RagMetrics

RagMetrics is a smart tool that helps check how well language models and Retrieval-Augmented Generation systems work. It helps users decide what good results look like for their specific needs. It also makes testing automatic, saving time and giving quick insights. RagMetrics is special because it matches human evaluations 95 percent of the time. This lets users focus on making their products better instead of doing manual checks.

Benefits

RagMetrics has several big pluses:
* Automatic Checking: Makes testing faster by removing the need for manual labeling.
* Custom Measures: Lets users set their own key performance indicators for precise checking.
* A/B Testing: Allows comparing models, prompts, and agents using data insights.
* Better Retrieval: Makes sure models get the most useful information quickly.
* Works with All Models: Supports all language models, whether they are commercial or open-source. This lets users upgrade their models with confidence.
* Over 1,000 Rubrics: Offers many performance measures to check success based on different tasks.
* Fake Data Making: Uses fake data and judge-LLMs to test quickly and efficiently.
* Data Insights: Improves the process using data insights instead of just guessing.
* Balanced Choices: Helps make good decisions that balance quality, speed, and cost.
* Full Checking: Measures how well the context fits, how accurate the meaning is, how complete the information is, how accurate the responses are, how varied the context is, and how fast it is.

Use Cases

RagMetrics makes checking RAG systems easy. It offers automatic testing, custom measures, and A/B testing. It lets users make data quickly, get information efficiently, and check performance across important measures. This makes retrieval methods faster and more accurate, improving the whole system.

Pricing

RagMetrics has two pricing plans:
* Free Plan: Includes fake data, all AI models, 1 custom measure, a library of 210 measures, a dashboard, A/B testing, experiments, 1 user, 10 experiment runs, and community support via Discord.
* Startup Plan: Includes fake data, all AI models, 3 custom measures, a library of 210 measures, a dashboard, A/B testing, experiments, 3 users, 500 LLM judgments per month, and email support.

Vibes

Girish Gupta, Co-founder of Tellen AI, said RagMetrics works really well with RAG methods. It does better than GPT-4 and other big language models. He is excited about using more advanced techniques and other language models, with Llama3 being one option.
Lawrence Ibarria, CEO of Nighthawk, talked about how smart and business-savvy RagMetrics'' founders, Alon and Aubrey, are. He suggested RagMetrics for any AI use, noting the company''s openness to feedback and customizations.