Aindo
Aindo provides a generative AI synthetic data platform and clinical language models that turn private healthcare data into analysis-ready evidence.
At a Glance
About Aindo
Aindo SpA, based in Trieste, Italy, develops a synthetic data platform for healthcare, life sciences and public institutions. Its generative AI creates artificial data that replaces personal data, so teams can run analyses without exposing patient-level information. The company's solutions cover public health planning, real-world evidence, external control arms and clinical language models.
What It Is
Aindo's platform uses generative AI to produce synthetic data that mirrors real datasets without containing personal information. The platform page describes four core capabilities: privacy protection, data completion for missing or inaccurate records, data compatibilization across formats and systems, and bias removal by balancing socio-demographic data. It has a visual interface and connects to major database systems. The platform page says it can be deployed locally.
Solutions and Workflows
- Public health: synthetic data for forecasting demand, scenario modeling and sharing insights across organizations without patient-level data.
- Real-world evidence: synthetic cohorts for observational studies and outcomes research.
- External control arms: synthetic control groups that can complement or replace traditional ones in clinical trials.
- Clinical intelligence: specialized clinical language models for treatment comparison, medical reasoning and knowledge access, trained on real and synthetic data.
Who It Serves and Compliance Positioning
Aindo targets researchers and clinicians, pharma companies and CROs, and public administrations. The site states that it is GDPR-ready, EHDS-ready and AI Act compliant. It lists Europrivacy, ISO 9001 and ISO 27001 certifications. These are vendor-published claims.
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Pricing
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Capabilities
Key Features
- Generative AI synthetic data generation
- Privacy protection by replacing personal data
- Data completion for missing or inaccurate records
- Data compatibilization across formats and systems
- Bias removal through socio-demographic balancing
- Synthetic cohorts for real-world evidence
- Synthetic external control arms for clinical trials
- Specialized clinical language models
- Connectivity to major database systems
- Local deployment option
- Visual user interface
