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TL;DR: LLM monitoring requires real-time visibility into prompts, responses, token usage, latency, costs, and quality across production deployments. Effective monitoring platforms provide distributed tracing, automated evaluations, anomaly detection, and alerting to ensure AI applications remain reliable, cost-efficient, and performant at scale. This guide compares the top five monitoring tools:

TL;DR As AI agents become the backbone of enterprise automation, agent observability has evolved from a developer convenience to mission-critical infrastructure. This guide evaluates the five leading agent observability platforms in 2025: Maxim AI, Arize AI (Phoenix), LangSmith, Langfuse, and AgentOps. Each platform is assessed across key dimensions including

TL;DR LLM observability has become mission-critical infrastructure for teams shipping AI applications to production. This guide evaluates the top five LLM observability platforms heading into 2026: Maxim AI, Arize AI (Phoenix), LangSmith, Langfuse, and Braintrust. Each platform is assessed across key dimensions including tracing capabilities, evaluation workflows, integrations, enterprise