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Enterprise AI platform for redacting, anonymizing, and governing sensitive data across documents and AI workflows.
Open-source, Rust-built secure runtime that runs AI agents in encrypted enclaves so credentials never reach the model.
Generative-AI security platform for watermarking and detecting voice, image, and video deepfakes, built on its own voice-cloning models.
AI red-teaming and security platform for LLMs, agents and GenAI apps, offering continuous testing and remediation.
AI/ML bug-bounty platform where researchers bypass LLM guardrails in timed challenges to win cash prizes.
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No public pricing
No public pricing
- ✦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
- ✦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
- ✦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
- ✦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
- ✦Timed AI-hacking challenges with cash pots
- ✦Public leaderboard and rankings
- ✦Guardrail-bypass and jailbreak objectives
- ✦Hacktivity feed of activity
- ✦Community via Discord
- ✦Blog on LLM exploits and AI security
- →Automating FOIA and public-records redaction
- →Protecting privileged data in eDiscovery
- →Preventing data leakage to AI systems
- →Running autonomous AI agents without exposing secrets
- →Self-hosting a secure personal AI assistant
- →Deploying agents in a confidential-compute environment
- →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
- →Red-team custom AI agents and copilots
- →Detect prompt injection and agent hijacking
- →Harden GenAI apps before shipping
- →Continuously assess AI security posture
- →Red-teaming and jailbreaking LLMs
- →Earning bounties for AI exploits
- →Learning AI attack techniques
- →Competing against other researchers