ML cube

Introducing Relevance, a key metric in our new RAG Evaluation Module! Relevance measures how well the retrieved context matches the query in terms of topic alignment, scoring from 1 to 5. This metric helps you understand: - Whether topics in the context and query match - How focused the retrieval process is Why does this matter? Because the more relevant the context, the more accurate and meaningful the model’s response can be. Is your RAG system retrieving the right information? Start measuring Relevance with our tool today! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing

Ready to unlock the full potential of your RAG system? We are excited to introduce our RAG Suite composed of three modules: - RAG Evaluation - RAG Security Assessment - RAG Topic Modelling Together these three modules let you to: - Evaluate the overall quality of RAG system - Understand adversarial attack protection level - Learn users domains to improve RAG system where they are interested in AI is evolving fast, and so are the tools to evaluate it. Don't miss out on this essential resource your RAG systems deserve the best! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing

Every day, new LLM models are released, improving upon their capabilities. Make sure your RAG keeps up with these advancements! Our RAG Evaluation module continuously analyzes your data by spotting any problem making sure your AI delivers meaningful results every time. Elevate your product's real-world performance today with our powerful evaluation tool.   Check it out now! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing

AI systems are only as good as the data they retrieve and the responses they generate. That’s why we have developed a comprehensive RAG Evaluation Module to help you measure and improve your RAG model’s performance! With our new module, you can: - Understand if your LLM is hallucinating or is aligned with the provided context - Measure the retrieval system performance with new point of view other than similarity - Have insights about the capacity of your system to correctly answer to the user input Whether you are developing a chat-bot, a recommendation engine, or a knowledge assistant, this tool gives you the metrics you need to optimize every interaction. Explore the future of RAG evaluation with us! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing

Retrieval-Augmented Generation (RAG) systems are game changers, but how do you know if they are truly effective? Our new RAG Evaluation Module offers a suite of quality and evaluation metrics to measure: - Relevance of retrieved information with user input - Coherence between context and response - Accuracy of answers based on user input With our tool, you can analyze the entire retrieval process, providing deeper insights into how well your AI integrates context with intelligent responses. Ready to improve your RAG system’s performance? Let’s get started! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing

We are thrilled to announce the launch of our new RAG evaluation Module, now live and ready for use! In today’s AI landscape, Retrival-Augmented Generation (RAG) systems are crucial for combinig the powerful models with relevant external knowledge. But how do you measure their effectiveness? Our latest module provides in-depth quality metrics to evaluate the relationship between: - User Input - Retrieved Contexts - Model Response From assessing the accuracy of retrieved data to how well models generate context-aware answers, our module covers it all. Curious to learn mode? Try it out and elevate your RAG system performance! #AI #RAG #TechLaunch #AIEvaluation #Innovation #NaturalLanguageProcessing