Popular Alternative :
Currently not enough data in this category. Generated by Gemini:
Gentrace is an evaluation and observability tool for generative AI builders. It helps developers to evaluate their generative AI models and to monitor their performance in production.
Evaluation
Gentrace provides a variety of features for evaluating generative AI models, including:
- Automated evaluation: Gentrace can automatically evaluate the quality of generative AI output using a variety of metrics, such as accuracy, fluency, and relevance.
- Human evaluation: Gentrace allows developers to create human evaluation workflows to get feedback on their generative AI output from real people.
- Custom evaluation: Gentrace allows developers to create custom evaluators to meet their specific needs.
Observability
Gentrace provides a variety of features for monitoring the performance of generative AI models in production, including:
- Real-time monitoring: Gentrace can monitor the performance of generative AI models in real time and alert developers to any problems.
- Historical data: Gentrace stores historical data on the performance of generative AI models, allowing developers to track trends and identify patterns.
- Customizable dashboards: Gentrace allows developers to create customizable dashboards to visualize the performance of their generative AI models.
Benefits of using Gentrace
Gentrace can help developers to:
- Improve the quality of their generative AI models
- Reduce the risk of regressions
- Monitor the performance of their generative AI models in production
- Identify and fix problems quickly
How to use Gentrace
To use Gentrace, developers first need to create an account and connect their generative AI models. Once the models are connected, developers can start creating evaluation and observability workflows.
Evaluation workflows
Evaluation workflows allow developers to evaluate the quality of their generative AI output using a variety of metrics. Developers can create automated evaluation workflows, human evaluation workflows, or custom evaluation workflows.
Automated evaluation workflows
Automated evaluation workflows use a variety of metrics to evaluate the quality of generative AI output, such as accuracy, fluency, and relevance. Developers can specify the metrics that they want to use and the percentage of the test set that they want to evaluate.
Human evaluation workflows
Human evaluation workflows allow developers to get feedback on their generative AI output from real people. Developers can create tasks for human evaluators to complete, such as rating the accuracy, fluency, and relevance of the output.
Custom evaluation workflows
Custom evaluation workflows allow developers to create evaluators that meet their specific needs. For example, a developer could create a custom evaluator to evaluate the compliance of generative AI output with their company's safety policy.
Observability workflows
Observability workflows allow developers to monitor the performance of their generative AI models in production. Developers can create real-time monitoring workflows, historical data workflows, or customizable dashboard workflows.
Real-time monitoring workflows
Real-time monitoring workflows monitor the performance of generative AI models in real time and alert developers to any problems. For example, a developer could create a real-time monitoring workflow to alert them if the accuracy of their model drops below a certain threshold.
Historical data workflows
Historical data workflows store historical data on the performance of generative AI models. This data can be used to track trends and identify patterns. For example, a developer could use a historical data workflow to identify which types of inputs are causing their model to perform poorly.
Customizable dashboard workflows
Customizable dashboard workflows allow developers to create dashboards to visualize the performance of their generative AI models. Developers can add charts, graphs, and other widgets to their dashboards to track the metrics that are most important to them.
Overall, Gentrace is a powerful and versatile tool that can help developers to improve the quality of their generative AI models, reduce the risk of regressions, monitor the performance of their generative AI models in production, and identify and fix problems quickly.
