Services

Clinical expertise for evaluation and data programmes.

From assessing a model’s clinical behaviour to building specialist reference datasets, we design and deliver work that helps healthcare AI teams develop, test and improve their products.

Medical imaging Clinical text, EHR & NLP Audio Video Other clinical media on request.

The methods and specialist team depend on the clinical task and intended use.

01

Clinical AI Evaluation

Understand performance where it matters clinically, including the nature and severity of errors.

  • Clinical review of model outputs for accuracy, appropriateness, safety, reasoning, uncertainty and escalation, as relevant to the use case.
  • Evaluation frameworks, scoring rubrics, error taxonomies and repeatable benchmark studies.
  • Preference ranking and clinician feedback for RLHF or other preference-based workflows.
  • Medical red-teaming, scenario design and analysis of failure modes.
  • Structured findings that can inform iteration and, where scoped, a validation plan.

Typical outputsScoring criteria, reviewed cases, preference pairs with rationale, severity-graded issues, benchmark reports and prioritised findings. The exact deliverables are set in the project brief.

Scope an evaluation
Clinical AI Evaluation
02

Specialist Clinical Annotation

Build dependable clinical datasets with specialists who understand the task and its downstream use.

  • Annotation strategy, criteria and platform/workflow selection or review.
  • Specialist recruitment and coordination, including geography or credentials where needed.
  • Delivery on your platform or infrastructure when appropriate.
  • Reviewer calibration, independent reads, QA, disagreement review, consensus or adjudication, as specified for the project.
  • Reference-standard and training annotation, with provenance and reporting shaped to your development or validation objectives.

Typical outputsAgreed protocol, structured labels, reviewer and decision provenance, quality summaries and project reporting. The exact design depends on the data and intended use.

Scope annotation
Specialist Clinical Annotation
03

Clinical Training Data

Generate and review clinical examples for model development.

  • Clinician-authored or clinician-reviewed questions and answers, case vignettes and task-specific examples.
  • Clinical reasoning and feedback in a format agreed with the AI team.
  • Iterative batches informed by observed model weaknesses where this is part of the brief.

Typical outputsStructured examples and review feedback aligned with an agreed schema and intended model workflow.

Scope training data
Clinical Training Data

How we engage

Built around your team and infrastructure.

We can help design the programme, select or configure an annotation or evaluation workflow, recruit and coordinate specialist clinicians, deliver on your platform, and manage calibration, QA, consensus and reporting. We align the work to your AI development or validation objectives. Where useful, PhD data scientists and AI engineers can work alongside your existing team rather than only handing over a dataset.

Discuss your project

Project brief

Tell us what you need to evaluate or build.

Share the clinical use case, modality, approximate volume and where you are in development. We will suggest a practical approach.

Scope a project