Openlayer

What is Openlayer?

Openlayer is a comprehensive evaluation tool designed specifically for machine learning workflows. It seamlessly integrates into your development and production pipelines, allowing data scientists and engineers to assess and deploy high-quality AI models with confidence. The tool supports a range of tasks, including large language models (LLMs), text classification, tabular classification, and tabular regression.

What are the main features of Openlayer?

1. Powerful Testing and Evaluation: Openlayer offers an extensive suite of testing, evaluation, and observability features for LLMs and other machine learning models. Users can conduct data quality testing, monitor for drift, and assess performance metrics to ensure models operate accurately over time.

2. Customizable Workflows: Users can create specific tests and workflows tailored to their needs, allowing for flexibility in model evaluation and monitoring.

3. Commit-Style Versioning: Openlayer employs a commit-style versioning system that helps users easily track and manage changes made to their models and datasets, similar to how source code is managed.

4. Real-Time Monitoring and Alerts: The platform notifies users of performance changes and data anomalies in real time via email, Slack, or within the Openlayer app.

5. Secure Deployment: Openlayer offers SOC 2 Type 2 compliant hosting and on-premise options, ensuring that user data and models remain secure within their infrastructure.

How to use Openlayer?

To get started with Openlayer, users can upload their models and datasets directly from their training notebooks or pipelines. With just a few lines of code, users can set up monitoring through the Openlayer API. The onboarding process is quick, typically taking only 60 seconds, allowing for immediate integration into existing workflows.

How much does Openlayer cost?

Openlayer offers a free trial for new users, enabling them to test the platform and its features. For those who require additional capabilities or extended usage beyond the trial period, subscription pricing is available, providing various tiers to accommodate different organizational needs.

Helpful Tips for Using Openlayer

• Leverage the Community: Join the Openlayer community on Discord to connect with other users, share insights, and seek support from the Openlayer team.

• Maximize Testing: Utilize the automatic testing features to maintain the quality of your models throughout their lifecycle, ensuring they meet the necessary performance standards.

• Monitor Regularly: Set up real-time alerts to stay informed about your models’ performance, which can enable proactive adjustments and enhance overall reliability.

• Utilize Documentation: The Openlayer documentation offers detailed setup instructions, tutorials, and API references to assist with any questions or challenges encountered during usage.

Frequently Asked Questions

Can I test multiple models simultaneously with Openlayer?

Yes, Openlayer allows users to monitor and test multiple models at the same time, making it easier to compare performance and track variations across different datasets and workflows.

Is my data safe with Openlayer?

Openlayer is committed to data security and compliance. The platform is SOC 2 Type 2 compliant, ensuring that your data is protected throughout its lifecycle.

What types of models can I evaluate with Openlayer?

Openlayer can be utilized for evaluating a wide range of machine learning models, including large language models, text classifiers, and regression models, making it suitable for diverse tasks and use cases in the machine learning field.

How can I get support if I encounter issues with Openlayer?

Users can access support through the Openlayer Discord community or consult the extensive documentation provided on their website for troubleshooting and guidance.