From raw data to evidence-ready cohorts

Real-World Evidence

From raw data to evidence-ready cohorts

Our AI evidence infrastructure allows you to safely access, analyze, and share health data.

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Aindo enables pharmaceutical companies, CROs, and research organizations to generate high-quality Real-World Evidence while maintaining full compliance with data protection and regulatory requirements.

Accelerates evidence generation Improves study scalability Reduces operational barriers

With Aindo's AI evidence infrastructure, you can:

Generate privacy-safe real-world datasets

Transform sensitive real-world data into statistically representative synthetic datasets that preserve analytical value while reducing re-identification risk.

Accelerate evidence generation

Bypass approval delays, contractual bottlenecks, and data-sharing complexity to start analysis immediately instead of months later.

Enable multi-site and cross-border collaboration

Share and combine datasets across partners, institutions, and geographies without transferring personal data.

Improve data coverage and representativeness

Augment sparse or biased datasets to better capture rare conditions, underrepresented populations, and real-world variability.

Built for Europe's most advanced healthcare regulations

Designed for the new European health data framework and certified for data processing in healthcare.

Europrivacy

Art 42 GDPR

ISO 9001

Quality

ISO 27001

Information security

Gender Equality

UNI PDR 125:2022

NIST

Cybersecurity & privacy

Where synthetic data amplifies real-world evidence impact

Regulatory submissions
Support regulatory submissions and label expansion studies with compliant synthetic evidence.
Post-market surveillance
Enable large-scale post-marketing surveillance and pharmacovigilance analytics at scale.
Comparative effectiveness
Conduct comparative effectiveness and outcomes research across representative populations.
Health economics & market access
Strengthen HEOR, pricing, and market access models with scalable synthetic datasets.
Feasibility & protocols
Accelerate feasibility studies and optimize protocols before and during clinical trials.
Data collaboration
Enable data sharing across consortia and external partners without exposing patient data.

Explore how synthetic data supports high-quality RWE

Read our white paper on synthetic data in clinical research.

Explore our white paper

Ingest and harmonize healthcare data

Clinical data are ingested and mapped to a standardized structure.

Generate and validate synthetic cohorts

Synthetic data are generated and validated for utility, bias, and privacy.

Deliver compliant, analysis-ready datasets

Teams receive cohorts ready for analysis, sharing, and iteration.

Synthetic data accelerate researchers' access to health data, facilitating the generation of clinical evidence.

Aldren Gonzales, PhDU.S. Dept. of Health and Human Services

Synthetic data can act as a proxy for real clinical trial data sets, and simultaneously have low privacy risks.

Samer El Kababji, PhD, MEng, MScCHEO Research Institute, Ottawa, Canada

Synthetic data goes beyond privacy: it can augment, rebalance, and improve datasets for downstream research.

Boris van Breugel, PhDSenior ML Researcher, Qualcomm AI Research

Results based on synthetic data were highly predictive of those based on real data.

Anat Reiner-BenaimAssistant Professor, Ben-Gurion University of the Negev

Synthetic data enable data generation and sharing in support of research and precision healthcare.

Randi E. ForakerChair of Biomedical Informatics, Biostatistics and Medical Epidemiology (BBME)

Partner with Aindo

Are you a life sciences organization, CRO, or public institution looking to modernize data-driven decisions while maintaining the highest privacy and compliance standards?