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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.
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.
Enterprise AI governance platform to inventory AI systems, assess risk and map controls to regulations like the EU AI Act and NIST.
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No public pricing
No public pricing
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
- ✦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
- ✦AI/agent registry with shadow-AI discovery
- ✦Continuous, contextual risk intelligence
- ✦Agentic risk and control library
- ✦Policy-to-code with pre-built regulatory policy packs
- ✦Compliance mapping and audit evidence
- ✦GAIA governance assistant and 300+ integrations
- →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
- →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
- →Comply with the EU AI Act, ISO 42001 and NIST AI RMF
- →Track and govern AI adoption and shadow AI
- →Assess third-party/vendor AI risk
- →Govern AI agents from intake to runtime