I have been working with LangSmith for several months and it has served me well for simple monitoring and prompt management. However, my projects are getting more sophisticated now, particularly when dealing with autonomous agents and retrieval-augmented generation setups. The current tooling feels restrictive for my growing needs.
I need something more robust that can handle advanced testing scenarios and comprehensive monitoring capabilities. Real-time notification systems would be extremely helpful for my workflow.
Does anyone have recommendations for platforms that excel in these areas? I would especially appreciate suggestions that integrate smoothly with retrieval-augmented generation architectures or offer instant alerting features out of the box.
Phoenix by Arize has been a game-changer for monitoring our autonomous agents. We switched from LangSmith four months ago when our multi-agent systems went haywire in production. Phoenix catches issues other tools completely miss - especially drift detection and hallucination patterns in complex RAG pipelines. The observability stack plays nice with most vector databases and gives you detailed insights when retrieval quality tanks. What sold me? It can trace conversation flows across multiple agents without losing context during handoffs. Their anomaly detection actually works for real-time alerts, unlike the basic threshold junk everywhere else. We catch embedding issues and retrieval failures before users even notice. Learning curve isn’t bad, and if you’re already doing OpenTelemetry instrumentation, integration is straightforward.
Promethium Labs has been rock solid for me. Made the switch 3 months ago after LangSmith kept crashing on our retrieval chains. Their testing framework gets agent workflows - doesn’t just treat everything like simple LLM calls. The notifications are good too, they’ll catch your RAG pipeline hallucinating before it becomes a real issue.
Been there - scaled our RAG systems last year and LangSmith crapped out fast once we got past basic stuff.
Go with LangFuse. We made the switch 6 months ago and it crushes complex agent workflows. Tracing goes deep enough to actually debug multi-step retrieval chains, plus their alerts caught production issues LangSmith would’ve missed completely.
If you’re doing heavy experimentation, check out Weights & Biases too. Their prompt tracking and A/B testing are solid, just expect a steeper learning curve.
Pro tip - whatever you choose, make sure it handles retrieval latency spikes without losing its mind. Our first monitoring tool threw false alerts every time the vector database hiccupped. Total nightmare.
Don’t sleep on notifications either. LangFuse lets you set custom thresholds for pretty much anything. LangSmith’s basic alerts are garbage in comparison.
Wandb Weave is worth checking out if LangSmith isn’t cutting it anymore. I switched our agent setup 8 months ago and it’s been great. The evaluation stuff handles tricky retrieval cases way better than other tools I’ve tried - especially when you’re dealing with multi-hop reasoning or need to check semantic consistency across different retrieval contexts. It plays nice with our existing MLOps setup, which was huge since we already had tons of monitoring in place. Debugging is where it really shines - you can actually follow agent decision paths and pinpoint exactly where retrieval starts falling apart. The real-time monitoring caught several edge cases in our RAG system that would’ve been disasters in production. Takes about 2 hours to set up if you know what you’re doing, and their Python SDK doesn’t clash with existing instrumentation like some other options.