From charts to datasets. In minutes, not months.
Leverage AI-driven chart retrieval and key variable extraction to accelerate clinical research and reduce manual effort by over 80%.
Manual chart reviews are costly, slow, and unsustainable.
⤫ Hundreds of hours spent per study on manual abstraction
⤫ Unstructured notes and fragmented data slow down IRB approvals
⤫ High FTE cost per variable abstracted
⤫ Risk of inconsistency and bias across reviewer
AI-Powered Chart Abstraction + Dataset Creation at Scale
Our solution
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NLP-driven variable extraction from physician notes, labs, and imaging
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Automatic chart retrieval and deduplication
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Real-time structured dataset generation (CSV, FHIR, SQL-compatible)
Research audit trail + transparency layer. HIPAA-compliant + IRB-friendly (with built-in logging).
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Impact Metrics
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80%+
Reduction in abstraction time
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70%
Lower per-study data collection costs
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10x
Faster from cohort selection to analysis
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>95%
Validated accuracy vs manual reviewers
Ideal for:
Retrospective cohort studies
Multi-site registry creation
Health outcomes research
AI model training & validation datasets
Protocol feasibility and real-world evidence (RWE)
