“Looking at the traces in Langfuse, I saw that running a single LLM call wasn't reliable enough.”
Langfuse for workflow automation
Use case / workflow automation
Buildreliableautomation agents
Workflow automation includes dozens of steps across systems and frameworks. Trace the full execution, track cost at every step, and continuously include human expertise to improve your system.
ingest_pdf
ocr_pages ×14
extract_fields
reconcile_retry ×3
$0.061
post_to_erp
one retry step · 66% of run cost
Trace the full execution across systems
Trace every step, tool call, and input and output your agent produces. Add deep links to and from your product to easily debug traces. Find failure modes and bottlenecks across executions, then prioritize issues by how often they happen so you fix what actually matters.
Tracing overview →Teams improving workflow automation agents on Langfuse
Any system,any workflow
Trace n8n, Temporal, LangGraph, and no-code builders through native integrations or OpenTelemetry — nothing else in your stack changes.
Agent frameworks
Need another framework? Browse all 80+ integrations →
Learn from real automation examples
Start tracing a full application, evaluate structured extraction, and study patterns for multi-step LLM systems.
Get started with tracing
Ingest your first trace and see a full application run in Langfuse.
Structured output extraction cookbook
Evaluate document and claim extraction per field, then improve the pipeline with experiments.
Observability in multi-step LLM systems
How to debug, evaluate, and test applications that chain many LLM and tool steps.
Ready to build reliable automation agents?
Use traces, cost analytics, and human review to observe and improve every workflow run with Langfuse.
No credit card required · Free tier available · Self-hosting option
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