RelayPlane vs Humanloop
Humanloop is a prompt management and evaluation platform with a visual editor, A/B testing, human feedback collection, and fine-tuning workflows. RelayPlane is an MIT-licensed npm proxy that intercepts LLM requests for real-time cost control and model routing. Here is how they compare for teams building and governing AI applications.
TL;DR
Choose RelayPlane when you want:
- npm install and running in 30 seconds with no account or SDK setup
- Real-time cost control and model routing in the request path
- Local SQLite cost tracking with no data leaving your machine
- OpenAI-compatible drop-in with one baseURL swap, zero code changes
- Works with Claude Code, Cursor, and any tool you cannot instrument
Humanloop may work for you if you need:
- A visual editor for managing and versioning prompts across your team
- A/B testing prompt variants with automated or human evaluation
- Human feedback collection and annotation workflows
- Fine-tuning pipelines built from collected prompt-response pairs
Feature Comparison
| Feature | RelayPlane | Humanloop |
|---|---|---|
| Product type RelayPlane sits in the critical path of every LLM request: it intercepts, routes, and logs each call transparently. Humanloop is an application-layer platform that wraps LLM calls with its SDK to track prompt versions, collect human feedback, and run evaluations. Humanloop does not proxy or route requests. | npm-native LLM proxy and gateway (local-first) | Prompt management, evaluation, and fine-tuning platform (application-layer SDK) |
| Install method RelayPlane ships as a standalone npm binary: one command and you are proxying requests. Humanloop requires installing its SDK and rewriting your LLM calls to use the Humanloop client instead of calling OpenAI directly. Every prompt must be wrapped in a Humanloop SDK call before it appears in the dashboard. | npm install -g @relayplane/proxy | pip install humanloop (Python) or npm install humanloop (JS), SDK wrapping required |
| No account required RelayPlane starts with zero signup, zero credit card, and zero cloud dependency. Humanloop requires creating an account and obtaining an API key before any prompt tracking or evaluation data is collected. There is no local or offline mode. | ||
| Free tier RelayPlane has no request cap or free tier limit. Humanloop's free tier covers basic prompt management with limited evaluation runs. The Growth plan at $49/month adds more evaluations and collaboration features. Enterprise pricing is custom. | MIT open source, no usage limits, fully free to self-host | Free tier available with limited prompts and evaluations. Growth plan at $49/month. Enterprise pricing on request. |
| No code changes required RelayPlane requires zero application code changes. Set OPENAI_BASE_URL=http://localhost:4100 and your existing code is automatically proxied. Humanloop requires replacing every OpenAI call with a Humanloop SDK call that specifies the prompt slug and version. Existing code must be rewritten to adopt the platform. | ||
| Request interception (proxy mode) RelayPlane intercepts every LLM request transparently via a baseURL swap. No code changes needed beyond pointing your client at localhost:4100. Humanloop requires explicit SDK integration in your application code and does not operate as an HTTP proxy that captures all outbound requests. | ||
| Model routing and fallback RelayPlane routes requests to different models based on complexity and cost, with automatic fallback on provider failures. Humanloop allows selecting a model per prompt in its UI, but does not dynamically route requests or switch providers when one fails. | ||
| Local SQLite cost tracking RelayPlane logs every request's exact dollar cost in local SQLite with no data leaving your machine. Humanloop tracks token usage and cost per prompt call in its cloud dashboard, but this data is stored on Humanloop's servers and requires an active account to access. | ||
| No data leaves your machine RelayPlane runs entirely on localhost by default with zero external telemetry. Humanloop sends all prompt inputs, outputs, and metadata to Humanloop's cloud servers. Every logged call, human feedback rating, and evaluation result is stored in Humanloop's infrastructure. | ||
| Spend governance and budget limits RelayPlane can enforce spend limits and route away from expensive models when budgets are exceeded. Humanloop tracks per-prompt cost in its dashboard but has no mechanism to block, reroute, or cap spending on live requests. | ||
| OpenAI-compatible drop-in RelayPlane exposes an OpenAI-compatible endpoint: set OPENAI_BASE_URL=http://localhost:4100 and your existing code works unchanged. Humanloop requires calling its own SDK methods instead of the standard OpenAI client, so existing code must be adapted to the Humanloop API surface. | ||
| Works with Claude Code and Cursor RelayPlane is designed for Claude Code, Cursor, Windsurf, and Aider with direct integration docs. Humanloop is an application-layer SDK that cannot intercept traffic from AI coding assistants you do not control the source code of. | Not applicable (SDK integration, not a proxy) | |
| Prompt versioning and management Humanloop's core capability is managing prompt versions in a central registry. You can edit prompts in the Humanloop editor, publish new versions, and roll back to previous ones without deploying code. RelayPlane focuses on cost control and routing rather than prompt lifecycle management. | ||
| A/B testing prompts Humanloop supports running experiments that split traffic between prompt variants and comparing outcomes based on human feedback or automated evals. RelayPlane routes based on cost and model capability, not prompt variant experiments. | ||
| Human feedback collection Humanloop provides tools for collecting thumbs-up/thumbs-down ratings, free-text annotations, and structured feedback on LLM outputs. This data feeds into evaluation reports and fine-tuning pipelines. RelayPlane logs request metadata but does not collect human feedback. | ||
| LLM evaluations (evals) Humanloop includes an evaluation framework for running automated checks on LLM outputs: custom code evals, AI-based scoring, and human review workflows. This is central to the Humanloop platform. RelayPlane focuses on cost control and routing rather than output quality evaluation. | ||
| Fine-tuning support Humanloop supports fine-tuning workflows where collected prompt-response pairs and human feedback can be used to fine-tune models. RelayPlane does not have fine-tuning capabilities. | ||
| Open source RelayPlane is MIT licensed end to end. Humanloop is a closed-source SaaS product. There is no self-hosted or open-source edition of the Humanloop platform. | MIT licensed |
Why Teams Choose RelayPlane When They Need Cost Control, Not Just Prompt Management
A proxy intercepts every request. An SDK wrapper only captures what you explicitly instrument.
Humanloop is an application-layer platform: you rewrite your LLM calls to use the Humanloop SDK, and only those wrapped calls appear in the dashboard. If you have existing code, a third-party library, or a tool like Claude Code making LLM requests, Humanloop cannot see or control them. RelayPlane is an HTTP proxy that intercepts all outbound LLM traffic at the network level. Set one environment variable and every LLM call from any application, library, or tool is captured, tracked, and governed without changing a single line of code.
npm install in 30 seconds vs SDK wrapping plus account setup
npm install -g @relayplane/proxy and you are proxying requests. Humanloop requires creating an account, obtaining an API key, installing the SDK (pip install humanloop or npm install humanloop), and rewriting each prompt call to use the Humanloop client. For new projects this is manageable. For existing codebases with hundreds of LLM calls, the migration effort is substantial. RelayPlane's HTTP proxy approach requires no migration: your existing OpenAI or Anthropic client code continues to work unchanged.
Built-in cost control in the request path, not just cost reporting after the fact.
Humanloop tracks the cost of each prompt call in its cloud dashboard, which is useful for understanding which prompts are expensive. But it cannot stop you from spending. RelayPlane tracks cost and can enforce it: budget limits, routing to cheaper models when thresholds are hit, automatic fallback when providers return errors. For agentic workloads that can run for minutes and burn unexpected tokens, having a proxy that caps spending in real time is meaningfully different from a dashboard that shows you what happened after the money was spent.
Use both tools together: RelayPlane for routing, Humanloop for prompt engineering.
RelayPlane and Humanloop address different problems and can complement each other. If your team uses Humanloop to manage prompt versions, run A/B tests, and collect human feedback, you can still run RelayPlane as the proxy layer underneath. RelayPlane handles routing and cost control at the infrastructure level. Humanloop handles prompt iteration and evaluation at the application level. You do not have to choose one or the other if your workflow needs both.
Humanloop Solves Prompt Engineering Problems. RelayPlane Solves Cost Control Problems.
Humanloop is a focused product for prompt engineers and AI product teams who need to iterate on prompts collaboratively, run A/B experiments, collect human feedback, and build evaluation pipelines. Its visual prompt editor, versioning system, and feedback collection workflows make it genuinely useful for teams that ship LLM features and need structured ways to improve prompt quality over time. The Growth plan at $49/month includes more evaluation capacity and team collaboration features suitable for product teams with active prompt development cycles.
But Humanloop cannot route requests, enforce budget limits, or intercept traffic from tools you do not control. It requires rewriting your LLM calls to use the Humanloop SDK. It does not work with Claude Code, Cursor, or other AI coding assistants because those tools do not expose SDK integration points. If you want to start tracking and controlling LLM costs today across any framework, any language, and any tool you use, RelayPlane installs in one npm command and runs on localhost with zero account or code changes required.
Humanloop Pricing at a Glance
| Plan | Price | Account Required | Key Limits |
|---|---|---|---|
| Free | $0/month | Yes | Limited prompts, limited evals |
| Growth | $49/month | Yes | More evals, team collaboration |
| Enterprise | Custom pricing | Yes | SSO, custom contracts, dedicated support |
| RelayPlane | Free (MIT) | No | No caps, no limits, runs on localhost |
Get Running in 30 Seconds
No account. No SDK wrapping. No rewriting your LLM calls: