Case StudiesMulti-state hospital chain
Medical annotation · 12K studies / week

Radiology annotation, clinical-grade.

Multi-rater pipeline for chest CT and MRI knee studies. 98.4% IAA, 12K studies / week, with two clinical reviewers in the loop.

AI training data is only useful if a radiologist would sign their name to it. We built the pipeline that lets them — multi-rater consensus, clinical reviewer escalation, RAGAS-style quality checks on every batch.

The headline
12K
images / week
Profile
  • ClientMulti-state hospital chain
  • PillarB2B Operations
  • IndustryHealthcare
12K
studies / week
98.4%
inter-annotator agreement
2
clinical reviewers in-loop
ABDM
+ HIPAA aligned
⌖ The brief

What they asked for.

Stand up a clinical-grade annotation pipeline for chest CT and MRI knee studies — high enough IAA that the hospital's AI team will train production models on the output, with audit trails the compliance team will sign off on.

▣ How we approached it

The approach.

01

Multi-rater consensus

Three independent annotators per study, model-assisted convergence, escalation to clinical reviewer on disagreement.

02

Clinical-reviewer QA

Senior radiologists review flagged disagreements and a sampling of consensus cases — IAA tracked weekly.

03

RAGAS-style quality

Faithfulness, agreement, edge-case coverage scored on every batch. Regressions block release to the AI team.

04

Compliance posture

ABDM linkage where applicable, HIPAA for export-facing teams. PHI de-identified end-to-end.

◇ What we shipped

Deliverables.

Annotation tooling

Web-based viewer, multi-rater workflows, escalation queues.

Quality dashboard

Per-batch IAA, edge-case tracking, throughput, SLA metrics.

Compliance pipeline

PHI de-identification, audit logs, evidence packs.

AI-team handoff

Versioned datasets, schema docs, sample notebooks.

↑ Outcomes

The numbers.

98.4%
IAA on chest CT
12K
studies / week
0
PHI escapes
Now booking Q3 2026

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shipped projects
12
industries
ISO 9001:2015
certified
98.4%
CSAT