See what your models are doing—and why.
Openlayer provides end-to-end observability for AI systems in production.
What Is AI observability?
It’s more than just monitoring
AI observability is about understanding why models behave the way they do—not just whether they’re working.
Observability for AI systems
Built for the complex reality of modern AI
Whether you’re deploying tabular models, fine-tuned LLMs, or chaining prompts through agents—Openlayer helps you see every step of the system in real time.
Live tracing and evaluation
Version comparisons and rollback insight
Cost, latency, and anomaly diagnostics
Prompt and response monitoring
Openlayer's approach to AI observability
Granular, continuous, and actionable insights
Whether you’re deploying tabular models, fine-tuned LLMs, or chaining prompts through agents—Openlayer helps you see every step of the system in real time.
Where Openlayer fits
Observability as a native layer, not an afterthought
Unlike generic monitoring platforms, Openlayer was built for AI. We provide visibility into things that actually matter—like prompt quality, model regressions, or output reliability.
Deployed alongside your inference stack. Compatible with LangChain, Kubernetes, LLM providers, and more.
Who it's for
ML engineers, LLM builders, and platform teams
Whether you manage a handful of models or operate critical AI infrastructure, Openlayer makes observability scalable, testable, and explainable. Built for teams shipping any kind of AI task.
Tabular models
NLP and vision models
Foundation models and LLM agents
FAQs
Your questions, answered
$ openlayer push