the regulator in federal court.

As described in the lead-up to the new lawsuit, a judge denied Kalshi’s request for a preliminary injunction in July, and an appeals court later rejected Kalshi’s attempt to block enforcement while its appeal continues.

Kalshi disputes New York’s framing. Elisabeth Diana, the company’s head of communications, said the action is “political theater,” arguing that states cannot simply shut down a federally licensed exchange, and warning that such a move would push users “offshore.”

CFTC says federal oversight should control

New York’s case sits within a broader legal contest about regulatory authority over prediction markets. In the days leading up to the lawsuit, the Commodity Futures Trading Commission (CFTC) filed an emergency motion in federal court seeking to block New York’s enforcement efforts.

The CFTC argued that New York’s approach interferes with the agency’s exclusive authority under the Commodity Exchange Act to regulate designated contract markets, including platforms such as Kalshi. Put differently, the federal regulator is asserting that once an exchange is operating within the CFTC’s framework, state gambling laws should not be used to restrict the same kinds of event contracts.

The CFTC has taken similar stances in disputes involving multiple states, positioning the conflict as an issue of federal supremacy and consistent commodities oversight. The regulator’s concern, as reflected in its court filings, is that allowing individual states to prohibit event contracts listed by federally regulated venues would create conflicting rules and “undermine federal commodities regulation.”

This framing matters for participants because it affects where prediction market activity can legally occur and how compliant operators must be. It also has practical implications for platform design and market access: if a state can apply its gambling rules regardless of federal designation, exchanges could face uneven compliance burdens across jurisdictions.

Prediction markets and mainstream momentum

Prediction markets operate by allowing participants to buy and sell contracts tied to future outcomes, with contract prices intended to reflect the market’s estimate of the probability that an event will occur. In recent years, this model has attracted increased attention—especially around high-profile events that draw large audiences.

Kalshi is not the only major player facing regulatory scrutiny. Polymarket, another prominent prediction market, has also encountered challenges abroad, with reporting noting restrictions and investigations tied to gambling and licensing concerns.

Meanwhile, the sector has continued to experiment with blockchain-based infrastructure. Kalshi began expanding into blockchain-based infrastructure in December 2025, launching tokenized prediction markets on Solana and later adding support for multiple blockchain networks. That shift underscores how prediction market operators are adapting product delivery, potentially changing how users access contracts and where trading activity occurs.

On-chain prediction markets have also shown signs of scale around major global events. According to analytics firm Chainalysis, blockchain-based prediction markets processed about $20 billion in trading tied to the 2026 FIFA World Cup, with more than 400,000 wallets participating—an example of the demand that can emerge when widely watched events create an appetite for probability-based trading.

What to watch as the legal fight advances

For market participants, the key question is whether the courts treat event-contract regulation as primarily a matter of federal commodities oversight—or whether states retain meaningful authority to apply their gambling laws to prediction platforms operating within (or near) federally regulated structures. The CFTC’s emergency motion and New York’s pursuit of enforcement remedies suggest the case could be used to clarify that boundary.

Readers should watch next for how federal courts address the CFTC’s arguments about exclusive jurisdiction, and whether any interim rulings change Kalshi’s ability to offer specific event contracts within New York while the broader appeal process plays out.