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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Aikido Security logo
Aikido Security
✓ verifiedFreemium

Developer-first security platform unifying code, cloud, runtime and AI pentesting with noise reduction and autofix.

670K visits/mo
218K visits/mo
Gamma AI logo
Gamma AI
✓ verifiedPaid

Cloud DLP and CASB that classifies and protects sensitive data across SaaS apps using deep learning (now Palo Alto Networks).

168K visits/mo
IronClaw logo
IronClaw
✓ verifiedFree

Open-source, Rust-built secure runtime that runs AI agents in encrypted enclaves so credentials never reach the model.

37K visits/mo
Vectra logo
Vectra
✓ verifiedPaid

AI-driven network detection and response platform that identifies and stops identity-based and lateral-movement cyberattacks in real time.

203K visits/mo1.0K saves
Pricing
Developer: $0 (2 users, 10 repos)
Basic: $300/mo (10 users, 100 repos)
Pro: $600/mo (200 repos)
Standard Pentest: $4,000 per assessment

Free trial available

No public pricing

No public pricing

No public pricing

No public pricing

Core features
  • 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
  • LLM API router
  • OpenAI API proxy
  • Model aggregation (OpenAI, Gemini, DeepSeek, Llama, Qwen, Claude, etc.)
  • Unified OpenAI API standard
  • Unlimited concurrency
  • Deep-learning data classification (99.5% claimed accuracy)
  • Cloud DLP across SaaS applications
  • One-click deployment across apps, devices and users
  • End-user self-remediation of violations
  • Broad SaaS integrations
  • Insider-threat and breach monitoring
  • 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
Use cases
  • Finding and fixing code vulnerabilities
  • Securing cloud and containers
  • Running continuous pentests
  • Automating compliance evidence
  • Integrating multiple AI models into applications using a single API
  • Accessing the latest AI models through a unified interface
  • Managing and scaling AI model usage with unlimited concurrency
  • Prevent data leaks across SaaS apps
  • Classify and monitor sensitive data
  • Reduce breaches from human error
  • Give security teams cloud data visibility
  • 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
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