Mural said in a funding announcement that it has raised $28 million in total, including a $15 million Series A led by Tether. North Island Ventures and existing investors also participated in the round. The financing places Tether’s capital behind a company building account, payment, identity and compliance tools for fintech platforms and other businesses.

The investment is notable because the underlying opportunity is broader than faster settlement or another crypto payment application. Mural is targeting what it calls agentic finance, a model in which software can initiate and execute financial transactions for a person or business. That model could eventually move money with limited direct intervention from employees or account holders, but it also creates a difficult question: how can a company allow software to act while retaining control over where funds go and under what conditions?

Capital is moving toward the control layer

Mural’s product is positioned as an operating layer between businesses and the financial infrastructure they already use. According to the company, its tools cover accounts, payments, identity verification and compliance across conventional banking networks and blockchains. That combination matters because companies using autonomous software will still need access to regulated financial systems, even if the software itself is built around artificial intelligence.

The capital allocation suggests that investors see infrastructure as a more durable opportunity than a narrow application. Rather than betting solely on a new consumer payment product, Tether is backing systems that could support multiple fintech platforms and business use cases. Mural’s stated customers include payroll platform Deel and browser developer Opera, giving the company a foothold in products that already handle payments or financial interactions.

For Tether, the transaction also represents a way to extend its role beyond issuing USDT. Stablecoins can provide a programmable settlement asset, but a token alone does not resolve the operational requirements of a business payment. Companies need accounts, identity checks, permissions, monitoring and records. They also need a way to connect blockchain transactions with banking and payment systems that remain central to payroll, commerce and corporate finance.

That makes Mural’s infrastructure relevant to the flow of capital through both crypto and traditional channels. If autonomous software becomes a meaningful source of payment activity, the companies controlling its access to accounts and rails could influence how stablecoins are used in everyday commerce.

Autonomy requires permissioning

Live Tether (USDT) price against the U.S. dollar · Live chart: TradingView

The central selling point of agent-enabled payments is convenience. A software agent could potentially send funds, pay invoices or manage recurring transactions without requiring a person to approve every individual action. The same autonomy, however, creates exposure to fraud, mistaken instructions and compromised systems.

Mural says businesses can set transaction limits, restrict counterparties and require additional approvals for larger transfers. These controls are intended to create boundaries around what an agent may do. A low-value payment to an approved recipient could proceed automatically, while a larger or unusual transfer could be held for review.

Mural funding figures from its funding announcementUSD million0102030Total raised28Series A15
Mural funding figures from its funding announcement

Such permissioning is familiar in corporate treasury and payments systems, but agentic finance increases the importance of enforcing it consistently. A human employee may understand a policy and recognize an unusual request. An automated system depends on the rules, data and software environment it has been given. If those inputs are manipulated, the agent could follow an instruction that appears valid while producing an unauthorized outcome.

Limits and approval workflows also address only part of the accountability problem. A business may still need to determine whether a payment was approved by a user, generated by an agent, triggered by a compromised account or caused by an error in the software. That distinction could matter for reimbursement, internal investigations and regulatory reporting.

A test of whether agentic finance is real

The funding round provides evidence that venture investors and stablecoin companies are preparing for autonomous payments, but it does not yet establish the scale of demand. The commercial case will depend on whether businesses are willing to delegate meaningful financial activity to software and whether the resulting efficiency outweighs the cost of supervision and risk management.

Mural’s approach reflects a cautious version of that future. It does not present autonomy as the removal of human oversight. Instead, it focuses on controls that allow companies to automate selected transactions while preserving restrictions and escalation procedures.

That distinction could determine how quickly the category develops. If agents are limited to routine, low-value payments, adoption may grow gradually through payroll, treasury and business operations. If companies eventually trust them with larger transfers, the infrastructure supporting identity, compliance and authorization will become more strategically important.

Tether’s investment therefore signals more than interest in another financial technology company. It shows where the stablecoin issuer believes future payment liquidity may need to move: through systems that connect programmable assets with regulated accounts, and through controls that make autonomous activity auditable. The open question is whether those controls will be sufficient for businesses to treat AI agents as financial operators rather than experimental software.

#Tether#Mural#North Island Ventures#Deel#Opera#USDT
Image credits

Ethan Brooks is not a person. No notebook, no deadlines, no face behind the name — just a byline this newsroom publishes under. Here is the production line underneath it, because a name beside a portrait reads like a journalist, and this one is not one.

The models. Writing: gpt-5.6-luna. Out on the live web: gpt-5.6-luna and gpt-5.6-terra. Pictures: gpt-image-1. Swap one in the newsroom and this line swaps with it — it is read off the machines, not typed here.

How a story is made

  • Research. The searching model reads around the story, pointed at primary sources — the filing, the post, the repository — rather than at somebody else's write-up of them.
  • Writing. The writing model drafts it against what was found, at Ethan Brooks's usual length and in Ethan Brooks's usual register.
  • The loop. A reviewer reads the draft and sends it back with notes. Then reads it again. A piece can go round several times before it leaves the building.
  • Enrichment. A quotation has to appear word for word on the page it is taken from. A chart may only use figures that appear in the source it cites. Whatever fails is dropped, and the reason is kept.
  • Fact check. A last pass hunts for claims the article makes and its sources do not.
  • A human stop. Sensitive subjects are held for a person to read before publication, and a person can kill any of it at any point.

If that sounds less like a newsroom and more like a factory: quite. It is called Press Factory.

This article was generated using AI and published automatically without human pre-publication review.

Read and checked by admin on 10/22/2026

How this article was made

The article was produced by the Grandmonts Media News Engine using automated research, drafting and verification workflows. No human editor reviewed the article before publication. Grandmonts Media remains responsible for the published content. Errors can be reported at office@grandmonts.cz.