Our Platform
Nimblemind automates ingestion, labeling, and governance to deliver structured, high-quality datasets from EMRs, imaging, wearables, and more.
Go from Data → Outcomes → Evidence
Curate training data sets across most clinical data types
Eliminate manual effort to edge cases
Reusable agent infrastructure and harness
Apply the same integrations across multiple specialties and use cases
We used to spend more time curating data than building models.
“Nimblemind flipped that ratio. It’s now the first step in our AI pipeline.”
— ML Lead, Health AI Startup
We were drowning in unstructured notes and couldn’t move forward on our readmission model
“Nimblemind gave us a labeled, high-quality dataset in under a month—and it actually reflected real clinical nuance. That would’ve taken our team 6 months, minimum.”
— Senior Clinician, Academic Medical Center
Multimodal Ingestion
Support for diverse clinical formats
Unified pipelines across specialties
No manual uploads or fragile scripts
AI Automated Labeling and Structuring
Built-in clinical annotation pipelines
Active learning with domain-specific models
Transparent and adaptable workflows
Governance and Access Control
Study-based access with user roles
Time-limited and auditable
Compliant collaboration at scale
AI Automated Labeling and Structuring
Schema-consistent datasets
Flexible export destinations
Versioned and traceable outputs
How it works
Nimblemind replaces brittle point tools and fragmented tools with a single platform:
1
Connect your sources
EMRs, imaging, labs, surveys, and notes
3
Configure access and permissions
Set user roles, study durations, and audit settings
Structured and unstructured inputs
Including EMRs, imaging, wearables, genomics, labs, and free-text notes
Used by AI teams, researchers, and care providers
Deployed in opioid treatment studies, geriatrics, GI, palliative care, and more
Supports both research and operational use
Trusted by teams working in academic, clinical, and commercial AI
