Key Challenges
Data Privacy & Compliance
Healthcare data is tightly regulated (HIPAA, GDPR, HITRUST). Sharing real EMRs and clinical data is risky and often prohibited.
Data Scarcity & Bias
Rare diseases, underrepresented demographics, and long-tail medical cases are difficult and costly to collect, leading to biased and incomplete datasets.
High Costs & Long Timelines
Clinical trial data, medical imaging, and labeled EMRs take months or years to acquire—slowing down drug discovery and AI development.
Integration Barriers
Legacy EHR systems, siloed datasets, and strict IT environments make it difficult for startups and vendors to experiment and deploy safely.
Our Solutions
Synthetic EMRs & Clinical Records
Generate lifelike but fully PHI-free patient records, enabling safe model training and collaboration.
Clinical Trial Simulation & Augmentation
Fill gaps in trial data with synthetic cohorts—simulate rare conditions, diverse demographics, and adverse events.
PHI-Safe Model Training & Evaluation
Replace sensitive identifiers with synthetic variants, enabling cloud-based testing, debugging, and safe POCs.
Bias Mitigation & Edge Case Coverage
Balance datasets across age groups, conditions, and populations to build fairer, more robust models.
Seamless Integration
Legacy EHR systems, siloed datasets, and strict IT environments make it difficult for startups and vendors to experiment and deploy safely.
Use Cases
Triage & Diagnostics
Synthetic ER visit data trains AI systems to prioritize urgent cases and assist clinicians in real time
Drug Research & Discovery
Simulate disease progression and treatment outcomes to speed up drug testing and reduce trial costs
Clinical Trials
Enhance study designs by generating synthetic control groups or extending rare-patient cohorts
Medical AI Agents
Train conversational healthcare agents and insurance workflow AI with PHI-safe synthetic transcripts and notes
Synthetic EMRs & Clinical Records
Generate lifelike but fully PHI-free patient records, enabling safe model training and collaboration.
Our Solutions
Clinical Trial Simulation & Augmentation
Fill gaps in trial data with synthetic cohorts—simulate rare conditions, diverse demographics, and adverse events.
PHI-Safe Model Training & Evaluation
Replace sensitive identifiers with synthetic variants, enabling cloud-based testing, debugging, and safe POCs.
Bias Mitigation & Edge Case Coverage
Balance datasets across age groups, conditions, and populations to build fairer, more robust models.
Seamless Integration
APIs and connectors slot into existing research, trial, and hospital IT pipelines for fast adoption.
Key Benefits
Accelerated Innovation
Cut months from model development by removing data bottlenecks
Regulatory Peace of Mind
Synthetic datasets are fully compliant with HIPAA, GDPR, and HITRUST
Cost Efficiency
Reduce reliance on expensive patient recruitment and manual labeling
Fair & Inclusive Models
Correct imbalances in datasets for more equitable healthcare outcomes
Collaboration Without Risk
Share synthetic datasets across teams, institutions, and vendors without exposing PHI
Future-Proof AI
Enable continuous retraining and drift management with scalable synthetic pipelines
Ready to Get Started?
Contact our team to learn how we can help your healthcare and life sciences organization develop AI systems that meet the highest standards.
"We strive to start each relationship with establishing trust and building a long-term partnership. That is why, we offer a complimentary dataset to all our customers to help them get started."
Puneet Anand
CEO DataFramer
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Privacy-Preserving AI for Healthcare & Life Sciences
Bridge gaps in clinical trials, enable PHI-safe AI training, and unlock new possibilities for medical research and care.
Key Benefits
Accelerated Innovation – Cut months from model development by removing data bottlenecks
Regulatory Peace of Mind – Synthetic datasets are fully compliant with HIPAA, GDPR, and HITRUST
Cost Efficiency – Reduce reliance on expensive patient recruitment and manual labeling
Key Benefits
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Accelerated Innovation
Cut months from model development by removing data bottlenecks
Regulatory Peace of Mind
Synthetic datasets are fully compliant with HIPAA, GDPR, and HITRUST
Cost Efficiency
Reduce reliance on expensive patient recruitment and manual labeling
Fair & Inclusive Models
Correct imbalances in datasets for more equitable healthcare outcomes
Collaboration Without Risk
Share synthetic datasets across teams, institutions, and vendors without exposing PHI
Future-Proof AI
Enable continuous retraining and drift management with scalable synthetic pipelines
"Synthetic electronic health records (EHRs) are used to safeguard patient privacy while enabling medical research and healthcare use cases."
CTO
Leading Japanese MNC