Keywords AI
Datadog LLM vs DeepEval
Compare Datadog LLM and DeepEval side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Enterprise | — |
| Best For | Enterprise teams already using Datadog who want to add LLM monitoring | — |
| Website | datadoghq.com | deepeval.com |
| Key Features |
| — |
| Use Cases |
| — |
When to Choose Datadog LLM vs DeepEval
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
About Datadog LLM
Datadog's LLM Observability extends its industry-leading APM platform to AI applications. It provides end-to-end tracing from LLM calls to infrastructure metrics, prompt and completion tracking, cost analysis, and quality evaluation—all integrated with Datadog's existing monitoring, logging, and alerting stack. Ideal for enterprises already using Datadog who want unified observability across traditional and AI workloads.
About DeepEval
DeepEval is an open-source LLM evaluation framework built for unit testing AI outputs. It provides 14+ evaluation metrics including hallucination detection, answer relevancy, and contextual recall. Integrates with pytest, supports custom metrics, and works with any LLM provider for automated quality assurance in CI/CD pipelines.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evals tools →