Multimodal medical imaging, AI-ready. Algorithms and agents, on the same foundation.
Shipping today: training-grade multimodal medical imaging cohorts, delivered on request. The same foundation powers our work on validated algorithms and agentic systems.
One foundation, three layers: data, models, agents.
We ship datasets today. Algorithms and agents are on the same data foundation, and arrive when partners are ready to build them with us.
Custom multimodal imaging cohorts
De-identified imaging volumes paired with structured reports, expert annotations, region grounding, and longitudinal context — already aligned across modalities and evaluated against expert ground truth. Custom cohorts assembled on request for foundation-model teams, pharma R&D, and research labs.
- In-house de-identification across DICOM, reports, and metadata
- Expert radiologist annotation, with QA and inter-rater review
- Synthetic generation for rare findings and edge cases
- Multimodal alignment and active-learning auto-labels
- Versioned releases with provenance, evaluation harness, and license terms
Medical-report data and linkage
Free-text radiology and clinical reports structured into linked signals — findings, impressions, regions, and longitudinal context — paired with the imaging they describe.
- Findings and impressions extraction
- Linkage to studies, series, slices, and regions
- Cohort-level evaluation against expert annotation
Multimodal imaging algorithms
Models that see imaging and read reports together — joint representations, region-grounded retrieval, and disease-specific algorithms. Built on the platform’s trusted-data and multimodal-alignment layers, evaluated against expert ground truth before release.
- Image–text joint embeddings
- Region-grounded evaluation
- Cross-modal retrieval and QA
Agentic workflows for imaging AI
Agentic systems for retrieval, reasoning, and quality assurance across imaging and reports — built for research and AI teams, with expert review in the loop. Same data and evaluation foundation as the rest of the platform.
- Retrieval and reasoning over images and reports
- Cohort and dataset construction with expert-in-the-loop
- Annotation QA and evaluation orchestration
Customers and partners across imaging AI.
Foundation-model teams, pharma R&D, and applied AI groups come to us for training-scale multimodal imaging. Hospitals, academic medical centers, and research labs partner with us on data, clinical context, and validation. The same platform foundation serves both.
Foundation-model labs
Foundation-model and applied AI teams building health AI — who need de-identified, expertly-annotated medical imaging at training scale.
Pharma & life sciences
Imaging biomarker, trial-imaging, and translational research teams working across studies, modalities, and disease areas.
Research labs
Academic and translational groups building cohorts, training models, and publishing on multimodal medical data.
Clinical & enterprise IT
Hospitals and imaging informatics teams partnering on data, security, and governance — with algorithms and agents on the roadmap.