LLM operations and observability
LLM applications do not fail by crashing; they fail by answering plausibly and wrongly. If you cannot reconstruct what the system saw before it answered, you cannot fix it.
Published · updated
How we ranked these
Stated before the list, so you can disagree with the weighting rather than the result.
The ranking
- 01
Langfuse4.6$29/mo
Open-source tracing, evaluation and prompt management for LLM apps, with a self-hosted option that costs nothing to license.
Add it before the first production incident rather than after. Self-host if the prompts are sensitive.
- 02
Helicone4.3$79/mo
Open-source LLM observability with a gateway that adds caching and provider fallbacks.
Good value when cost and reliability are the concerns. Pair it with a dedicated evaluation tool if quality is.
- 03
Portkey4.3$49/mo
A control panel for production AI: gateway, observability, prompt management and guardrails in one place.
Worth it once LLM features are in production and spend is real. Premature before that.
- 04
Braintrust4.4$249/mo
Evaluation infrastructure for AI systems: production traces and offline eval sets live in the same place.
Worth it once LLM output quality is something you have to defend. Build the evaluation set first.
- 05
LlamaIndex4.5$50/mo
Document parsing, extraction and indexing as a service, alongside the open-source framework of the same name.
Strong for table-heavy documents. Verify the extraction manually before trusting it downstream.
- 06
Unstructured4.3$0.015/ページ
Turns PDFs and internal documents into something a model can actually read, with ETL pipelines included.
Test it on your ugliest PDFs. If they come out clean, the per-page cost is cheap.
- 07
Firecrawl4.5$19/mo
Fetches web pages in a shape models can read, through scrape, crawl and search endpoints.
Good value for RAG ingestion. Model the credit cost before a large crawl.
- 08
Browserbase4.4$20/mo
Cloud browsers for agents that need to click through the web, with the Stagehand SDK on top.
Worth it the moment browser automation becomes more than a script. The free tier shows you quickly.
- 09
E2B4.4$150/mo
Isolated sandboxes for running AI-generated code, billed per second of vCPU and RAM.
The right default for code execution agents. Check the CPU-only constraint against your design.
Questions we get
- When should we add this?
- Before the agent reaches production. Most teams add it after a problem, at which point the traces for that problem do not exist. Langfuse's free tier covers a small production app, so there is nothing to wait for.
- RAG answers are poor — where do we look?
- Preprocessing, not the prompt. If a three-column PDF parsed into nonsense, no prompt recovers it. Inspect the parse output in Unstructured or LlamaIndex before touching retrieval.
- Where should generated code run?
- In an isolated sandbox with a time limit and no route to your infrastructure. Not on your laptop.