FluiqFluiq
  • ObservabilityTrace every call, cost, and latency
  • SecurityBlock attacks, redact PII and secrets
  • OptimizationCache repeated prompts automatically
  • EvaluationScore responses and whole agent runs
  • DatasetsGolden sets that capture whole agent runs
  • Prompt ManagementVersion and deploy prompt templates
  • AlertsPush eval and security events to Slack

LLM Providers

  • OpenAI
  • Anthropic
  • Google Gemini
  • Google Vertex AI

Agent Frameworks

  • LangChain
  • LangGraph
  • CrewAI
  • Google ADK
  • MCP

Vector Databases

  • Pinecone
  • Chroma
  • Weaviate
  • FAISS
  • Qdrant
14 integrations · zero wrappersView all
Pricing
  • Fluiq DocsGuides, concepts & SDK reference
  • Code SamplesCopy-paste integration snippets
  • LLM Cost CalculatorCompare OpenAI, Claude & Gemini pricing
Contact
LoginStart free
Observability

Full trace visibility across every LLM call

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.

Start freeRead the docs
Fluiq/ traces
247 rpm · live
All modelsAny statusAny security247 traces
FUNCTIONMODELLATENCYCOSTSOURCE
answer_questiongpt-4o1,243ms$0.012LangChain
search_docsclaude-3.5-s⚡ cached$0.000Cached
generate_reportgpt-4o2,108ms$0.041OpenAI
classify_intentgemini-1.5890ms$0.005Google
answer_questiongpt-4o1,540ms$0.019LangChain

What you get

Attribution

Per-node token and cost

Token counts and USD cost at live provider rates, attributed down to the span that spent them.

Latency

p50 / p95 / p99

Latency histograms per agent and per model, so you watch the tail, not just the average.

Multi-agent

Real DAGs, not flat lists

Fan-outs, joins, and loop-backs across LangGraph, CrewAI, and Google ADK render as the graph your agents actually executed.

Live

Real-time streaming

Traces land on the dashboard as calls complete. Watch a run unfold instead of refreshing.

One decorator turns any call into a span.

  • Patches OpenAI, Anthropic, Gemini, LangChain, and vector stores automatically
  • Nested calls build a full span tree with parent and child timing
  • Cost is computed at live provider rates, per model
Free · unlimited on every plan
app.py
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 tree

Part of the Fluiq platform

Compare plans
SecurityBlock attacks, redact PII and secrets.ExploreOptimizationCache repeated prompts automatically.ExploreEvaluationScore responses and whole agent runs.ExploreDatasetsGolden sets that capture whole agent runs.ExplorePrompt ManagementVersion and deploy prompt templates.ExploreAlertsPush eval and security events to Slack.Explore

Unlimited traces, always free.

Start on the free tier and turn on each pillar as your pipeline grows. No code changes required.

Start freeRead the docs
FluiqFluiq

Observe, protect, optimize, evaluate.

PlatformObservabilitySecurityOptimizationEvaluationDatasetsPrompt ManagementAlerts
CompanyIntegrationsPricingDocsCost CalculatorBlogContact
Comparevs LangSmithvs Langfusevs Heliconevs Braintrustvs Portkeyvs Lakera
IntegrationsOpenAIAnthropicLangChainCrewAIPineconeView all →