Zavo
Zavo builds the data infrastructure for frontier medical AI, sourcing and structuring proprietary clinical datasets across 95+ medical specialties. The company provides expert annotation services, RL training environments grounded in real clinical workflows, and evaluation benchmarks to support the full model development lifecycle. Its network includes over 12,000 vetted healthcare professionals across North America and EMEA.
- Artificial Intelligence
- Healthcare Technology
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Frontier medical AI models require large volumes of high-quality, clinically grounded data and realistic training environments, yet such resources are fragmented, difficult to source, and often lack expert validation. Conventional public datasets fail to capture the breadth, depth, and longitudinal context needed to train and evaluate models for real-world clinical decision-making.
Solution
Zavo is a research lab building the complete data infrastructure for medical AI development. The company sources and structures proprietary clinical data—including structured EHR fields, imaging, genomics, clinical notes, and clinician-patient conversations—across 95+ medical specialties. Zavo pairs these datasets with expert annotation services, RL training environments grounded in real clinical workflows, and evaluation benchmarks that enable capability tracking and failure-mode identification. The platform supports the full lifecycle of model development, from data sourcing and structuring to training, evaluation, and iteration, giving AI teams the resources needed to build and validate medical intelligence at scale.
Target Audience
Primary customers are AI research labs, healthcare technology companies, and pharmaceutical or biotech organizations developing medical intelligence models that require clinical data, expert annotation, RL environments, and evaluation benchmarks.
Features
- Proprietary multimodal datasets combining EHR, imaging, genomics, clinical notes, audio, and medical conversations linked across the same patient journey
- Access to 95+ medical specialties and rare or specialised cohorts unavailable in conventional public datasets
- RL training environments structured around patient context, agent decision, and expert-defined feedback for measurable outcome evaluation
- Expert annotation and clinical evaluation services from a network of 12,000+ vetted medical professionals across North America and EMEA
- Benchmark suites for tracking model improvements, comparing versions, and identifying failure modes over time
- Data formats including DICOM, FHIR/HL7, structured EHR exports, whole-slide pathology, ICU waveforms, and surgical video