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Sarus

The privacy layer for analytics and AI.

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Sarus is a privacy layer positioned between a data source and its consumers, allowing analysts and data scientists to query sensitive data without direct access to the underlying records. Each submitted query or processing job is checked against a privacy policy and rewritten on the fly, so results are checked and enforced before they are returned. The approach is built on differential privacy research, and the platform also offers synthetic data generated by a generative-AI model trained with differential privacy.

Key capabilities include connectors to data sources, privacy policies, audit logging, synthetic data, analytics and BI, machine learning, and action upon data. It supports query rewriting, output-level control, and LLM workflows, including fine-tuning open source models on private data. Sarus deploys on-premises or in public cloud environments (Azure, AWS, GCP) using Docker or Kubernetes, and works with tools such as SQL, pandas, and sklearn. It is aimed at data security teams, data protection teams, and AI and analytics teams.

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