Dan Wagner has spent much of his career building businesses around technologies before they were widely understood. In the early 1980s, he digitized business information before the commercial internet existed. In the late 1990s, he built one of Europe’s early software-as-a-service commerce platforms, years before “cloud computing” became standard enterprise practice.
In 2016, well before generative artificial intelligence became a boardroom priority, he founded Rezolve Ai on the premise that commerce would eventually shift from static digital storefronts to systems driven by machine intelligence.
Now, as AI moves from experimentation to enterprise deployment, Wagner is leading a company that was designed for that transition long before it became fashionable.
Building Digital Information Before the Web
Wagner’s first major venture began with a practical frustration. In his early 20s, working at a London advertising agency, he found that gathering intelligence on clients and markets required physical library visits and manual clipping services. Information existed but access was fragmented and slow.
After seeing an early demonstration of networked computers communicating with one another, Wagner concluded that information retrieval could be systematized and delivered electronically.
He founded MAID – Market Analysis Information Database – in 1984, a time when the internet had not yet entered commercial use. The company digitized newspapers, trade publications and corporate reports into searchable electronic databases. Clients could access structured information remotely, a significant advance over paper archives and proprietary filing systems.
MAID expanded internationally and evolved into Dialog, which became one of the largest online business information services of its era. At its peak, the network served major corporations and financial institutions that relied on structured digital research long before web search made such access commonplace. Wagner was a pioneer in what would later be understood as digital knowledge infrastructure.
The theme of structuring information and reducing friction in access would recur throughout his career. Venda and the Early Days of SaaS Commerce By the late 1990s, Wagner saw a comparable inefficiency emerging in online retail. Companies building e-commerce sites were commissioning custom systems that were expensive to maintain and difficult to scale. Each retailer operated its own technology stack.
In 1998, Wagner founded Venda, building what would become one of Europe’s earliest multi-tenant SaaS commerce platforms. At the time, the concept of delivering enterprise software as a centrally managed, continuously updated service was not yet widely accepted.
Venda offered retailers shared infrastructure with centralized development, uptime reliability and global deployment capability. Among its clients were Lands’ End, Tesco, Boohoo, TJX Companies and Neiman Marcus.
The logic was straightforward: instead of each retailer building and maintaining its own commerce system, a common platform could serve many.
Venda was acquired by Oracle in 2014, reflecting the broader shift of enterprise software toward cloud-based models. The transaction marked Wagner’s second major bet on infrastructure proving commercially viable.
Attraqt and the Evolution of Search
In 2003, Wagner founded Attraqt, a company focused on on-site search, product discovery and digital merchandising. Attraqt addressed a persistent challenge in online retail: how to ensure that customers searching within a retailer’s website were presented with relevant results not merely keyword matches.
The company developed structured search and relevance technologies that predated today’s AI-driven personalization systems. It went public and was sold in 2019.
In December 2025, Rezolve Ai absorbed Attraqt, integrating its search and merchandising capabilities into Rezolve’s broader AI commerce architecture. The acquisition effectively reunited two strands of Wagner’s earlier work – structured relevance and enterprise commerce – under a machine-learning-driven framework.
Rezolve Ai: Founded Before the AI Boom
Rezolve Ai was founded in 2016 at a time when artificial intelligence was largely associated with predictive analytics and narrow machine-learning applications. Large language models were still largely experimental and generative AI had not entered mainstream business conversation. Wagner’s thesis was that digital commerce would eventually move beyond search boxes and static navigation. Instead of requiring customers to filter menus and specifications, systems would interpret intent conversationally.
Equally important, he believed that probabilistic AI systems would introduce a new category of risk in commercial environments.
“In creative applications, an error can be interesting,” Wagner says. “In commerce, an error can undermine trust immediately.”
From the outset, Rezolve was structured around reliability. The company developed brainpowa, its proprietary commerce-focused language model, trained on structured product data and governed by unique processes designed to reduce hallucination risk.
As generative AI entered the mainstream and concerns about hallucinations became widely discussed, Rezolve’s early emphasis on commercial control systems became central to its positioning. The company has secured patents around aspects of its architecture and transactional controls.
Rezolve’s focus has been less on conversational novelty and more on structured execution within regulated enterprise environments.
From Conversational Interface to Transactional Infrastructure
Wagner describes Rezolve’s approach as “agentic commerce,” a model in which AI does not merely recommend products but facilitates end-to-end transactions.
Traditional e-commerce relies on navigation hierarchies and keyword search. In Rezolve’s framework, a consumer might articulate a need, such as equipment suited for landscape photography and the system interprets context, evaluates available inventory, and narrows recommendations accordingly.
The goal is not simply personalization but transaction completion within governed parameters. Rezolve’s platform supports conversational product discovery, embedded checkout flows and enterprise compliance controls. The emphasis, Wagner says, is on replacing fragmented digital pathways with integrated systems capable of executing decisions.
Integrating Payments: RezolvePay
As Rezolve expanded its scope, Wagner concluded that conversational AI and payment execution could not remain separate layers.
The result is RezolvePay, an embedded payment and digital settlement capability integrated into the company’s AI transaction flows. RezolvePay allows merchants to process traditional card payments alongside digital asset rails including stablecoin settlement options.
The objective, according to Wagner, is operational cohesion rather than financial experimentation. “If the AI handles discovery and recommendation, it should also be able to complete the transaction,” he says. “Otherwise the experience fragments.”
By embedding payment functionality within conversational workflows, Rezolve seeks to consolidate intent, authorization and settlement within a single system.
A Public Company at an Inflection Point
Rezolve Ai is now publicly listed on Nasdaq and positioned at the intersection of enterprise AI, commerce modernization and embedded payments.
Its strategic priorities include scaling deployments of its AI commerce systems, expanding RezolvePay integrations and deepening partnerships across retail and financial services.
Wagner’s career has included significant reversals as well as exits. After a previous venture was derailed by a hostile takeover, he began building Rezolve in his early fifties. The decision to start again, this time with a focus on long-term architectural discipline, reflected what he describes as a preference for structural businesses over cyclical ones.
Across MAID, Venda, Attraqt and Rezolve, the connection is clear: information becomes infrastructure; infrastructure becomes platform; platform becomes ecosystem.
Wagner does not frame his work as disruption for its own sake. Instead, he argues that each major technological shift eventually consolidates into foundational systems.
“Every technology cycle matures,” he says. “The companies that endure are the ones that build the rails.”
If artificial intelligence is moving from experiment to enterprise utility, Rezolve’s wager is that commerce will be one of the sectors to institutionalize it. For Wagner, the pattern is familiar: identify the structural gap, build the infrastructure and allow the market cycle to validate the thesis.
