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Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
Claims a fully autonomous AI system that runs companies 24/7; overreaching pitch, thin proof.
Open-source, self-hosted app to manage teams of AI agents like a company - org chart, goals, budgets and per-agent approvals.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
No public pricing
No public pricing
- ✦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
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- ✦Autonomous planning, coding, and marketing
- ✦24/7 continuous business operations
- ✦Third-party tool integrations (Email, Social, Payments)
- ✦Self-adapting and data-driven optimization
- ✦Founder inbox management and VC negotiation
- ✦Live dashboard for real-time task tracking
- ✦Manage teams of AI agents
- ✦Bring-your-own-agent (any runtime/provider)
- ✦Org chart with roles and reporting lines
- ✦Goal alignment for tasks
- ✦Per-agent budget and cost controls
- ✦Ticket system with full audit trail
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →Building and launching a startup with zero human staff
- →Automating multi-channel marketing and content promotion
- →Maintaining and updating software products on autopilot
- →Managing investor relations and daily business workflows autonomously
- →Orchestrating agents across business functions
- →Running dev, marketing and research agents
- →Building autonomous-business workflows
- →Governing and budgeting agent work
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale