Evaluate GenAI Quality with Confidence
RagMetrics helps GenAI teams validate agent responses, detect hallucinations, and accelerate deployment with AI-assisted QA and human-in-the-loop feedback.
.png)
Why AI Evaluations Matters
Hallucinations erode trust in AI
65% of business leaders say hallucinations undermine trust.
Manual evaluation process doesn’t scale
Automated review cuts QA costs by up to 98%.
Enterprises need proof before deploying GenAI agents
Over 45% of companies are stuck in pilot mode, waiting on validation.
Product teams need rapid iteration
Only 6% of lagging companies ship new AI features in under 3 months.
The Purpose-built Platform for AI evaluations
AI-assisted testing and scoring of LLM / agent output
Reduced hallucinations and accurate outputs.
Human-in-the-loop workflows
Scale your existing AI development team.
Failure detection and quality dashboards
Quickly address issues before they impact the customer.
Testing and Retrieval
Use data-driven insights to improve AI pipelines. Fine-tune the retrieval strategy and understand the changes in performance.
Flexible and Reliable
LLM Foundational Model Integrations
Integrates with all commercial LLM Foundational models, or it can be configured to work with your own.
200+ Testing Criteria
With over preconfigured criteria and flexibility to configure your own, you can measure what is relevant for you and your system.
AI Agentic Monitoring
Monitor and trace the behaviors of your agents. Detect if they start to hallucinate or drift from their mandate.
Deployment Cloud, SaaS, On-Prem
Choose the implementation model that fits your needs -– cloud, SaaS, on-prem. Stand Alone GUI or API model.
AI Agent Evaluation and Monitoring
Analyze each interaction to provide detailed ratings and monitor compliance and risk.
The RagMetrics AI Judge
Overview: Ragmetics connect to foundational LLM models in the Cloud, SaaS, and on-prem, allowing developers to evaluate new LLMs, agents, and copilots before they go to production.
What Client Say About Us
Hear what our clients have to say about their experience working with us. Real stories, real results, real impact.
I was thrilled to see this graph from Aubrey Kayla and Alon Bochman at RagMetrics yesterday. It demonstrates that our RAG methodology at Tellen employing techniques from semantic search to LLM-based summarization significantly outperforms GPT-4 and all other large language models. Excited to boost these numbers by both leveraging more sophisticated RAG—HyDE, reranking, etc. and other language models, for which we're already building private endpoints in Microsoft Azure. Seems Llama3 could be a good bet!
I have had the pleasure to work with RagMetric's founders Alon and Aubrey. They are very knowledgeable on the areas of AI, LLM, as well as business. They know that a successful product is more than just technology. The results provided by RagMetrics are helpful for any AI product development and the company is very open to feedback and customizations. I would recommend anyone with an AI application to look into what RagMetrics can do for their use case.
Frequently Asked Questions
Yes, we do.
Yes, we can run as a hosted service, on-prem, or on a private cloud.
It's as easy aconnecting your pipeline, your public model (Anthropic, Gemini, OpenAI, DeepSeek, etc.), creating a task, labeling a dataset, selecting your criteria, and starting to run an experiment!
Your public API keys, the endpoint of your pipeline, a source of domain expertise for your labelled data, and a concrete description of the task of your model, as well as your own criteria of success!
Yes, it's as easy as copying and pasting your endpoint URL.
Validate LLM Responses and Accelerate Deployment
RagMetrics enables GenAI teams to validate agent responses, detect hallucinations, and speed up deployment through AI-powered QA and human-in-the-loop review.
Get Started%201.svg)
