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Parea AI

Debug and monitor LLM applications with Parea’s features.
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What is Parea AI?

Parea AI is an online platform designed for AI engineers that aims to help them develop reliable, production-ready large language model (LLM) applications. The platform offers various features such as a prompt playground with function calling, custom test collections and evaluation metrics, log and trace monitoring, and analytics. It also supports batch evaluation jobs and unlimited deployed prompts. Users can choose between a Starter plan, which supports up to 2 members and has a monthly limit of 3k logged events, or a Pro plan that allows for more members and higher event limits. The platform also offers support for personalized evaluation metrics.

 


 

⚡Top 5 Parea AI Features:

  1. Prompt Playground: A feature that allows users to experiment with prompts and functions.
  2. Custom Test Collections and Evaluation Metrics: Users can create their own test collections and set specific evaluation metrics for their projects.
  3. Log and Trace Monitoring: This feature enables real-time monitoring and analysis of logs and traces during application development.
  4. Batch Evaluation Jobs: Users can process multiple evaluation tasks simultaneously using batch jobs.
  5. Unlimited Deployed Prompts: The ability to deploy an unlimited number of prompts for various purposes.

 


 

⚡Top 5 Parea AI Use Cases:

  1. Debugging LLM Applications: Developers can use Parea to identify and resolve issues in their large language model (LLM) applications.
  2. Monitoring Application Performance: The platform provides real-time monitoring of application performance, allowing users to quickly address any issues.
  3. Evaluating Model Accuracy: Users can evaluate the accuracy of their models using custom test collections and evaluation metrics.
  4. Batch Processing for Efficiency: Batch processing jobs enable developers to process multiple tasks simultaneously, increasing efficiency.
  5. Personalized Evaluation Metrics: This feature allows users to set specific evaluation metrics tailored to their project requirements.
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