Sanctuary Health Manifesto

May 15, 2026

Healthcare should be abundant. There is no law of nature that says a person in the UK should wait eighteen months for surgery. These are not inevitable features of modern life. They are symptoms of systems that have become so burdened by their own complexity that they can no longer do the thing they were built to do: deliver care.

We started Sanctuary because we believe AI can change this. Not by adding another layer of technology to an already overstretched system, but by relieving it of the administrative weight that prevents it from functioning. We call this healthcare abundance.

To explain why we believe this, and why now, it helps to first understand what went wrong.

Diagnosis: Compounding Complexity

Healthcare is a system constrained by complexity. Not complexity that is unavoidable, but complexity that has compounded over time through well-intentioned intervention.

Roughly every five years, successive UK governments repeat a familiar cycle: consult the civil service to identify the system's main problems; receive a set of diagnoses, often accurate in isolation; design new plans, targets, incentives, and structures to address them; implement reforms over the course of a parliamentary term; then abandon or supersede them when the next government arrives. The process restarts.

Viewed in isolation, each intervention appears reasonable. The people in Westminster are motivated by genuine failures, and they are designing their interventions with good intentions. The problem lies not in any single reform, but in what happens when they accumulate.

Healthcare is inherently complex because people are complex. The system manages human health – a biological and social phenomenon of extraordinary intricacy – under conditions where the worst-case outcome is death. This creates a profound asymmetry of risk: the cost of getting things wrong is morally, politically, and emotionally intolerable.

This asymmetry causes a deep aversion to failure. In response, politicians and bureaucrats attempt to bound risk through rules, regulations, targets, and oversight. The system increasingly seeks to abstract away uncertainty by codifying behaviour however they can: specifying processes, defining acceptable actions, and reducing discretion wherever possible.

The NHS is not failing despite increasing regulation and oversight, but partly because of it. In complex systems, each attempt to reduce risk or impose control increases systemic complexity, which in turn generates new failures that demand further intervention. The result is a self-reinforcing cycle: management replaces judgement, bureaucracy replaces care, and stability is purchased at the cost of adaptability.

Processes only ever accumulate. The system is structurally biased toward invisible failure – slow deterioration, rationing, delay – over visible failure, where a specific identifiable error is caused by a specific, identifiable change. No one is fired for the ten-thousandth patient who waited eighteen months for surgery. But someone is fired when a new policy causes a single, traceable death.

Misallocated Supply

The resulting problem from years of compounding regulation and complexity is that a huge % of the supply of healthcare is misallocated towards low-productivity work. While we were working in a GP practice in Manchester, we saw patient files transferred between clinics via a mailbag. It was one of the admin team's jobs to then scan the documents and create a new patient record at that practice.

Another doctor I spoke with said that when planning surgery, he would order the equipment he needed weeks in advance. Then, when arriving in the operating room, about 40% of the requested equipment would be present. The solution to this was to send a junior doctor running around the hospital, collating the necessary equipment.

Finally, the referral process between primary and secondary care, at least in the UK, can only be described as Chinese whispers with different doctors and administrative staff shuffling documents through digital equivalents of air tubes in the hope that something would be done on the other end.

All of this represents a misallocation of resources. Too many well-trained and high-value people are oriented toward doing low-value, burdensome work.

AI Will Increase the Supply of Healthcare

Our core belief is that AI can relieve healthcare of its administrative burden and, in doing so, allow the system to actually deliver care. This is what we call healthcare abundance.

When we have observed the healthcare system up close, we have consistently been struck by human ingenuity. People are the glue that keeps these broken systems working. They improvise, adapt, and compensate for institutional failure every single day. For the first time in history, technology can begin to replicate that ingenuity at scale.

Why Now Is Different

Historically, software has forced conformity onto healthcare. Entrepreneurs and engineers would observe similar but subtly different clinical processes and build a single product to sell across the sector. The product would be good enough at solving a problem that it was worth buying, but it would force doctors, nurses, and patients to conform to what the software company had built.

The world's biggest EHR, Epic, brings genuine benefits: data centralisation, security, patient record access. But it also forces clinicians into doing a thousand things they didn't sign up for, navigating a platform full of features they don't want or need. The result is feature and process bloat that makes the software more confusing than helpful.

This was healthcare SaaS, and it was the only way. The cost of engineers and writing code meant it was not feasible to customise or build bespoke solutions for each clinical context. The trade-off — generic software imposed on heterogeneous reality — was accepted as inevitable.

That is no longer true, for two reasons.

First, the cost of writing and deploying code is collapsing. Deploying and iterating tailored systems across many local contexts was once economically prohibitive but is now within reach. This does not eliminate complexity, but it makes it workable. It allows technology to conform to clinical reality, rather than forcing clinical work to conform to technology.

Second, AI agents can meaningfully increase healthcare supply. Agents represent the first technology that can truly imitate the ingenuity of human beings. It is not unimaginable that a series of AI agents could complete the core administrative tasks that clinicians and staff are currently burdened with – booking, referral management, documentation, equipment coordination, coding, and reimbursement.

Our hope is that as efficiency improves in non-clinical domains, the freed capacity is not simply absorbed by more volume, but reinvested in clinical domains. Longer consultations. Better continuity. More humane care. Outcomes that scarcity has progressively eroded.

For the first time since the invention of modern computing, it is possible to write, deploy, and scale customised software in healthcare – software that can run agents and models capable of completing a wide variety of historically human tasks, the way humans would. If we can aggressively deploy this model, we can move toward a world of abundant healthcare.

Sanctuary's Mission

We will unlock an era of abundant healthcare with AI.

We will achieve this by putting engineers where the problems are. Not in an office designing software for clinicians, but inside clinical settings, watching, learning, and building alongside the people who hold the system together every day. We will focus on the most difficult and highest-value problems we can find.

From there, we will build customised software solutions capable of handling the context dependencies and heterogeneous reality of modern healthcare. Over time, we will develop a core capability set that allows us to scale more efficiently without sacrificing the specificity that makes our solutions effective.

Where This Leads

We believe this method will compound into something greater than the sum of its parts. We are deliberately not prescribing a fixed product roadmap. The companies that have built the most enduring enterprise infrastructure did so by deploying into the hardest environments they could find, discovering that the same structural problem appeared everywhere, and building the platform that solved it — Palantir primary among them, despite their current unpopularity in the UK. We believe we will discover something analogous: the absence of an orchestration layer capable of turning clinical intent into coordinated action across a fragmented system.

Each deployment teaches us where the system breaks. Each solution we build captures data — about communications, referrals, diagnostics, clinical decisions — that has never been structured before. Over time, these accumulate into new data ontologies upon which AI agents can operate and in doing so, we build a new operating system for healthcare.

As I look forward, it is not inconceivable that Sanctuary one day owns and operates a hospital that can deliver care at a lower cost per patient than any NHS trust. We will pioneer a new model of healthcare, one that has AI at its center and allows humans to focus on what they do best: caring for their fellow humans.

Fixing Healthcare

For too long, healthcare professionals have carried the burden of a failing system through personal sacrifice, improvisation, and exhaustion. Patients have been asked to accept delay, fragmentation, and indignity as unavoidable.

Neither is acceptable, and neither is inevitable.

If we can fix healthcare, then we must. Not because it represents a compelling business opportunity, but because the cost of inaction is measured in harm that could have been avoided. The moment calls not for another review or reform cycle, but for the willingness to build the future we want: a world with abundant healthcare.