Keywords AI
Confident AI vs Datadog LLM
Compare Confident AI and Datadog LLM side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Open Source | Enterprise |
| Best For | Developers who want to add automated LLM evaluation testing to their CI/CD pipeline | Enterprise teams already using Datadog who want to add LLM monitoring |
| Website | confident-ai.com | datadoghq.com |
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When to Choose Confident AI vs Datadog LLM
- Unit testing LLM applications
- Automated evaluation in CI/CD pipelines
- Benchmarking across model versions
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
About Confident AI
Confident AI develops DeepEval, the most popular open-source LLM evaluation framework. DeepEval provides 14+ evaluation metrics including faithfulness, answer relevancy, contextual recall, and hallucination detection. The Confident AI platform adds collaboration features, regression testing, and continuous evaluation in CI/CD pipelines.
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.
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 →