Railway
One-click deploy from GitHub with persistent volumes and databases for stateful agent deployments.
What Railway is for
Railway sits in the infrastructure & tooling category of the agent stack. Agent infrastructure covers the layer that makes agents production-ready: deployment, hosting, sandboxed execution, tool integration, and scaling. If frameworks are the engine, this is the drivetrain.
Typical use cases
- Deploying and scaling agents in production
- Sandboxed code execution for untrusted agent actions
- Connecting agents to third-party tools and APIs safely
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FAQ
What is Railway?
Railway is a tool in the infrastructure & tooling category. One-click deploy from GitHub with persistent volumes and databases for stateful agent deployments.
What is Railway used for?
Tools in this category are commonly used for: deploying and scaling agents in production; sandboxed code execution for untrusted agent actions; connecting agents to third-party tools and apis safely.
What are alternatives to Railway?
Popular alternatives in the infrastructure & tooling category include Agent Starter, AgentDock, AWS Bedrock AgentCore, AWS Lambda, codex-profiles. Compare them all on the Infrastructure & Tooling category page.
Alternatives & related in Infrastructure & Tooling
Agent Starter
Project-local config manager that syncs one `agent.json` manifest into Claude Code, Codex, Cursor, and MCP setup while preserving manual edits and detecting drift.
AgentDock
Framework for building and deploying production-ready AI agents with composable node architecture.
AWS Bedrock AgentCore
Managed AWS infrastructure for Bedrock-based agents with compliance, scaling, and monitoring built in.
AWS Lambda
Serverless function runtime with Firecracker isolation for executing short-lived agent tasks at scale.
codex-profiles
Bash CLI for switching OpenAI Codex CLI and Desktop profiles with isolated CODEX_HOME directories.
Crawl4AI
Extracts structured data from web pages using LLM-friendly output formats optimized for agent ingestion.