Real-world validation.
Real-time trust.
Healthcare AI, verified.
We provide the verifiable Human-in-the-Loop infrastructure to ensure AI models meet expert-reviewed quality standards before clinical deployment.
The high cost of unvalidated AI
Models deployed without sufficient expert review create a dangerous gap between technical capabilities and clinical safety requirements.
Unsafe recommendations
Unvalidated AI models can provide clinically inappropriate guidance.
Patient harm
Incorrect AI outputs risk patient safety and treatment outcomes.
Legal exposure
Organizations face liability without proper AI validation frameworks.
Loss of trust
Clinicians and patients lose confidence in AI-driven healthcare.
The new standard in clinical AI validation
We have combined rigorous HITL testing with a global clinician network to build the adjudication layer for the next generation of healthcare AI.
Clinician expertise, at scale
7,500+ clinicians contributing to AI evaluation
The clinical adjudication layer
Human-in-the-loop evaluation for medical AI
Our Human-in-the-Loop system captures the reasoning of top medical experts, creating the ground-truth data needed to train the automated AI judges of tomorrow.
Our foundation isn’t just code. For years, iCliniq has been a global ecosystem of care, serving over 8 million patients.
We applied the same rigorous accountability from our clinical operations to our internal AI tools. We realized that traditional evaluation methods failed to capture the unique interdependence of accuracy, safety, and empathy required in medicine.
Use cases
Clinical Utility
Measure whether your model is clinically useful-not just correct.
Modern LLMs may provide technically correct answers but still lack actionability, clinical nuance, or safe recommendations. Perpendicular AI evaluates clinical utility using both gold-standard benchmarks and physician review, depending on the product.
What we measure
Where this matters
Preferred Response
Ensure your model expresses the right answer in the right way.
Healthcare requires not only correctness but also the preferred style of communication for clinicians, patients, or internal workflows.
What we measure
Where this matters
Chain of Thought Evaluation
Assess reasoning quality-without revealing sensitive internal reasoning to users.
Many healthcare tasks depend on structured reasoning: differential diagnosis, treatment justification, rule-out logic, and stepwise problem solving.
What we measure
Where this matters
Citations & Evidence Alignment
Evaluate citation correctness + evidence grounded-ness.
In healthcare, unsupported claims pose real risk. Perpendicular AI evaluates whether outputs are factually linked to reputable evidence sources and whether citations are: Correct, Relevant, Non-hallucinated, Consistent with the clinical answer
What we measure
Where this matters
Imaging Response Evaluation
Evaluate multimodal model reasoning with radiology, pathology, dermatology, and other clinical images.
As models expand into image modalities, evaluation must measure diagnostic quality, finding recognition, and risk detection.
What we measure
Where this matters
Retrieval-Augmented Generation (RAG) Evaluation
Evaluate the full RAG pipeline-retrieval quality, grounding, and final answer accuracy.
For healthcare, the retrieval component can make or break safety. We provide RAG-specific evaluation metrics to assess how well sources are fetched, grounded, and cited.
What we measure
Where this matters
11-axis evaluation framework
We transform AI evaluation from a single metric to a comprehensive assessment of clinical viability using a proprietary framework.
Real-world scenarios
High-fidelity workflows drawn from millions of consultations.
Hybrid scoring
Integrating automated metrics (BERT, ICC) with HITL judgment.
Expert adjudication
Continuous oversight by Medical Review Board.
Risk & compliance
Dedicated bias checks aligned with HIPAA/GDPR.
Pricing
Get a tailored enterprise quote built to match your model’s needs, evaluation depth, and delivery timelines.
Frequently asked questions
How do you verify that your clinicians are real and qualified?
Every clinician undergoes identity and credential verification, with licenses checked against national medical boards.
How long does an evaluation take?
Most evaluations are completed within 5-7 business days, depending on volume and complexity.
Is my model data kept private and secure?
Yes, all data is encrypted in transit and at rest. We comply with HIPAA and GDPR for data handling.