Check Point AI Agent Security vs. Protegrity
A side-by-side comparison based on G2 review data.
| Metric | Check Point AI Agent Security | Protegrity |
|---|---|---|
| Overall rating | 4.2 | 4.5 |
| Review count | 12 | 14 |
| Ease of use | 8.6 | 9.0 |
| Ease of setup | 8.7 | 9.3 |
| Quality of support | 9.0 | 9.3 |
| Meets requirements | 8.7 | 9.3 |
| NPS | 45.454545 | 57.142857 |
| Small Business | 50.0% | 23.1% |
| Mid-Market | 33.3% | 46.2% |
| Enterprise | 16.7% | 30.8% |
| Total page views | 194 | 307 |
| Total LLM citations | 672 | 666 |
Check Point AI Agent Security
Check Point AI Agent Security is a security platform for discovering, governing, and protecting AI agents that organizations build and deploy. It provides visibility into AI agents across supported cloud and low-code platforms, including their tools, Model Context Protocol (MCP) servers, permissions, and connected components. The platform assesses agent risk to help security teams identify unknown agents, risky configurations, excessive access, and other security exposures.
- Features
Protegrity
Protegrity secures the data and knowledge layer AI runs on, binding protection directly to the data itself rather than locking access around it. Its platform tokenizes, encrypts, and masks sensitive data at the field and knowledge-graph level, enforcing policy in real time at the point of a prompt, query, or answer — across AWS, Azure, GCP, and OpenShift, with FIPS-validated, post-quantum-ready cryptography.