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Subscription bundle of a dozen role-based AI assistants (support, social, sales, SEO, and more) letting small teams delegate routine work.
MiniMax's general-purpose autonomous AI agent that plans and completes complex multi-step tasks from a single prompt.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
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
No public pricing
- ✦12+ role-specific AI helpers covering support, sales, SEO, and more
- ✦One-click use-case templates for common tasks
- ✦15+ third-party integrations
- ✦Custom brand knowledge base ('Brain AI')
- ✦Support for 100+ languages
- ✦Continuous 24/7 automated operation
- ✦No-code, chat-based interface
- ✦Autonomous multi-step task execution
- ✦Natural-language task delegation
- ✦Powered by MiniMax frontier models
- ✦Handles research, building and content tasks
- ✦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
- ✦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
- →Automating social media scheduling and content creation
- →Handling routine customer support replies
- →Drafting marketing copy and email campaigns
- →Turning business data into actionable insights
- →Running SEO audits and optimizing content
- →Screening candidates and drafting recruiting materials
- →Delegating complex tasks to an AI agent
- →Automating research and analysis
- →Producing reports and deliverables
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →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