CERLAN Healthcare
Find the clinical failures your benchmarks may miss.
Independent expert evaluation for a defined healthcare AI workflow. We examine consequential failure cases before a release, pilot, or product expansion.
A focused evaluation scoped to your product, intended use, and next decision.
The evaluation gap
A passing benchmark can leave important questions open.
Healthcare AI teams need to understand how their product responds when context is incomplete, instructions conflict, or a plausible answer carries clinical consequences. CERLAN designs focused challenges around the workflow you are preparing to deploy and examines the failures that emerge.
The launch offering
Clinical AI Failure Audit
An independent, fixed-scope evaluation of a defined healthcare AI workflow.
What it does
Test the system against its intended use.
Together, we set the evaluation boundaries, test a frozen system version against challenging scenarios, and review the findings for their clinical significance.
When teams use it
Approaching a model release, health-system pilot, new agent deployment, specialty expansion, major update, or clinical-safety review.
What we evaluate
Questions that matter in use.
01 / CONTENT
Clinical content
Are important facts missing, misstated, or presented with unwarranted certainty?
02 / REASONING
Reasoning and recommendations
Does the response account for relevant risks, limitations, and escalation needs?
03 / BEHAVIOUR
Workflow behaviour
Does the system stay within its intended role when a request is ambiguous or outside scope?
04 / PATTERNS
Consistency
Do related cases reveal recurring failure patterns?
How it works
From intended use to reusable tests.
Define the workflow, users, intended use, and outcomes to examine.
Build product-specific cases that probe clinically consequential behaviour.
Run a frozen system version and obtain independent ratings.
Retain differences in reviewer judgment for analysis.
Escalate serious or disputed cases to expertise matched to the question.
Identify failure patterns and practical remediation priorities.
Turn selected cases into a private regression suite for the client.
What clients receive
Findings your team can act on.
The agreed scope determines the final package.
- Row-level evaluation dataset
- Severity and failure taxonomies
- Reviewer agreement analysis
- Adjudication log
- Prioritized remediation findings
- Executive findings report and discussion
- Private regression suite
Judgment and trust
A review process built around the question.
Expertise matched to the task
Clinical evaluation calls for different judgment at different stages. Depending on the workflow, reviews may involve physicians, residents, nurses, pharmacists, clinical researchers, coders, or other relevant specialists.
Review criteria are defined in advance. Independent ratings are retained, disagreement is examined, and consequential or disputed cases can be escalated for adjudication. No single reviewer is automatically treated as ground truth.
Set data boundaries before work begins
CERLAN starts with synthetic, public, client-generated, or appropriately de-identified material wherever possible. Before an engagement, we agree on the data to be used, who needs access, how findings will be shared, and the retention and deletion terms.
Please do not send identifiable patient information through the website or in an initial inquiry.
About CERLAN
Independent expert evaluation for high-stakes AI.
CERLAN is building independent expert evaluation for high-stakes AI, beginning with healthcare. Its first offering helps healthcare AI teams investigate clinically consequential failures in a specific product workflow and carry the resulting cases into future testing.
Founder
Pulkit Kumar
Pulkit holds an MSc in Surgery and has worked across medical research, clinical and global-health research coordination, and AI evaluation. He founded CERLAN to bring structured, independent judgment to healthcare AI evaluation.
Start a conversation
Preparing a release or pilot?
Tell us what your system does, what decision is coming up, and what you most need to learn from an independent evaluation.
Request a 20-minute conversationEmail [email protected]. Please leave patient information out of your first message.
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Privacy
Last updated September 24, 2026
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Contact
For privacy questions or requests, email [email protected].
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Terms of Use
Last updated September 24, 2026
Purpose of this site
This website provides general information about CERLAN and the Clinical AI Failure Audit. It is not medical advice, a clinical evaluation of any particular product, or a regulatory certification. Do not rely on it to make a patient-care decision.
Engagements
Submitting an inquiry does not create a client relationship or an agreement to perform an audit. Any engagement, scope, deliverables, confidentiality requirements, and data-handling terms must be agreed separately in writing.
Content and availability
We aim to keep the information on this site current, but may revise it or change the site without notice. You may share a link to the site; please do not reproduce its content or present it as your own. Any external links are provided for convenience and are governed by their respective sites.
Contact
Questions about these terms can be sent to [email protected].
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