Technical performance is not the same as clinical readiness. Clinical AI Check independently examines how AI-supported healthcare workflows meet real clinical practice — before procurement, pilot, deployment or expansion.
The implementation gap
Clinical AI enters environments shaped by incomplete information, time pressure, changing patient conditions, professional judgement and organisational boundaries.
A technically capable system can therefore behave very differently once it meets actual clinical work. Performance is measured in the conditions of the evaluation. Safety is decided in the conditions of the ward.
The offer
Can we safely buy, pilot, deploy or expand this system?
An independent clinical assessment of a defined healthcare-AI use case, workflow or implementation decision. It is the work Clinical AI Check exists to do, and it carries the decision.
Output: assessment, priority risks, conditions for safer use and a decision-ready recommendation.
What Clinical Review coversWhere a review needs to be pressed harder, a narrower challenge-testing layer sits inside Clinical AI Check. Clinical Failure Test
Clinical Review · the primary engagement
Clinical Review examines whether the proposed use of AI is clinically defensible and sufficiently understood for its intended next step. Procurement, pilot, deployment and expansion all sit here.
Clinical relevance
Whether the intended use makes clinical sense.
Workflow fit
Whether the proposed use fits real clinical work.
Patient-safety exposure
Where the proposed use may create meaningful clinical risk.
Human oversight
Whether the proposed human control is realistic in practice.
Real-world use
Whether the intended use remains workable outside ideal conditions.
Readiness conditions
What should be clarified or strengthened before proceeding.
The same review logic across the lifecycle
Before procurement
Before committing to a system.
Before pilot
Before entering real care.
Before deployment
Before wider clinical use.
After material change
When the system or workflow changes.
Before expansion
Before use grows to new settings or workflows.
What this looks like in practice
An AI system detects that a patient is deteriorating. It is right, and it is early. The alert goes to the ward's shared tablet. The tablet is at the nurses' station, on charge. It is two in the morning, and both nurses on duty are in other rooms. The alert is seen at the morning handover. Six hours later.
No one made a mistake. The model was accurate and the staff were competent. The technology simply met a clinical workflow that differed from the assumed one. That is the kind of gap Clinical Review is designed to find.
Composite scenario based on recurring clinical workflow patterns. It does not describe an individual patient, organisation or product.
Review area · agentic AI
Agentic systems can interact with information, tools and workflows in ways that introduce new questions about autonomy, human oversight and clinical responsibility.
Clinical Review can assess whether that operating model is defensible in its intended clinical environment. Agentic AI remains part of Clinical Review; scope depends on the task, the degree of autonomy and the intended clinical environment.
Clinical Review output
You receive the decision-relevant findings. The review method itself stays internal.
Independent assessment
A structured clinical view of the proposed use.
Priority risks
The issues most relevant to the decision.
Conditions for safer use
Safeguards, limits or clarifications that may be required.
Human-oversight assessment
Whether the proposed control model is realistic.
Decision-ready report
A concise written basis for internal decision-making.
Recommendation
What should happen next.
Scope and fee
Scope can range from a single focused workflow to a wider pathway or implementation decision.
For healthcare organisations and AI companies deciding whether an AI-supported system should be bought, piloted, deployed, expanded or reassessed after material change.
Clinical Review
From SEK 60,000
Excluding VAT. Scope and price depend on clinical complexity and depth of review. Larger engagements are quoted separately.
Discuss your use caseWho it is for
Healthcare organisations
Independent scrutiny before buying, piloting, deploying or expanding healthcare AI.
AI and medtech companies
An independent clinical perspective before a product reaches real healthcare environments.
Innovation and implementation teams
External clinical scrutiny before implementation decisions become difficult to reverse.
A narrower layer within Clinical AI Check
Clinical Failure Test actively challenges a defined healthcare-AI workflow under difficult clinical conditions. It is a specialist challenge-testing product within Clinical AI Check: an add-on to a Clinical Review, a follow-up once something has already been identified, or a narrowly scoped standalone engagement where the question is genuinely only about failure.
Observed failures. Clinical consequences. Remediation priorities. Retest.
Explore Clinical Failure TestWhere it sits in the work
Clinical Review
The assessment that carries the decision.
Targeted Failure Test
Where the review found something worth pressing.
Remediation
Your work, on your priorities.
Retest
Whether the change held under the same conditions.
Later reassessment
After material change, or before expansion.
Independent clinical perspective
Clinical AI Check was created around a simple problem: technical performance does not automatically translate into safe or workable clinical performance.
The work is grounded in 27 years of clinical nursing experience and first-hand understanding of healthcare workflows, professional judgement, changing patient conditions and organisational constraints. The purpose is to bring clinical reality into AI evaluation early enough to influence the decision, the implementation or the product.
Aneth Olofsson
Registered nurse. Founder, Clinical AI Check.
Worth being clear about
Before procurement. Before pilot. Before deployment.
Describe the system, the context it will be used in, and what made you reach out now. How you frame the problem is itself useful information.
Independent clinical AI review and failure testing. Sweden and remote. Swedish or English.
