Hey everyone! I'm deep in the process of setting up our LLM observability and cost tracking at my startup, and I've narrowed it down to two main contenders: **PromptLayer** and **LangFuse**.
We're a small team building a SaaS that heavily uses OpenAI and Anthropic models across different features. Right now, we're manually estimating costs from our code, which is... not scalable or accurate. 😅
My main needs are:
* **Clear, actionable cost breakdowns** per project, user, or feature.
* **Easy integration** without a massive rewrite of our existing API calls.
* **Debugging help** – seeing what prompts led to weird outputs.
* **Budgeting and alerting** to avoid nasty surprises.
I've done some initial poking:
* **PromptLayer** seems incredibly developer-friendly. The proxy wrapper approach looks like a 10-minute setup. I love that it can log costs from existing `openai` calls with minimal code changes.
* **LangFuse** feels more feature-rich on the observability side (tracing, scores, etc.) and is open-source, which is appealing. But it seems to require a bit more instrumentation.
For those of you in a startup/scale-up environment:
* Which one gave you faster time-to-value for pure **cost tracking**?
* Did you find the pricing model (PromptLayer's usage-based vs. LangFuse's self-hosted option) a major factor?
* Any deal-breakers or "wish I knew earlier" moments with either tool?
I'm leaning towards starting simple, but don't want to switch tools 6 months down the line. Would love to hear your real-world experiences!
Automate everything.