Set Up LLM Observability Like an Enterprise AI Platform Team
Get full visibility into your AI calls in about two hours of setup.
Download workflow config (JSON)How the data moves
This is a handoff plan, not an automatic integration. Review outputs before the next step. Unlabeled arrows show order, not a verified data format. Use the capability links to explore tool substitutions.
Step 1
Instrument AI Calls for Logging
Add Langfuse to your codebase so every prompt and response gets logged automatically for later review.
Step 2
Track Cost and Latency Per Request
Route your API calls through Helicone to get per-request cost and latency tracking without changing your application logic.
Step 3
Set Up Alerts for Failures and Drift
Configure alerts so you're notified immediately if error rates spike or output quality starts drifting.
Tools
No catalog tool specified
Step 4
Run a Weekly Usage Review
Review the week's logs for unusual spend, latency spikes, or failure patterns worth investigating.
Tools
No catalog tool specified
Time Required
2 hours, one-time setup
Expected Result
Every AI call logged, tracked for cost and latency, and alerting you automatically when something breaks or drifts.
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