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ByteDance's no-code platform for building and deploying AI chatbots and agents with plugins and workflows.
Searchable directory of open-source AI agent 'skills' (SKILL.md files) for developers building with Claude, Codex, or ChatGPT agents.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
Open-source, self-hosted app to manage teams of AI agents like a company - org chart, goals, budgets and per-agent approvals.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦No-code bot and agent builder
- ✦LLM-powered conversations
- ✦Plugin ecosystem
- ✦Visual workflow builder
- ✦Knowledge base (RAG)
- ✦Multi-channel publishing
- ✦Full-text search across millions of indexed SKILL.md files
- ✦Browse skills by creator or by occupation category
- ✦Inspect GitHub source links for each skill before use
- ✦REST API access to the skill catalog
- ✦One-click running of skills inside supported agent platforms
- ✦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
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦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
- →Building customer-support bots
- →Deploying agents to messaging channels
- →Automating workflows
- →Prototyping AI assistants
- →Finding an existing agent skill instead of writing one from scratch
- →Comparing similar skills across different creators
- →Building custom search or analytics on top of the skill catalog via API
- →Discovering skills relevant to a specific job function
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Orchestrating agents across business functions
- →Running dev, marketing and research agents
- →Building autonomous-business workflows
- →Governing and budgeting agent work