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
Enterprise AI platform for redacting, anonymizing, and governing sensitive data across documents and AI workflows.
Generative-AI security platform for watermarking and detecting voice, image, and video deepfakes, built on its own voice-cloning models.
Cloud DLP and CASB that classifies and protects sensitive data across SaaS apps using deep learning (now Palo Alto Networks).
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
Free trial available
- ✦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
- ✦Multimodal deepfake detection for audio, image, and video
- ✦Invisible, persistent watermarking for media provenance
- ✦Real-time deepfake monitoring bot for live meetings
- ✦Voice cloning and text-to-speech generation
- ✦Pay-as-you-go credit-based Flex pricing plan
- ✦Enterprise on-premise deployment and SSO options
- ✦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
- ✦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
- ✦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
- →Automating FOIA and public-records redaction
- →Protecting privileged data in eDiscovery
- →Preventing data leakage to AI systems
- →Enterprises verifying caller identity to prevent voice fraud
- →Media companies watermarking content for provenance tracking
- →Security teams monitoring live calls for deepfake impersonation
- →Developers building AI voice agents with cloned voices
- →Prevent data leaks across SaaS apps
- →Classify and monitor sensitive data
- →Reduce breaches from human error
- →Give security teams cloud data visibility
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements