Generate safe EHR data at scale
Synthetic healthcare data with limitless possibilities
Generate Safe Synthetic Healthcare Data for Analytics, ML, and Software Development.
- Clinical Trials
Synthetic healthcare data can help in simulating patient data for clinical trials, facilitating more efficient initial testing phases and protocol development.
- EHR Data Analysis
Enable the safe analysis of electronic health records (EHR) by using synthetic patient data, maintaining patient privacy while extracting valuable insights for healthcare improvement.
- Personalized Treatment Plans
Develop personalized treatment plans using synthetic healthcare data that employs differential privacy, ensuring safe and privacy-preserving EHR data analysis.
- Software Development
Unlock data access for non-production environments increasing development cycles and productivity while eliminating sensitive data exposure.
Synthetic Healthcare Data for Training LLMs and Conversational AI
- Patient Interaction
Improve patient interaction bots through synthetic healthcare data, enhancing automated patient support and communication.
- Medical Consultation
Generate synthetic conversations for training AI in understanding diverse medical queries, supporting the development of AI-driven consultation systems.
Boost Model Robustness with Synthetic Healthcare Data
- Disease Prediction
Boost the accuracy and reliability of disease prediction models by integrating synthetic EHR data to cover a wide spectrum of patient conditions and histories.
- Healthcare Operations
Improve EHR data models that optimize hospital operations and resource allocation by incorporating synthetic patient data for varied scenarios and patient influxes.
The data bottleneck
- Biased datasets
EHR records are often imbalanced due to factors like social inequalities in healthcare and low adverse clinical outcomes.
- Sensitive patient records
Sensitive patient information is regulated and its use requires adherence to HIPAA, GDPR, and other privacy frameworks.
- Unavailable clinical records
Patient data is difficult to find for some medical conditions due to issues in reporting or infrequency of rare diseases.
Why synthetic data generation?
- Quality EHR records at scale
Backed by multiple generative AI models and proven across healthcare use cases, scale your data needs as required without compromising on quality or privacy.
- Mitigate regulatory risks
With tunable privacy filters and models built with differential privacy—complete with mathematical guarantees, rest assured EHR data is safe.
- Accelerate better clinical applications
Make your data asset safe and better so teams can stop worrying about data quality and access and focus on improving patient outcomes.
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