AI Agent Monitoring Platforms Compared 2026: LangFuse vs Datadog vs Helicone

AI agents differ from web apps: a web app crashes with a 500, an agent silently does the wrong thing. This compares three LLM observability platforms - LangFuse (31,224 stars, open-source standard), Datadog (built on existing APM), and Helicone (leanest proxy option) - with pricing and team fit.

💡 What You Will Learn

AI agents differ from web apps: a web app crashes with a 500, an agent silently does the wrong thing. This compares three LLM observability platforms - LangFuse (31,224 stars, open-source standard), D

📜 Table of Contents

• LangFuse (31,224 stars)
• Datadog AI Monitoring
• Helicone (5,949 stars)
• LangSmith
• Comparison Table

AI agents are different from traditional web apps. A web app crashes or returns 500. An AI agent silently does the wrong thing -- calls a wrong function or hallucinates.

LangFuse (31,224 stars)

LangFuse is the de facto standard for open source LLM observability. Key features: - Full trace visualization for multi-step agent chains - Cost tracking per model, user, session - Evaluation scores for output quality - Self-hosted or cloud Best for: Teams wanting full LLM observability without vendor lock-in. Pricing: Open source (self-hosted free). Cloud: $59/month.

Datadog AI Monitoring

Datadog entered LLM observability in late 2025. It piggybacks on existing APM. Key features: - LLM call traces integrated with Datadog APM - Token usage dashboards - Alerting on cost spikes and latency Best for: Teams already on Datadog.

Helicone (5,949 stars)

Helicone is the leanest option -- a proxy between your app and LLM provider. Key features: - Zero-code setup (change endpoint URL only) - Real-time cost tracking - Request/response logging with PII redaction Best for: Small teams wanting running in 5 minutes. Pricing: Open source. Cloud: free tier (10K req/month).

LangSmith

LangChain official monitoring platform. Best for: Teams already using LangChain.

Comparison Table