S

    Sherpa.ai

    Privacy-preserving SaaS platform specializing in Federated Learning for secure AI model training without raw data sharing.

    ESSpain·Founded 2012
    Headquarters
    🇪🇸Spain
    Data Hosting
    Customer-defined
    Structure
    Independent
    Compliance
    ▣GDPR◆EU HQ▦EU Data

    Sherpa.ai key facts

    Last updated
    Legal entity
    Sherpa.ai (Sherpa Europe SL)
    Headquarters
    Spain (ES)
    Ownership
    Independent
    Founded
    2012
    Data hosting
    Customer-defined
    Infrastructure
    SaaS platform with client-localized nodes
    Open source
    No
    US Cloud Act exposure
    Low (no US parent)
    Certifications
    ISO 27001, HIPAA (aligned)
    Replaces
    Google Cloud AI, Amazon SageMaker, Azure Machine Learning, PySyft (OpenMined)

    About Sherpa.ai

    Sherpa.ai is a leading European AI company that provides an enterprise SaaS platform for Federated Learning. Their technology allows organizations to train artificial intelligence models without the need to share or centralize raw data, keeping sensitive information localized behind the participants' own firewalls. This approach solves major privacy and regulatory hurdles in highly sensitive sectors. The platform is designed for large-scale enterprise deployments in sectors such as healthcare, finance, and manufacturing. By moving the AI algorithms to the data rather than the data to the algorithms, Sherpa.ai enables secure collaboration between different entities (e.g., multiple hospitals or banks) to create more accurate global models while maintaining total data sovereignty for each participant.

    Alternative to

    Hosting & Security

    Infrastructure

    SaaS platform with client-localized nodes

    Certifications
    ISO 27001
    HIPAA (aligned)

    Key Features

    Federated Learning platform
    Privacy-preserving AI model training
    Hub-and-spoke architecture
    Horizontal and Vertical Federated Learning support
    Real-time inference at the edge
    Cross-organization data collaboration
    Anonymized model parameter aggregation

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