$ loading_
Build, deploy, and manage fully managed AI agents and workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "trigger.dev" yet — see the docs or source repo.
Using trigger.dev, design a fully managed AI customer support agent workflow that receives user questions, retrieves answers from a knowledge base, escalates uncertain cases to a human, and explain deployment and monitoring steps.
A customer support agent workflow plan with node design, deployment flow, escalation logic, and monitoring recommendations.
Based on trigger.dev, plan a content moderation workflow that triggers on new content, uses an LLM for policy violation detection, queues high-risk items, and notifies the operations team.
An executable moderation automation plan covering triggers, model calls, queue handling, and notifications.
Use trigger.dev to design a scheduled AI analytics agent that summarizes business metrics daily, generates brief insights, and automatically sends them to product and operations teams.
A workflow design for a scheduled analytics agent, including task scheduling, insight generation, and message delivery.
List agents, run workflows, and enforce team AI governance policies.
Build, run, inspect, and debug AI agents with better visibility.
Build and sync AI agents and multi-agent workflows visually or with TypeScript.
An open-source workspace to build, share, and run AI agents
Build self-hosted visual AI workflows with agents, RAG, HITL, and observability.
Track AI agent market intelligence, rankings, trust signals, and liveness.