RagMetrics | LLM Application Evaluation

Key Features

Best AI LLM Judge of the Market

95% Human-LLM agreement, so you can step out of the loop.

Custom Performance Metrics

Measure success on your task, not on some leaderboard.

A/B Testing

Improve your pipeline (model, prompt, agent, vector database, etc.) with data, not just gut feel.

Retrieval Optimization

When the stakes are high, retrieval is 80% of the battle.

Prove your ROI to customers and investors

We help you define a KPI for your use case, and then measure that KPI for standalone models and within your pipeline. The difference between those is your value-add.

Illustration of language model selection process

Pick the right language model

We help you make smart tradeoffs among multiple KPIs, such as answer quality, latency, cost, and >1,000 other metrics.

Automated Evaluation Loop

Labeling data and judging LLM responses by hand doesn't scale. Our synthetic data generation and judge-LLMs allow you to iterate and get to production faster.

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Why You'll Love Us

Compatible with all LLMs, commercial
and open-source

Works with your model. Helps you upgrade with
confidence. For example, from GPT4-Turbo to
GPT4o

Works with your code

No loss in flexibility or control

Over 1,000 rubrics to choose from

Pick the right north-star for your use case.

Detailed analytics

Make smart tradeoffs between quality, latency,
and cost

LLM as a judge with rationale and high
user agreement

Scalable and affordable evaluation for unstructured text outputs. Click here to see our study on human agreement.

Synthetic-labeled data generation

Don't block on data availability or domain experts.
Save time and money vs third-party data labelers.

Let's Talk

A bit about us

Alon Bochman

Chief Executive Officer

Product leader with 20+ years in DS/ML/AI

Olivier Cohen

Chief Business Officer

20+ year leadership in technology companies

What Our Customers Say

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.

The best LLM Judge for AI Startups