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It is an AI observability and LLM evaluation platform designed to help ML and LLM engineers and data scientists surface model issues quicker, resolve their root cause, and ultimately, improve model performance. | It is a platform for structured prompt engineering. It helps you develop, test, and monitor your LLM structured tasks using templates, queries, collections, and functions. |
Automatically detect model issues in production;
Trace the root cause back to problematic data;
Fine-tune performance and improve outcomes;
Designed with your goals in mind | Design your prompt templates in an extended playground;
Test prompts on entire query collections at once;
Define test-queries with expected result JSON schemas or values;
Follow up with the entire history of your runs and tests |
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It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.

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It improves the cost, performance, and accuracy of Gen AI apps. It takes <2 mins to integrate and with that, it already starts monitoring all of your LLM requests and also makes your app resilient, secure, performant, and more accurate at the same time.

It is the leading observability platform trusted by high-performing teams to help maintain the quality and performance of ML models, LLMs, and data pipelines.

It is a tool for testing and evaluating LLM output quality. With this tool, you can systematically test prompts, models, and RAGs with predefined test cases. It can be utilized as a CLI, a library, or integrated into CI/CD pipelines.

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