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
Open-source, Rust-built secure runtime that runs AI agents in encrypted enclaves so credentials never reach the model.
AI-driven network detection and response platform that identifies and stops identity-based and lateral-movement cyberattacks in real time.
Developer-first security platform unifying code, cloud, runtime and AI pentesting with noise reduction and autofix.
Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Real-time AI-driven threat detection beyond traditional EDR
- ✦Detection of identity-based attacks and lateral movement
- ✦360 Response for enforced containment across identity, devices, and network
- ✦Exposure management and security posture improvement tools
- ✦Managed detection and response (MXDR/MDR) services
- ✦Integrations across existing security tool ecosystems
- ✦Attack Labs research sharing threat intelligence and techniques
- ✦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
- ✦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
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- →Running autonomous AI agents without exposing secrets
- →Self-hosting a secure personal AI assistant
- →Deploying agents in a confidential-compute environment
- →Security operations teams needing detection beyond EDR/SIEM gaps
- →Enterprises defending against identity-based and hybrid cloud attacks
- →Organizations needing managed threat detection and response services
- →Finance, healthcare, and public sector teams meeting compliance-driven security needs
- →Finding and fixing code vulnerabilities
- →Securing cloud and containers
- →Running continuous pentests
- →Automating compliance evidence
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents