Apheris AI

Apheris AI

A deep tech company with the mission to fundamentally change how organizations collaborate securely and extract value from data.

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$20.8m

Series A
Total Funding000k

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Revenues, earnings & profits over time
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Source: Company filings or news article

More about Apheris AI
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Apheris is a startup that operates in the data security and privacy sector, providing a comprehensive solution for machine learning (ML) governance, security, and privacy. The company's services are designed to cater to businesses that handle sensitive data and require robust security measures. Apheris offers a unique approach to data protection, where data never moves or is directly accessible, thus ensuring its value and security.

The company's business model revolves around the Apheris Compute Gateway, a tool that brings ML and analytics computations to the client's data. This gateway can be deployed in any cloud or on-premise environment, allowing businesses to scale from a single dataset to a full data ecosystem. This approach not only ensures data security but also reduces costs and increases the speed of delivering data and ML-powered products to customers.

Apheris also provides enterprise-grade authentication and authorization, encryption in transit and at rest, and detailed audit logs for traceability, governance, and compliance. This comprehensive security package is designed to minimize the risk of data reverse engineering and to comply with any current and future regulations.

In addition to data security, Apheris also promotes data collaboration. It allows businesses to define who can execute computations on their data, enabling internal data collaboration and the building of a data ecosystem. The company's services can be integrated into any tech stack, including popular ML frameworks, and can be used to build new and improved ML-enabled products.

In summary, Apheris is a data security and privacy startup that provides a comprehensive solution for businesses handling sensitive data, enabling them to securely and efficiently use their data for ML and analytics computations.

Keywords: Data Security, Data Privacy, Machine Learning, Analytics, Cloud Deployment, On-Premise Deployment, Data Collaboration, Compliance, Authentication, Encryption.

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