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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.
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Adversa AI
✓ verifiedPaid
AI red-teaming and security platform for LLMs, agents and GenAI apps, offering continuous testing and remediation.
35K visits/mo
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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
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Flagright AI
✓ verifiedPaid
AML and fraud compliance platform pairing transaction monitoring, screening, and explainable AI agents for financial institutions.
39K visits/mo321 saves
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Mindgard
✓ verifiedPaid
Automated AI red-teaming platform that discovers, tests, and defends AI models and agents against security threats.
32K visits/mo
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦AI threat modeling for your stack
- ✦Continuous autonomous red-teaming
- ✦Auto-generated patches and remediation reports
- ✦Coverage for agents, MCP, LLMs and GenAI apps
- ✦Managed service or self-serve platform
- ✦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
- ✦Real-time transaction monitoring and rule engine
- ✦Explainable AI forensics agents
- ✦Dynamic risk scoring
- ✦Watchlist/sanctions/PEP screening
- ✦AI-native case management
- ✦Automated SAR filing to FinCEN and 70+ GoAML countries
- ✦Automated AI red teaming
- ✦AI discovery and attack-surface mapping
- ✦Agent-native reconnaissance
- ✦Exploitable-risk detection and reporting
- ✦Runtime AI protection and response
- ✦CI/CD, Burp Suite, and API integrations
Use cases
- →Red-team custom AI agents and copilots
- →Detect prompt injection and agent hijacking
- →Harden GenAI apps before shipping
- →Continuously assess AI security posture
- →Prevent data leaks across SaaS apps
- →Classify and monitor sensitive data
- →Reduce breaches from human error
- →Give security teams cloud data visibility
- →AML compliance and monitoring
- →Reducing false-positive alerts
- →Streamlining fincrime investigations and SAR filing
- →Testing AI systems against evolving attacks
- →Finding vulnerabilities in models and agents
- →Securing agentic workflows in production
- →AI governance and compliance reporting
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