OWL by Camel AI

OWL by Camel AI is an open-source framework for building, running, and managing Retrieval-Augmented Generation (RAG) applications with a focus on reproducibility, observability, and evaluation. It provides a structured way to define RAG workflows as composable pipelines, enabling developers to integrate document retrieval, chunking, reranking, and large language model (LLM) generation into a single, testable system. OWL supports multiple vector databases and LLM providers, allowing teams to experiment with different components without changing application logic.

A key capability of OWL is its built-in evaluation and benchmarking tools, which help measure the quality of retrieval and generation using quantitative metrics and human feedback. This enables data-driven iteration on prompts, retrieval strategies, and model choices. OWL also includes tracing and logging features that capture detailed execution metadata, making it easier to debug failures, analyze latency, and understand model behavior in production.