Emerging Technology
The technologies we work around, and how we work around them.
We work on emerging technology as an adoption problem: strategy, market intelligence, partnerships, ecosystem development and venture creation. Not as an engineering problem.
That distinction matters, so it is stated plainly on this page rather than left for you to discover in a meeting.
Our position
What do we actually do with these technologies?
Strategy, adoption, market intelligence, partnerships, ecosystem development and venture creation. We help organisations decide what a technology means for them, design the experiments that produce evidence, find and qualify the external teams with the relevant capability, and build the commercial and ecosystem layer around it.
We do not present ourselves as a deep technical engineering firm. Where a venture or a pilot needs engineering, we work with specialist technical partners and say so.
How do we choose what to work on?
We work where a technology is real enough to build on and unresolved enough that adoption is still being decided. Too early and there is nothing to decide; too settled and the interesting work has already happened.
In practice that has meant artificial intelligence, digital assets and tokenisation, trust and digital identity, and the financial infrastructure connecting traditional and on-chain environments.
Areas
Where we work.
Artificial intelligence
Adoption strategy at workflow level: which work an organisation should change, how the output gets verified, what it is measured against, and the operating model that keeps the gain after the pilot team leaves.
AI agents
The harder question of allowing a system to act rather than to produce. Permissions, boundaries, reversibility, logging and where an agent belongs in a process that already has accountability attached.
Digital assets
Strategy for organisations moving into digital assets: what the instrument is, who the counterparties are, what infrastructure it depends on, and what has to be true for institutions to participate.
Blockchain and Web3
Where a shared ledger genuinely changes what is possible, and where it is an expensive answer to a question a database already answers. We are useful mainly because we will say which.
Tokenisation
Tokenised assets and instruments as a distribution and market-structure question: who issues, who holds, who services, and where demand actually comes from.
On-chain infrastructure
The rails beneath the applications - settlement, custody, compliance, identity and interoperability - and the businesses being built on them.
Digital identity
Verification, credentials, provenance and owner-controlled information as the foundation for services that currently cannot exist because trust cannot be established cheaply.
Fintech
Payments, treasury and financial operations where traditional and digital-asset environments now have to work as one system.
Emerging technology infrastructure
Standards, rails, data layers and interoperability - the layers that quietly decide which applications become viable.
How we work with them
Five kinds of work.
Strategy and adoption
Deciding what a technology means for an organisation, and designing the work that produces the evidence.
Market intelligence
Reading where demand is forming, who is credible, what is structurally blocked and what has actually changed.
Ecosystem development
Scouting, matchmaking, partnerships and programmes that connect capability to the organisations that need it.
Venture creation
Building new companies where a technology has opened a problem worth solving commercially.
Partnerships and go-to-market
The commercial layer: positioning, first customers, distribution and the partnerships that make adoption possible.
Common questions
Working across emerging technology.
Does Subirachs Ventures build technology?
Product definition, architecture decisions and delivery management sit with the platform. Deep technical engineering is delivered through specialist technical partners selected for each project. The platform's own capability is in strategy, adoption, market intelligence, partnerships, ecosystem development and venture creation.
How do you approach AI adoption differently?
By scoping to workflows rather than functions, and by treating verification as the binding constraint. If the person accountable for an output cannot check it quickly and cheaply, adoption does not hold regardless of model quality. That single test changes which projects get started.
Is blockchain still relevant to corporate innovation?
In specific places: tokenised instruments, settlement and custody infrastructure, provenance, and identity or credential systems where multiple parties need a shared record they do not have to trust each other to maintain. In most other cases an existing system is the better answer, and we will say so.
Which regions do you cover?
Presence across New York, Barcelona and Dubai, with global operating reach - which in practice means North American capital markets, European startup ecosystems and programmes, and Gulf, wider MENA and Asian institutional markets.
A technology on the table, and no decision yet?
That is the usual starting point, and it is a good one.