---
title: "Deploy Anyray"
description: "Self-hosted AI-spend optimizer: gateway, optimizer, and console."
category: "AI/ML"
url: https://railway.com/deploy/anyray
---

# Deploy Anyray

Self-hosted AI-spend optimizer: gateway, optimizer, and console.

**[Deploy Anyray on Railway](https://railway.com/template/anyray)**

Machine-readable deploy manifest (JSON, validated by TemplateCI): https://railway.com/deploy/anyray/manifest.json

- **Creator:** Othentic
- **Category:** AI/ML
- **Total deploys:** 3

## Template content

### Postgres

- **Image:** ghcr.io/railwayapp-templates/postgres-ssl:17

### proxy

- **Image:** public.ecr.aws/anyray/proxy:v1.10.224

### gateway

- **Image:** public.ecr.aws/anyray/gateway:v1.10.224
- **Health check:** /

### optimizer

- **Image:** public.ecr.aws/anyray/optimizer:v1.10.224
- **Health check:** /health

## Documentation

# Deploy and Host Anyray on Railway

Anyray is a self-hosted AI-spend optimizer. It sits in front of your LLM providers, serves each request as cheaply as it can, and gives you spend visibility and governance — without exposing prompt or response content to humans.

This template deploys the full stack: an OpenAI-compatible **gateway** (which also serves the Anyray console), the inference **optimizer**, an nginx **proxy**, and a **Postgres** datastore for the content-free trace and spend store. All secrets are auto-generated by Railway.

## About Hosting Anyray

Hosting Anyray on Railway stands up four services as one project. The gateway exposes an OpenAI-compatible API and the admin console; the proxy serves the console on a public domain. After the services deploy, you generate two public domains — one for the proxy (target port 80, the console) and one for the gateway (target port 8787, the API) — add at least one provider key on the gateway, then sign in to the console with the auto-generated `ANYRAY_ADMIN_TOKEN`. Prompt and response content is encrypted at rest and never logged in plaintext; the Postgres store keeps metadata only.

## Why Deploy Anyray on Railway

Railway provisions and wires all four services from a single template, auto-generating every secret and the Postgres password, so there is no manual setup. You keep full control of your data — keys and content stay inside your own Railway project — while Railway handles scaling, networking, and persistence.

## Common Use Cases

- Cut the AI-inference spend your employees' coding assistants, agents, and SDK jobs generate.
- Give an organization spend visibility and per-team/per-user attribution for LLM usage.
- Run a privacy-preserving LLM gateway where prompt/response content is never exposed to humans.

## Dependencies for Anyray Hosting

- A Railway account/plan able to run four services.
- At least one upstream LLM provider API key (e.g. OpenAI or Anthropic).

### Deployment Dependencies

- Anyray docs: https://docs.anyray.ai
- Install repo and template spec: https://github.com/anyrayHQ/install

### Implementation Details

Expose only the `proxy` and `gateway` services publicly; keep `optimizer` and `Postgres` private. Railway's private network is IPv6-only, and the proxy rewrites its nginx upstreams to `*.railway.internal` automatically.

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Open this page in a browser: https://railway.com/deploy/anyray