Sarus
by Sarus · Privacy layer for analytics and AI on sensitive data
7.4 — BenchRank score out of 100
Screenshots of Sarus
Homepage
Overview
A privacy layer that lets analysts and data scientists query sensitive data without direct access to it. Sarus rewrites data processing jobs into privacy-safe versions on the fly, applies differential privacy to results, and supplies synthetic data from a model trained with differential privacy. It is deployed on-premises or in your own cloud, then connected to your data sources.
- Best for
- Data and compliance teams that need analysts to use personal data without seeing it
- Pricing
- No prices are shown on the captured page; the site directs you to get in touch.
- Runs on
- WebSelf-hosted
Strengths and trade-offs
Strengths
- Analysts query sensitive data without ever seeing raw records
- Differential privacy applied to every query result
- Works with SQL, pandas and scikit-learn workflows
- Self-hosted via Docker or Kubernetes, no data movement
Trade-offs
- No pricing published; you have to contact the vendor
- You host and operate it yourself, on-prem or in your own cloud
- Previews come from synthetic data, not the real records
- LLM support is still an opt-in beta
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
- MCP support
- 0 out of 100
- API quality
- 0 out of 100
- Documentation
- 0 out of 100
- Agent friendliness
- 39 out of 100
- Changelog
- 0 out of 100
- Marketing site structure
- 20 out of 100
- Operational trust
- 0 out of 100
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
- Openness
- 60 out of 100
- Maintenance
- 15 out of 100
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