Helicone (YC W23)

Drop-in proxy for LLM logs, costs, and routing

Some setup needed Web · API

About

Swap your LLM API base URL and start capturing every prompt, response, and token in a consistent format. Teams use it to monitor production LLM traffic, track costs across 100+ providers, and debug issues without adding heavy SDKs. The single proxy endpoint keeps multi-model comparisons and cost/latency routing straightforward.

Editor's Take

We recommend Helicone for engineering teams that need fast, low-friction observability and multi-provider routing for LLM traffic; it's best suited for monitoring costs, latency, and debugging rather than full model training or deployment pipelines.

Key Features

Change your LLM base URL to Helicone → all requests and responses are logged in a unified schema
Send traffic through the gateway → token-level analytics and model-by-model cost reports appear
Route across 100+ providers → compare quality, latency, and price without rewriting your app
Attach metadata to each call → trace user journeys and segment performance by customer or feature
Enable caching and routing rules → reduce latency spikes and control spend during peak usage

Use Cases

An ML engineer launching a chat assistant and needing per-user cost tracking and failure debugging in the first week
A platform engineer evaluating models across providers to balance latency and price before a production rollout
A product manager reviewing token usage and error trends to prioritize prompt and model changes after a feature launch

Try It Like This

1
Track per-user cost for a chat assistant
Sign up and point your app's LLM base URL to the Helicone proxy → Helicone logs each request and response with metadata (user_id, session, feature) → open the dashboard to filter by user_id and view token-level costs and error rates for that user.
2
Compare multiple models for latency and price
Configure routing rules to send traffic to two different providers/models through Helicone → run a controlled test (same prompts) and collect requests through the gateway → use the model-by-model cost and latency reports to decide which model fits your SLA and budget.
3
Debug production failures quickly
Enable unified logging so every prompt/response is captured in a consistent schema → reproduce the failing request path and find the logged entry with the error and full response payload → inspect metadata and tokens to trace root cause and rollback or patch prompts.
4
Reduce spend during peak traffic
Attach feature or customer metadata to calls, then create routing/caching rules in Helicone to throttle or cache noncritical prompts → during peaks route lower-priority traffic to cheaper models or cached responses → monitor token-usage dashboards to verify spend drops.
5
Audit model behavior across features
Tag calls by product feature when sending through the gateway → collect unified logs and run token-level analytics per feature → use the reports to prioritize prompt fixes or model swaps for the features causing highest cost or errors.

Pros & Cons

Pros

Proxy-based integration captures every request and response in a unified schema without heavy SDK changes, enabling fast time-to-logging.
Supports routing across 100+ providers, making multi-model comparisons and cost-based routing straightforward without rewriting application code.
Provides token-level analytics and model-by-model cost reports so teams can monitor spend and latency at high granularity.

Cons

Focused on observability and gateway controls rather than full MLOps features (e.g., model training/deployment pipelines), so teams needing end-to-end MLOps may need additional tools.
Pricing includes subscription tiers plus usage-dependent components, which can complicate cost forecasting for high-volume workloads.

Getting Started

1 Visit docs.helicone.ai and create an account (open-source repo available on GitHub).
2 Point your app’s LLM API base URL to Helicone and send a test request with metadata headers.
3 Open the Helicone dashboard to see the request log, token usage, and cost by model within minutes.