Deepchecks Software

Deepchecks automatically annotates interactions with Language Models (LLM) incorporating open-source, proprietary, and LLM models. Users can customize the default scoring settings, select the functions needing focus, and fine-tune properties and thresholds, which helps them adjust the sequence of each step throughout the process and enhance precision.

Automated scoring aids automated assessing through human intervention when required. It helps utilize a pre-configured auto-annotation workflow and adjust it according to user preferences.

Your models are integral to your value proposition for customers across various sectors such as healthcare, finance, IT, and e-commerce. To maintain exceptional customer service, real-time alerts about model issues are essential for prompt response.

Golden Set management, like the conventional "test set" in traditional machine learning, is customized for evaluating generative applications. Deepchecks LLM evaluation can enhance your golden set by generating fresh data or improving current datasets, providing valuable insights for further improvement and evaluation.

When the Retrieve, Analyze, Generate (RAG) feature fails to perform as required, the fine-tuning and debugging tool helps identify issues. It can utilize information to adjust the code or prompts or simply download the data for the next iteration of retraining.