Manual data extraction is time-consuming
Teams rely on manual efforts to extract and curate structured information from clinical records.
Clinical data is valuable but underutilized
Research funding is declining, yet clinical data remains a valuable asset that is not fully leveraged.
Data is difficult to trust and reuse
Unstructured formats and inconsistencies make it hard to validate and apply data across use cases.
Access to data remains a bottleneck
Teams struggle to access the right data efficiently, slowing down research, operations, and decision-making.
Our Solution
Nimblemind uses specialty-trained agents to extract, standardize, and organize clinical data into consistent datasets.
1
Extract clinical information
Identify and capture key concepts such as entities, events, attributes, and relationships from unstructured data.
3
Enable access and reuse
Ensure data is consistent, trusted, and reusable across teams, studies, and workflows.
Faster time to first dataset
Generate structured, analysis-ready datasets in weeks instead of months, accelerating research timelines and operational workflows.
Increased research throughput
Support more studies and initiatives per quarter without increasing team size by removing data preparation bottlenecks.
Improved compliance posture
Reduce uncontrolled PHI duplication and improve auditability through structured, governed data workflows.
“By organizing and curating data from our EMR, patient surveys, and wearable devices, they are helping us identify patient interventions more effectively. This kind of AI-driven insight is the future of personalized, proactive care.”
Lynn M. Madden, PhD - CEO of APT Foundation
Palliative Care Speciality
Upload electronic health records, assessments, notes, and more without formatting steps. Nimblemind structures, labels, and prepares datasets automatically, then exports directly into your workflow.
Reduce prep time
Go from raw files to labeled corpuses in hours using built-in automation
Keep governance tight
Assign and revoke access by role or study with built-in audit logs
Ophthalmology
Works with fundus imaging and clinical notes to generate consistent datasets for severity scoring, analysis, and clinical workflows.
Gastroenterology
Handles endoscopy video and clinical context to produce usable datasets for detection, evaluation, and downstream analysis.
Radiology
Supports radiology imaging across sources and formats, making it usable for analytics and model development.
Anatomical Pathology
Works with high-resolution pathology images to create structured datasets for analysis and deployment.
Nimblemind is built to process the full range of clinical data used in care delivery.
Data Type
Examples
EMRs and Clinical Notes
Diagnoses, symptom logs, palliative consult notes
Patient-Reported Outcomes
Pain scores, fatigue levels, depression scales
Medication Data
Opioid dosing schedules, PRN usage, deprescribing notes
Lab Results
Kidney function, liver enzymes, inflammatory markers
Functional Assessments
ADLs, ECOG performance status, mobility notes
Social Determinants
Caregiver availability, home environment, support systems
Speech and Audio Data
Voice samples for symptom expression, comfort assessments
Nutrition and Dietary Logs
Intake records, feeding tube data, weight loss trends
Care Planning Documents
Interdisciplinary team notes, hospice eligibility forms
