Evidence before assertion
The system must preserve what is known, what is missing and what requires human judgment before it makes a consequential claim.
Leadership
Founder & CEO · Aprentiz
Phil O’Brien
Building the evidence infrastructure that regulated organisations need before they can trust AI with consequential work.
The conviction
AI will reshape regulated work. Evidence will determine whether it deserves trust.
Phil founded Aprentiz around a practical observation: in high-stakes work, an answer is only useful when the organisation can understand what applies, inspect the evidence and account for the decision that follows.
That conviction drives a substantial regulatory-intelligence stack spanning source ingestion, local inference, hybrid retrieval, governed memory, evidence design and operating controls.
As project lead for Aprentiz’s UKRI AIRR work, Phil has directed controlled retrieval and domain-adaptation research on Isambard-AI, the UK’s national AI research resource.
How Aprentiz is led
A serious engineering culture for consequential systems.
Engineering before theatre
The work starts with identity, data boundaries, provenance, failure states and recovery—not a polished answer box.
Ambition with discipline
Aprentiz pursues difficult RegTech problems with controlled research, explicit gates and a refusal to overstate the result.
The work
One company, one accountable intelligence system.
Aprentiz joins regulatory knowledge, organisational context and engineering controls so that regulated teams can make progress without losing the thread of accountability.
Regulatory intelligence
Turning source material, applicability and evidence into a reviewable decision path.
Sovereign AI systems
Local-first intelligence architecture designed around controlled data boundaries.
Research-grade engineering
Using controlled evaluation and national-scale compute to improve the system without confusing research with product proof.
Start with the work
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