LLM Observability

Expedite Troubleshooting of Your LLM Applications

Gain full visibility into end-to-end traces for each user request, allowing you to quickly pinpoint the root causes of errors and failures in your LLM chain
Analyze inputs and outputs at each step of the LLM chain to quickly resolve issues such as failed LLM calls, task interruptions, and service interactions
Improve the accuracy and relevance of your LLM outputs by identifying and correcting errors in the embedding and retrieval steps, and optimize the performance of Retrieval-Augmented Generation (RAG) systems

Optimize resource use and reduce costs across all major LLMs with key operational metrics, including cost, usage patterns, and latency trends
Swiftly take action to maintain optimal performance of LLM applications with real-time alerts on anomalies, such as spikes in latency or errors
Instantly uncover opportunities for performance and cost optimization with comprehensive data on latency and token usage across the entire LLM chain

Easily spot and address quality concerns, such as missing responses or off-topic content, with turnkey quality evaluations
Enhance business-critical KPIs, and detect hallucinations, by implementing custom evaluations that accurately assess and improve the performance of your LLM applications
Automatically detect drifts in production and optimize your LLMs by isolating and addressing low-quality prompt-response clusters with similar semantics

Protect user privacy by preventing the exposure of sensitive data, including PII, emails, and IP addresses, with built-in security measures powered by Datadog's Sensitive Data Scanner
Defend your LLM applications from response manipulation attacks with automated flagging of prompt injection attempts