Why Choose EdgeOne Makers for AI Deployment
The fastest path from ai agent deployment code to production — focus on your business logic, we handle the infrastructure for every agent deployment.
One-Command Deployment
Deploy with `git push` for auto-deploy or `edgeone makers deploy` via CLI — no Docker, no Kubernetes, no server provisioning.
Built-in Agent Runtime
Managed runtime with session-sticky routing, up to 1-hour execution time, and in-memory state reuse — purpose-built for LLM calls and multi-step agent loops.
Integrated AI Models
Access DeepSeek, MiniMax, Hunyuan, and more through a unified AI gateway. New accounts receive 500K free tokens with zero configuration.
Full Observability
Zero-instrumentation distributed tracing — view complete call chains, LLM interactions, tool invocations, and latency metrics in local and cloud dashboards.
How to Complete AI Deployment in 3 Steps
From code to live ai agent deployment in minutes — no terminal expertise or complex configurations needed for agent deployment.
1
Write Your Agent
Build in the `agents/` directory with any framework (OpenAI SDK, Claude SDK, LangGraph, CrewAI, DeepAgents).
2
Deploy to Production
Push to Git (GitHub/GitLab/Gitee) for auto-deploy, or run `edgeone makers deploy` via CLI.
3
Go Live
Deploys globally in minutes with automatic SSL and edge routing.
Everything You Need for AI Deployment
A complete ai agent deployment platform with all the infrastructure, tools, and AI models your agent needs to run in production.
Feature | Description |
|---|---|
| Agent Runtime | Hosts LLM calls, Agent loop orchestration, and business logic, with session-based routing and automatic scaling. |
| Sandbox Tools | Provides two separate yet interoperable API layers for both LLMs and developers. Browser automation, code execution, Shell, and file operations all run in an isolated sandbox environment. |
| Conversation Storage | Provides framework-compatible memory management, with unified APIs for sessions and messages. |
| Observability | Automatically collects call traces with zero-intrusion instrumentation, enabling unified trace viewing in both local and cloud dashboards. |
| Built-in Models | Access Hunyuan and other mainstream Chinese models through AI Gateway with a limited-time free token quota. |
How do I complete AI deployment on EdgeOne Makers?
Write your agent logic in the `agents/` directory, set the framework in `edgeone.json`, then push via Git or run `edgeone makers deploy`. Your ai agent deployment goes live globally in seconds. See the Quick Start Guide: https://pages.edgeone.ai/document/agents-quick-start for a full walkthrough.
What frameworks are supported for AI deployment?
EdgeOne Makers supports ai agent deployment with OpenAI SDK, Claude SDK, LangGraph, CrewAI, and DeepAgents in both JavaScript and Python. The platform adapts automatically.
What are the free tier limits for AI deployment?
Free tier: 200,000 executions/month, 100,000 GB-s memory time, 40 concurrent sessions, 3,600-second max runtime. No credit card required for agent deployment.
How long can a deployed AI agent run per request?
Each ai agent deployment supports execution from 5 minutes up to 1 hour, suitable for complex multi-step agent loops and long-running workflows.
Does AI deployment include built-in AI models?
Yes. 500K free tokens per month per account (shared across all projects) via AI gateway, supporting DeepSeek, MiniMax, Hunyuan, and more. No separate model setup required.