Langfuse Has a Free LLM Observability Platform — Monitor AI App Costs and Quality

Langfuse is an open-source LLM engineering platform for tracing, evaluation, and prompt management.

What You Get for Free

• Tracing — trace every LLM call with inputs, outputs, latency, cost
• Cost tracking — per-request and aggregate cost monitoring
• Prompt management — version control prompts, A/B test
• Evaluation — score outputs manually or with LLM-as-judge
• Datasets — create test datasets for regression testing
• User feedback — collect thumbs up/down from end users
• Metrics dashboard — latency, cost, token usage, quality scores
• Integrations — OpenAI, LangChain, LlamaIndex, Vercel AI SDK
• Self-hosted — free, unlimited traces
• Cloud free tier — 50K observations/month

Quick Start

# Cloud: cloud.langfuse.com (free tier)

# Self-hosted
git clone https://github.com/langfuse/langfuse.git
cd langfuse
docker compose up -d

from langfuse.openai import openai

# Drop-in replacement — same API, automatic tracing
response = openai.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello"}]
)
# Every call is traced: latency, cost, tokens, input/output

Why AI Teams Need It

Without observability, LLM apps are a black box:

• Cost surprises — one bad prompt loop can cost $100+ in API calls
• Quality regression — model updates silently degrade output quality
• Debugging — trace exact prompts and responses for failures

An AI startup's GPT-4 costs jumped from $200/mo to $1,400/mo. Langfuse tracing revealed a retry loop was calling the API 7x per request. They fixed the bug and costs dropped back — a $1,200/mo bug found in 5 minutes.

---

Need Custom Data Solutions?

I build production-grade scrapers and data pipelines for startups, agencies, and research teams.

Browse 88+ ready-made scrapers on Apify → — Reddit, HN, LinkedIn, Google, Amazon, and more.

Custom project? Email me: [e-mail] — fast turnaround, fair pricing.