Build, troubleshoot, and optimize robust agentic systems.

Monitor, evaluate, and improve RAG pipelines with full-stack observability from Arize and seamless integration with MongoDB Atlas.

Unified AI Engineering Platform to Make AI Work

The Gold Standard for RAG Storage & Retrieval

MongoDB Atlas powers your RAG applications with fast, flexible vector search and semantic indexing—backed by the scalability of a developer-first cloud data platform.

End-to-End Tracing & Evaluation

With Arize Phoenix, you get granular observability across your RAG stack—from document retrieval to generation output—plus LLM-as-a-Judge evaluations and diagnostics.

Bring Transparency To Every Step of Your RAG Pipeline

Arize provides end-to-end observability that lets engineers trace data flow across complex architectures like RAG, from input to final output.

Why use Arize and MongoDB together

RAG-Ready Observability

Trace the full chain of your RAG pipeline—from the input query to retrieval results stored in MongoDB, to the final LLM output—along with relevant metadata.

Evaluation With Context

Use Phoenix to automatically evaluate output quality using LLM-as-a-judge, custom metrics, or human-in-the-loop workflows.

Faster Debugging & Iteration

Quickly identify where things go wrong—bad queries, poor retrieval, hallucinated outputs—and improve your application with targeted insights.

Test Memory and Retrieval Performance with MongoDB + Arize

Start your AI observability journey.

Get in touch with our team of AI observability experts to see how Arize and Databricks can work together for your business.

Evaluation Driven Development

Purpose-built tools and workflows that streamline performance improvement iteration cycles

Test Changes As You Build

Prompt template versioning and a prompt playground enable testing as you go, along with the ability to replay use cases in production.

Quickly Find and Curate Datasets

AI-driven search and embeddings similarity search eliminates manual data curation and annotation in your daily workflow.

Guardrails to Protect Your Business

Dynamic data used for detection of activities such as jailbreaks, PII leaks, or user frustration – then respond with a corrective action.

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