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AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
AI/ML bug-bounty platform where researchers bypass LLM guardrails in timed challenges to win cash prizes.
Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦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
- ✦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
- ✦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
- ✦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
- ✦LPU custom inference hardware
- ✦GroqCloud tokens-as-a-service API
- ✦High-speed, low-latency inference
- ✦Pay-as-you-go token pricing
- ✦Free API key to start
- ✦Broad open-model support
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Red-teaming and jailbreaking LLMs
- →Earning bounties for AI exploits
- →Learning AI attack techniques
- →Competing against other researchers
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API