Cybersecurity & Security

Fight advanced threats by sharing intelligence—without sharing data

The application of Artificial Intelligence through Sherpa.ai’s Privacy-Preserving platform will allow the prediction algorithm to improve the diagnosis without the need to share any patient data. This platform may enable testing of diagnosis and therapeutics for a group of diseases that are currently without specific treatment options.

Thomas Kalil

Former Deputy Director, Office in Science and Technology Policy, The White House

Use Cases

Collective Threat Detection


Unify signals from multiple organizations to detect complex attack patterns without exposing internal systems.

Stronger Defense Models Across Companies

Train federated models on cross-company data to prevent more sophisticated attacks.

Proactive Ransomware Prevention

Identify suspicious behavior early without needing to share internal logs.

Protection of Critical Infrastructures


Collaborate with other entities to secure essential environments while maintaining full control over your data.

Scalable and Private Object Detection with Federated Learning

This study evaluates training object detection models (YOLOv8) in privacy-sensitive environments without sharing data or metadata. Sherpa.ai’s Horizontal Federated Learning significantly outperforms local baselines, proving its effectiveness while ensuring full data privacy.

Sherpa.ai Partners Prosegur

Collaborative and Private Ransomware Detection with Federated Learning

This study shows how organizations can collaboratively detect ransomware using Horizontal Federated Learning with Sherpa.ai. The federated model outperforms locally trained models and closely matches centralized performance, all while preserving privacy and avoiding data sharing.

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