At a glance
| Alye | Helicone | |
|---|---|---|
| How data is collected | SDK in your service; records are sent in the background | Proxy or AI gateway in the request path |
| Request path | Requests go straight to the provider | Requests pass through Helicone |
| Free plan | 500,000 calls a month, 14 days of history, 3 members | Hobby: 10,000 requests, 7 days of retention, 1 seat |
| Entry paid plan | Team: $49 a month for 10 million calls, then $5 per 100,000; 90 days; unlimited members | Pro: $79 a month, usage-based beyond 10,000 requests; 1 month of retention; unlimited seats |
| Next plan | Enterprise from $500 a month | Team: $799 a month, 3 months of retention |
| Regional and marketplace prices | Azure OpenAI, Vertex AI and Bedrock by region | Not listed on its pricing page |
| Caching and gateway features | Not offered | Yes, including caching |
| Alerts | Spend, forecast, error rate, latency and silent services, to Slack, Teams or email, checked every minute | Alerts and reports on Pro |
Which one to choose
Choose Helicone if
- You want to start by changing one URL, without adding a library.
- You want gateway features such as caching in the same tool.
- You want to self-host.
Choose Alye if
- You don't want another hop in front of your model provider.
- You need cost per customer and per service, not just per request.
- You need correct regional prices and alerts in Slack or Teams.
- Your volume is high: 10 million calls a month for $49.
Why the request path matters
With a proxy, every model request waits on one more service, and an outage there can stop your AI features unless you build a fallback. With an SDK, Alye records each call after it happens and sends the record in the background; if Alye is slow or down, your requests carry on as normal.
Also compared: Alye vs Langfuse · Alye vs LangSmith. New to the topic? Start with what LLM observability is.