Artificial intelligence has become a default talking point in financial crime compliance. Yet for many regulated firms, particularly those operating across capital markets, payments, and treasury functions, the challenge is no longer whether AI can be used, but whether it can be deployed in a way regulators will accept. For Vivox AI, a young company that has already secured live production deployments across multiple jurisdictions, that distinction has shaped both its technology and its early market traction.
Vivox is led by CEO and co-founder Tim Khamzin, whose background sits firmly in large-scale bank operations rather than Silicon Valley experimentation. Before founding the company, Khamzin spent years automating back-office functions at major financial institutions, including one programme that reduced headcount from 24,000 to under 6,000 in four years. That experience informs Vivox’s focus today. “We are focused on automating manual repetitive tasks done by first line of defence compliance analysts,” he says, “but in a way that is going to be finally accepted by regulators.”In conversation with RegTech Insight, Khamzin explains the immediate demand being addressed is fast-growing FinTechs, payments firms and digital banks that cannot scale compliance teams at the pace regulation requires. Hiring dozens of analysts is difficult, even where budgets allow. Vivox’s proposition is to augment the capacities of a small number of expert practitioners with AI agents to support onboarding and monitoring at scale.
Vivox is live in company onboarding, enhanced due diligence for medium- and high-risk customers, sanctions screening, adverse media monitoring, and false-positive reduction. Khamzin points to one UK bank employing around 500 people to handle adverse media alerts alone. “It’s a massive story,” he says, and one where efficiency gains are well proven.
Atomic Workflow Automation
What differentiates Vivox from many AI-driven compliance tools is not the ambition to automate, but how that automation is structured. The company has built its platform around what Khamzin describes as “atomic steps.” Instead of applying AI to a complete end-to-end process, Vivox breaks workflows down into discrete human actions and automates each one separately. “The probability to make a mistake for atomic human action while you’re automating it is much lower than if you wanted to automate a big process,” he says.
He offers a practical example from nature-of-business verification. Rather than relying on a large language model to summarise a company website, Vivox mirrors how a human analyst would work. The system identifies the website, checks terms and conditions, validates the legal entity name, captures timestamped screenshots, and reviews product pages before forming a conclusion. Each step is logged and can be replayed for auditors or supervisors. “It’s complicated in terms of IT and tech, but it’s explainable,” he explains.This design choice is driven by regulatory expectations. “From a regulator’s point of view, they will not accept a decision if you can’t demonstrate how the decision was made,” he said, contrasting Vivox’s approach with black-box summarisation tools that produce different answers to the same question. Several Vivox customers, have already passed independent audits using this model.
Human in the Loop
Human oversight remains central. Vivox embeds human-in-the-loop controls through scoring mechanisms, feedback comments, and thresholds that must be met before a workflow moves into production. Analysts can approve or reject outputs and explain why. That feedback is retained and used to refine the system for that specific customer. “It actually acts as a junior compliance analyst,” Khamzin said, trained by senior staff during early deployment.
Ultimate beneficial ownership remains one of the most difficult areas in financial crime, and Vivox does not claim to solve it universally. The platform aggregates global corporate registries, maps customer-provided information, and applies open-source intelligence research where digital sources exist. Where an authoritative source can’t be found, the system records that absence rather than inferring an answer. “We just need to clarify, we couldn’t find any data,” Khamzin said, and document the limitation.
Although Vivox’s early traction has been strongest in payments and cross-border FinTechs, capital markets and investment use cases are already emerging. Asset managers and investors are using the platform to screen potential investments, including checks on founders and executives. Khamzin described an example where the platform identified a company founder previously involved in fraud who had changed his name. The change was detected across public digital records, including LinkedIn profile history. The system surfaces and timestamps such changes as part of the screening output for investors.
Rapid Adoption
The company’s footprint has expanded quickly since its launch in 2024. Vivox is live across around 100 countries, working with a large global payments infrastructure provider and customers in the UK, Ireland, Switzerland, Singapore, and the US. Several implementations have been reviewed through independent audits, including under Swiss regulatory scrutiny – “They’re quite tough,” Khamzin notes.
Geography shapes the go-to-market strategy. Vivox doubles down where it gains traction, rather than pursuing broad coverage from day one. Ireland, the UK, and Switzerland are current focus areas, with US expansion under exploration following early customer wins.
Looking ahead, Vivox is positioning governance as a differentiator rather than a constraint. The company is bringing former senior regulators and central banking figures into advisory roles to reinforce its regulator-first stance. “You can implement AI by yourself,” Khamzin said, “but if you’re going to do it in a safe way, there are no shortcuts.”
AI in financial crime is less about disruption than discipline. In capital markets and treasury environments, auditability is non-negotiable. This disciplines approach may explain why Vivox has moved from pilot to production faster than many of its peers.
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