RelayPlane vs Helicone AI Gateway
Helicone AI Gateway launched in 2026 as an LLM middleware layer built around observability, logging, and analytics. RelayPlane is an MIT-licensed npm package that runs on localhost with zero config and enforces per-request cost budgets automatically. Here is how they compare for Node.js developers and AI agent builders who need cost control, not just logging.
TL;DR
Choose RelayPlane when you want:
- npm install and running in 30 seconds with no account required
- Per-request budget enforcement with automatic model downgrade
- Runaway spend protection for production AI agents
- All request data stored locally in SQLite, no hosted backend
- Cost-first routing that fits your existing Node.js stack
Helicone AI Gateway may work for you if you need:
- Deep LLM observability with logging and request tracing
- Hosted analytics dashboard for LLM call inspection
- Middleware that feeds into the Helicone analytics platform
- Observability-first design with rich logging features
Feature Comparison
| Feature | RelayPlane | Helicone AI Gateway |
|---|---|---|
| Install method RelayPlane is a globally installed npm package. Helicone AI Gateway deploys via npx and is built around a hosted logging backend. For teams already using Node.js and npm, RelayPlane requires no additional tooling. | npm install -g @relayplane/proxy | npx helicone-ai-gateway deploy |
| Docker required Neither tool requires Docker to run. RelayPlane runs as a Node.js process on localhost. Helicone AI Gateway uses npx for deployment. | ||
| Node.js native RelayPlane is written in TypeScript and runs as a native Node.js process. Helicone AI Gateway is LLM middleware that connects to a hosted Helicone backend and is not a Node.js-native package. | ||
| Zero-config startup RelayPlane starts with relayplane start and requires no configuration file. Helicone AI Gateway requires a Helicone API key and setup steps to connect to the Helicone logging backend before it routes requests. | ||
| Per-request cost tracking RelayPlane calculates and stores the cost of every request in local SQLite, including token counts and model pricing. Helicone AI Gateway tracks usage through its observability backend but cost tracking is not the primary design goal. | ||
| Runaway spend protection RelayPlane enforces per-request and per-session budgets and automatically blocks or redirects requests when a cost threshold is hit. Helicone AI Gateway does not include automatic runaway spend protection. | ||
| Auto-downgrade on budget When a request would exceed a budget, RelayPlane automatically routes to a cheaper model rather than failing the request. Helicone AI Gateway does not implement cost-driven automatic model downgrade. | ||
| Built-in model routing RelayPlane routes requests to cheaper models based on estimated complexity and current budget state. Helicone AI Gateway is designed as observability middleware and does not include complexity-based model routing. | ||
| Auth passthrough Both tools pass your existing provider API keys through without requiring you to replace them. You keep your own keys. | ||
| REST API Both tools expose OpenAI-compatible REST endpoints that your existing code can target with a baseURL change. | ||
| TypeScript native Both projects use TypeScript. RelayPlane is a locally running TypeScript process. Helicone is a TypeScript SDK that connects to a hosted backend. | ||
| Open source Both projects publish source code. RelayPlane is MIT licensed. Helicone is open source on GitHub. | MIT | Open source (GitHub) |
| Dashboard RelayPlane includes a built-in web dashboard backed by local SQLite. All data stays on your machine. Helicone AI Gateway sends data to the hosted Helicone dashboard, which requires a Helicone account. | Built-in local SQLite dashboard | Hosted Helicone dashboard |
| Telemetry Both tools collect and surface telemetry. RelayPlane stores telemetry locally. Helicone sends telemetry to its hosted platform. | ||
| Observability-first design Helicone AI Gateway is designed around observability: logging, tracing, and analytics. RelayPlane is designed around cost control: per-request budgets, spend routing, and automatic downgrade. Different primary goals. | ||
| Setup time RelayPlane is running in under 30 seconds with no account or API key required for the proxy itself. Helicone AI Gateway requires a Helicone account and API key before requests route through it. | Under 30 seconds | 2 to 5 minutes |
| Pricing Both offer a free tier. RelayPlane pricing scales with usage. Helicone has subscription plans for higher request volumes and advanced dashboard features. | Free tier plus usage-based | Free tier plus paid plans |
| Primary use case RelayPlane is built for teams that need to track and control LLM spend per request. Helicone AI Gateway is built for teams that need deep observability into LLM calls, logging, and analytics. | Cost control and routing | Observability and logging |
Why Teams Choose RelayPlane Over Helicone AI Gateway
npm install vs npx deploy plus Helicone account
npm install -g @relayplane/proxy and relayplane start and you are proxying LLM requests in under 30 seconds, with no account required for the proxy itself. Helicone AI Gateway requires a Helicone account, an API key, and a deploy step that connects to the Helicone hosted backend before any request routes through it. For Node.js developers who want cost tracking without a hosted dependency, RelayPlane is significantly lower friction.
Runaway spend protection that Helicone AI Gateway does not include
RelayPlane enforces per-request and per-session spend budgets. When a request would push you over a cost threshold, RelayPlane automatically routes to a cheaper model rather than failing the call or allowing spend to continue unchecked. This automatic downgrade behavior is the core reason teams building production AI agents use RelayPlane. Helicone AI Gateway gives you observability and logging but does not enforce spend limits or redirect requests based on cost.
Local data storage vs hosted logging backend
RelayPlane stores all request data in local SQLite on your machine. You own the data indefinitely and it never leaves your environment. Helicone AI Gateway is built around the hosted Helicone backend, which means your request logs and analytics live in a third-party service. For teams with data residency requirements, privacy concerns, or on-premise constraints, RelayPlane's local-first design is a meaningful advantage.
Cost-first vs observability-first: different tools for different jobs
Helicone AI Gateway is a well-designed observability tool. If your primary need is logging, tracing, and dashboards for your LLM calls, it is a legitimate choice. But if your primary need is controlling what you spend per request, routing to cheaper models automatically, and stopping runaway agent costs before they hit your invoice, RelayPlane is purpose-built for that problem in a way Helicone AI Gateway is not. They serve different goals.
Helicone AI Gateway Is Built for Observability. RelayPlane Is Built for Cost Control.
Helicone launched their AI Gateway product in 2026 as a distinct offering from their original proxy and observability platform. It is designed as LLM middleware with logging, analytics, and request tracing as the core value. If your team primarily needs visibility into what your LLM calls are doing -- who called what, when, and with what prompts -- Helicone AI Gateway serves that use case.
But if your primary problem is cost -- specifically, tracking what every request costs, enforcing spend limits, and automatically routing to cheaper models before your invoice gets out of hand -- Helicone AI Gateway is the wrong tool. RelayPlane is built specifically for that problem. It installs via npm, starts with no config, stores everything locally, and enforces budgets at request time. Those are different design goals, and it matters which one matches your actual need.
Get Running in 30 Seconds
No account. No hosted backend. No config file: