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.

"Synthetic electronic health records (EHRs) are used to safeguard patient privacy while enabling medical research and healthcare use cases."
CTO, Leading Japanese MNC

Key Challenges

Challenge Description
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

Solution Description
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 APIs and connectors slot into existing research, trial, and hospital IT pipelines for fast adoption.

Use Cases

Use Case Description
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

Key Benefits

Benefit Description
Skip the IRB Bottleneck Train and test models without waiting months for data access approvals
HIPAA/HITRUST Compliant by Default Synthetic records contain no real patient data, eliminating PHI exposure risk
Fill Gaps in Rare Disease Data Generate cohorts for conditions where real patient data simply doesn't exist in volume
Share Freely Across Institutions Collaborate with external researchers and vendors without data use agreements
Test on Diverse Populations Ensure models work across demographics that are underrepresented in your real data

"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

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.

Book a Meeting