Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
Open-source, Rust-built secure runtime that runs AI agents in encrypted enclaves so credentials never reach the model.
Enterprise AI platform for redacting, anonymizing, and governing sensitive data across documents and AI workflows.
Developer-first security platform unifying code, cloud, runtime and AI pentesting with noise reduction and autofix.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Runtime protection for AI agents and apps
- ✦Prompt-injection and jailbreak prevention
- ✦Data-leakage detection in prompts
- ✦Shadow-AI discovery across apps and browsers
- ✦Policy controls by user, app and action
- ✦AI red-teaming and adversarial testing
- ✦Encrypted credential vault injected only at approved endpoints
- ✦Agents run inside Trusted Execution Environments (encrypted enclaves)
- ✦Sandboxed tools in Wasm containers with capability-based permissions
- ✦Real-time outbound leak detection to block credential exfiltration
- ✦Rust codebase for memory safety
- ✦One-click cloud deploy on NEAR AI Cloud or self-host from source
- ✦AI-powered document redaction
- ✦Real-time data anonymization
- ✦AI guardrails for generative-AI apps
- ✦Automated compliance enforcement
- ✦Industry-specific solutions for government, legal, and healthcare
- ✦SAST, SCA and secrets scanning
- ✦Cloud misconfiguration (CSPM) and container scanning
- ✦AI-powered autonomous pentesting
- ✦AutoFix pull requests and auto-triage
- ✦Runtime and bot protection (Zen)
- ✦SOC 2 and ISO compliance support
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements
- →Running autonomous AI agents without exposing secrets
- →Self-hosting a secure personal AI assistant
- →Deploying agents in a confidential-compute environment
- →Automating FOIA and public-records redaction
- →Protecting privileged data in eDiscovery
- →Preventing data leakage to AI systems
- →Finding and fixing code vulnerabilities
- →Securing cloud and containers
- →Running continuous pentests
- →Automating compliance evidence