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On the recordRead 5 Oct 202624 facts
Ragas
On the record
- Customization
- Ragas documents options to customize metrics, test set generation, prompts, and model configuration.docs.ragas.io · read 5 Oct 2026
- Custom metrics
- Users can create custom metrics tailored to their use case.docs.ragas.io · read 4 Oct 2026
- Enterprise
- The product site invites inquiries about enterprise features and collaborations by email or a founder meeting.ragas.io · read 4 Oct 2026
- Evaluation coverage
- Documented metrics cover RAG, agent and tool use, factual correctness, SQL, and other tasks.docs.ragas.io · read 5 Oct 2026
- Evaluation workflow
- Ragas supports experiments to evaluate application changes, observe results, and iterate.docs.ragas.io · read 5 Oct 2026
- Experiments
- Its experiments-first approach lets users run evaluations, observe results, and iterate on application changes.docs.ragas.io · read 4 Oct 2026
- Framework integrations
- Documented framework integrations include LangChain, LlamaIndex, Haystack, Griptape, and others.docs.ragas.io · read 5 Oct 2026
- Install
- The quickstart shows installation with uvx or pip and project dependencies with uv or pip.docs.ragas.io · read 4 Oct 2026
- Installation
- Ragas can be installed with pip or from its GitHub main branch.docs.ragas.io · read 5 Oct 2026
- Integrations
- The documentation lists integrations with Arize, LangSmith, Amazon Bedrock, Google Gemini, OCI Gen AI, LangChain, LangGraph, LlamaIndex, and other frameworks.docs.ragas.io · read 4 Oct 2026
- Maker
- The product site identifies founders Shahul and Jithin James and gives Vibrant Labs email addresses; it does not state headquarters or founding year.ragas.io · read 4 Oct 2026
- Metrics
- Users can use available evaluation metrics or create custom metrics.docs.ragas.io · read 5 Oct 2026
- Model providers
- The quick start documents use with OpenAI, Anthropic, Google Gemini, Ollama, and OpenAI-compatible providers.docs.ragas.io · read 5 Oct 2026
- Platform format
- The installation instructions describe installing the Python package and do not list desktop or mobile apps.docs.ragas.io · read 5 Oct 2026
- Product
- Ragas is a library for systematically evaluating large language model applications.docs.ragas.io · read 4 Oct 2026
- Production monitoring
- The product site describes online monitoring to evaluate LLM application quality in production.ragas.io · read 4 Oct 2026
- Provider choice
- The quickstart documents OpenAI, Anthropic Claude, Google Gemini, local Ollama models, and custom providers for evaluation.docs.ragas.io · read 4 Oct 2026
- Purpose
- Ragas is a library for systematically evaluating AI and large language model applications.docs.ragas.io · read 5 Oct 2026
