In the rapidly evolving landscape of AI and Machine Learning, it is crucial to choose tools that not only meet technical requirements but also provide seamless user experiences. At Lumina, we offer two robust options: PrismRCL™, our Windows-based application, and our LuminaRCL™ API. Both are tailored to accomplish similar tasks utilizing the RCLC classification algorithm, yet they come with unique nuances and functionalities. In this blog post, we will delve deep into the comparison between these two offerings, shedding light on their features, use cases, and how they can be used in tandem to elevate your operations.
Overview
Before we dive into the specifics, let’s have a quick look at the core essence of each product.
LuminaRCL™ API – The LuminaRCL™ API is hosted by Lumina, and provides users the ability to train and infer against models. This web-based service is composed of a front-end that allows users to manage their datasets, models and jobs, as well as a backend to interface directly with the API.
PrismRCL™– PrismRCL™ is a Windows-based application currently in beta. This allows users to train models on their local Windows machines while maintaining their data locally.
Feature Comparison
Let’s break down the features of both offerings to provide a detailed comparison.
| Features | LuminaRCL™ API | PrismRCL™ Windows Application |
| 1. User Interface | The LuminaRCL™ API provides a front-end system for users to manage their datasets, models, and results. All assets are ID based, ensuring clarity for API users. | PrismRCL™ is a local application, and allows you to run one-line commands to train your data and run inference sessions. |
| 2. Hardware Compatibility | The LuminaRCL™ API has no hardware requirements and is a hosted solution. Users require internet access to utilize the API. | PrismRCL™ is only available for Windows at this time. Full systems specifications can be found below for your convenience. |
| 3. Performance | The LuminaRCL™ API’s performance is based on your internet connection and the size of the job you are running. Each user can run one job at a time.Given that data is being uploaded to a remote server, large datasets may take significant time and compute. | PrismRCL™’s performance allows additional flexibility and control, as it runs on your local hardware. Users can add more memory or CPU resources as required. PrismRCL does not require internet access.Note that that when selecting your PrismRCL paid license, performance is based on the number of threads included. |
| 4. Integration | The LuminaRCL™ API allows for integration, via API, to your existing applications or workflows. We have provided example python scripts showing how to connect your services to the RCLC API. | PrismRCL™ does not provide the capability to connect to your current applications or workflows via API. |
| 5. Security | Utilization of the LuminaRCL™ API requires that you upload your datasets to Lumina’s hardware for usage. Note that Lumina does not own your data, nor do we utilize client data. Please ensure your datasets are eligible to be shared outside of your organization, or on hardware outside of your domain environment. | Utilizing PrismRCL™ allows you to keep your data on your own Windows-based hardware. Additional security is managed at the end-point level, and is the user’s responsibility. |
| 6. Support and Documentation | LuminaRCL™ API users can request support from the Lumina team by sending a request to our Technical Support team. | PrismRCL™ users can request support from the Lumina team by sending a request to our Technical Support team. |