Full visibility into your LLM pipelines

LLM observability

Full visibility into your LLM pipelines

Trace system behavior, monitor cost and latency, and catch failures before your users do.

Core features

Explore the platform

Trace every interaction

Get full visibility into every step of your LLM pipeline, from initial prompts to intermediate tool calls and final responses.

Monitor your live system

Keep tabs on prompt injection, toxic output, and data leaks. Continuously run safety and performance tests on live requests.

Instant alerts

Receive real-time notifications when something breaks—whether it’s latency spikes, hallucinations, or inappropriate content.

Track latency and cost

Identify bottlenecks or expensive operations across RAG, agent workflows, and retrieval systems. Optimize where it matters.

Why it matters

When LLM systems fail, your reputation is at risk

From toxic outputs to latency spikes and cost overruns, LLM-based systems present unique production challenges. Observability helps you trace, debug, and optimize your GenAI pipelines before things escalate.

Use cases

Observability for dynamic LLM workflows

Whether you're orchestrating agents, building retrieval-augmented generation (RAG) systems, or fine-tuning internal copilots, Openlayer gives you full visibility into system behavior, cost, and latency.

Why Openlayer

Built for modern GenAI operations

Monitor from individual LLM calls to system-levelTrack every prompt, chain, and end-to-end flow in real time to spot issues instantly.

Built-in support for tracing, cost, and latencySee token-level traces, dollar spend, and response times side-by-side—no extra tooling required.

Lightweight integration with LangChain, LlamaIndex, and moreInstrument your pipelines with just a few lines of code and keep your stack flexible.

Designed for RAG, agents, and tool-calling systemsMeasure retrieval quality, agent reasoning steps, and tool calls right out of the box.

Integrations

Works across your GenAI stack

Openlayer integrates with OpenAI, LangChain, Anthropic, OpenTelemetry, and more. Connect to tracing tools and cloud infra. Deploy with zero vendor lock-in.

Customers

Visibility that builds trust

“We debugged a prompt injection issue in minutes—not days. Our GenAI systems are safer because of Openlayer.”

VP of Engineering at Healthcare Institution

FAQs

Your questions, answered

What is LLM observability?

LLM observability is the practice of monitoring, tracing, and debugging GenAI systems in production to ensure quality, safety, and performance.

What can I trace with Openlayer?

Prompts, tool calls, latency, cost, model responses, and failure modes across chained workflows.

Does this work with agentic and RAG systems?

Yes, Openlayer supports tracing and monitoring across multi-step and retrieval-based systems.

Can I set up cost and latency thresholds?

Absolutely. You can create custom tests or alerts based on performance and efficiency metrics.

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LLM observability