Expertise
Digital Assets, Tokenization & AI Agents
Digital assets are no longer an experiment: they are an operating layer for issuance, ownership and settlement. AI agents are becoming the same for operational work. My contribution sits between the two and the business around them: structuring the product, satisfying the regulator, and building the commercial engine that turns it into revenue.
Tokenization and real-world assets
Tokenization means representing an asset (equity, debt, a fund share, a physical product, a right) as a digital instrument that can be issued, transferred and settled programmatically. The technology is rarely the hard part. What decides whether a tokenized product works is the design around it: what exactly the token represents, who is legally obliged to honour it, how it is transferred between counterparties, and what happens when something goes wrong. I work on that design layer, and on the instruments, custody models and operational flows that make it usable for regulated counterparties.
Regulation as a product decision
Rules such as MiCA, FINMA, VARA, MAS, SFC and SEC frameworks are not paperwork to handle at the end of a build. They determine the structure of the product: which token is a security and which is not, what may be marketed to whom, what a custodian must hold separately, and how a stablecoin reserve or a payment flow has to be documented. I translate those requirements into product decisions early, so the business model does not have to be rebuilt six months later.
Stablecoins, payments and custody
A stablecoin or crypto payment flow only becomes a business when the money movement is reliable end to end: on-ramps and off-ramps, settlement, reconciliation, and clear responsibility for the assets while they are held. In practice this means selecting and integrating custodians, exchanges, liquidity providers and market makers, then writing down the commercial terms on which each of them participates. I have built and priced these structures for clients who had to answer to a regulator, a bank and a board at the same time.
AI agents in financial workflows
AI agents are moving from demos into operational work: research, monitoring, first-line client handling, document review, and the repetitive steps between systems that used to need a person. The commercial question is the same as with any new capability: where does it remove cost or add capacity, who is accountable for its output, and what does the customer actually pay for. I help teams answer that before they scale a pilot, and I connect it to the go-to-market work that makes it sellable.
Taking it to market
Strategy becomes a business through the unglamorous parts: a defined ideal customer, a price that holds up, a pipeline that can be forecast, and a sales motion a team can repeat without the founder in the room. I have done this from a standing start, hiring and leading the people who run it, and I still do it as an advisor when a leadership team needs an experienced pair of hands on the commercial side.
If any of this matches what you are working on, start a conversation. A short brief is enough: what you are building, where you are, and what you need next.