Generate safe EHR data at scale

Use synthetic electronic health records (EHR) data to accelerate the development of clinical applications while safeguarding patient privacy.

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.

EHR Challenge
The Healthcare Data Challenge

The data bottleneck

The healthcare industry is in the midst of digital transformation, with advanced data science and AI bringing new possibilities for improving patient care. However, working with EHR poses unique challenges relating to data privacy, data quality, and data availability.
  • 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.

The Solution

Power innovation with synthetic EHR data

Synthetic health data accelerates clinical research while protecting patient privacy by generating artificial records that resemble real EHR without including any actual patient information.

Organizations also generate synthetic data to augment AI training datasets by boosting low sample sizes, balancing between classes, filling in missing fields, and  simulating new examples for underrepresented medical conditions.

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Key Synthetic Healthcare Data Benefits

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.

Healthcare Resources

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