Keywords AI

Datadog LLM vs Patronus AI

Compare Datadog LLM and Patronus AI side by side. Both are tools in the Observability, Prompts & Evals category.

Quick Comparison

	Datadog LLM	Patronus AI
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Enterprise	Enterprise
Best For	Enterprise teams already using Datadog who want to add LLM monitoring	AI teams that need rigorous, automated quality evaluation and safety testing
Website	datadoghq.com	patronus.ai
Key Features	LLM monitoring within Datadog platform Unified APM + LLM observability Automatic instrumentation Cost and token tracking Integration with existing Datadog dashboards	Automated LLM evaluation platform Hallucination detection RAG-specific evaluation metrics Red-teaming capabilities CI/CD integration
Use Cases	Unified monitoring for AI and traditional services Enterprise LLM monitoring at scale Correlating LLM performance with infrastructure Compliance and audit logging Large-scale production monitoring	Detecting hallucinations in production RAG quality evaluation Adversarial testing of LLM systems Continuous evaluation in CI/CD Model comparison and selection

When to Choose Datadog LLM vs Patronus AI

Choose Datadog LLM if you need

Unified monitoring for AI and traditional services
Enterprise LLM monitoring at scale
Correlating LLM performance with infrastructure

Pricing: Enterprise

Choose Patronus AI if you need

Detecting hallucinations in production
RAG quality evaluation
Adversarial testing of LLM systems

Pricing: Enterprise

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.

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About Patronus AI

Patronus AI provides automated evaluation and testing for LLM applications. The platform detects hallucinations, toxicity, data leakage, and other failure modes using specialized evaluator models. Patronus offers pre-built evaluators for common use cases and supports custom evaluation criteria, helping enterprises ensure AI safety and quality before and after deployment.

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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 →