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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.
Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Conversational writing and editing
- ✦Code generation and debugging (Claude Code)
- ✦Data analysis and visualization
- ✦Web search plus memory across chats
- ✦Connectors and remote MCP integrations
- ✦Extended thinking for complex tasks
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- ✦Enterprise search across company apps
- ✦Personal AI assistant grounded in work data
- ✦Agent builder, orchestration and governance
- ✦250+ connectors and actions
- ✦Enterprise knowledge graph and hybrid search
- ✦Security controls for scaling AI
- →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
- →Drafting and refining written content
- →Building and debugging software
- →Analyzing datasets for insights
- →Research and learning support
- →Team and enterprise automation
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows