Every token, latency, and dollar attributed to the exact agent node that spent it. Unlimited traces on every plan — retention is the only paid axis.
| FUNCTION | MODEL | LATENCY | COST | SOURCE |
|---|---|---|---|---|
| answer_question | gpt-4o | 1,243ms | $0.012 | LangChain |
| search_docs | claude-3.5-s | ⚡ cached | $0.000 | Cached |
| generate_report | gpt-4o | 2,108ms | $0.041 | OpenAI |
| classify_intent | gemini-1.5 | 890ms | $0.005 | |
| answer_question | gpt-4o | 1,540ms | $0.019 | LangChain |
Attribution
Token counts and USD cost at live provider rates, attributed down to the span that spent them.
Latency
Latency histograms per agent and per model, so you watch the tail, not just the average.
Multi-agent
Fan-outs, joins, and loop-backs across LangGraph, CrewAI, and Google ADK render as the graph your agents actually executed.
Live
Traces land on the dashboard as calls complete. Watch a run unfold instead of refreshing.
import fluiq
fluiq.instrument(api_key="fl_...")
@fluiq.trace
def answer(question: str) -> str:
docs = store.search(question, k=5)
return llm.invoke(prompt(question, docs))
# Traced with cost, latency, and a full span treeStart on the free tier and turn on each pillar as your pipeline grows. No code changes required.