artificial intelligence (ai) is a rapidly expanding field with new applications daily. However, ensuring the accuracy and reliability of these models remains a difficult task. Conventional ai testing techniques are often cumbersome and require extensive manual configuration, impeding continuous development and disrupting developer workflows. There is no established framework, application, or set of rules for testing and working together on models. Mostly, engineers must manually examine faulty rows before deployment to understand and improve the models.
The innovative OpenLayer solution
Meet open layer, an evaluation tool that adapts to your development and production processes to help you ship high-quality models with confidence. Openlayer seeks to transform ai testing by providing a simple, automated methodology that can be easily incorporated into current development procedures.
Openlayer's solution is very simple. Developers only need to set a series of “mandatory” tests for their ai system and connect their Github repository to Openlayer. Developers can generate their own unique tests or select from a library of over 100 pre-built test alternatives. Once integrated, each code commit automatically triggers these tests on the Openlayer platform. This ensures continuous evaluation without the need for additional work from the developer.
Key Features and Benefits of Openlayer
- open layer It makes the testing process more efficient, allowing developers to find and fix bugs frequently. This increases the overall caliber and reliability of ai models and frees up crucial development time that can be used for creative efforts.
- Developers can track, test and deploy models with the help of Openlayer. Works with current workflows.
- Openlayer provides features such as automatic testing and real-time monitoring.
- Through the platform, users can work together and monitor their progress.
- Openlayer provides local hosting and is SOC 2 compliant.
Financing rounds
Openlayer recently announced that it has raised 4.8 million dollars in a seed round led by Quiet Capital, with additional funding from Ground Up VC, Y Combinator, Picus Capital, Hack VC, Liquid2 Ventures, Soma Capital and Mantis VC.
Key takeaways
- Because too much human configuration and customization is required, all ai testing systems are cumbersome and disrupt developer workloads.
- An evaluation tool called Openlayer helps developers raise the caliber of their machine learning models.
- Developers can use it to track, test, and deploy models.
- Openlayer includes capabilities such as real-time monitoring and automated testing, connecting with existing workflows.
- Through the platform, developers can work together and monitor their progress.
In conclusion
Openlayer convincingly simplifies the often difficult process of evaluating ai. It gives developers the tools to build more reliable and durable machine learning models by providing automated testing, real-time monitoring, and seamless integration. With its emphasis on developer experience and dedication to security, Openlayer offers itself as a useful tool for advancing ai development.
Dhanshree Shenwai is a Computer Science Engineer and has good experience in FinTech companies covering Finance, Cards & Payments and Banking with a keen interest in ai applications. He is excited to explore new technologies and advancements in today's evolving world that makes life easier for everyone.