Frees you up to focus on higher level AI work so you can add more value to the business.
Whether you're a data scientist, data engineer, data analyst, or an IT operations specialist, you know that there's a lot to keep track of when you're working on an AI project. RZT aiOS is the only Operating System of its kind on the market — we created it specifically as an environment that would allow you to keep all of your AI in one place.
What can you do with this artificial intelligence Operating System software?
Build powerful AI applications using pre-built, pre-tested code blocks on the RZT aiOS. Combine proven components in the easy-to-use graphical UI to build, tune, and deploy your AI in days, not months.
By unifying all of these components with a user-friendly interface, RZT aiOS lets you streamline your process and manage your AI projects from start to finish with ease.
RZT aiOS offers an intuitive AI development environment that lets you explore data, visually build models, create processing pipelines, provision and troubleshoot engines, run experiments, and view analytics and explanations—without advanced software engineering skills.
The RZT aiOS removes impediments to end-to-end AI lifecycle management, and provides you a simple and elegant IDE and SDK to manage all aspects of the lifecycle. RZT aiOS includes the following components:
The IDE includes the following capabilities and features:
The RZT aiOS Software Development Kit (SDK) is a comprehensive set of tools and frameworks that provide capabilities ranging from creating distributed Pipelines to managing projects and execution Engines. The comprehensive Python SDK is accessible from a built-in Jupyter notebook that provides all the functionality that the IDE provides.
Blocks and Pipelines are a high-level framework for composing complex computation flows capable of executing in a scalable, distributed manner:
The RazorThink engines are capable of running workloads initiated by the IDE or through external sources:
Unification is one of the reasons why RZT aiOS is among the best artificial intelligence software on the market today. This operating system keeps all of your artificial intelligence technology, processes, and infrastructure in one place. Our convenient modular architecture makes it easy for you to find what you're looking for at every stage of development. The components of our operating system include:
The RZT Model Lifecycle Manager (MLM) is a repository to store all your trained ML and DL models. The MLM is integrated with the Engine, Log, and Metric servers, ensuring it captures all the necessary meta-information such as input/output data to the model, model parameters, model metrics, and logs.more...
The Metrics Server is a central store for all metrics coming out of executed pipelines, and is built to scale based on expected load. The Metrics Server includes pre-built graphs and charts to visualize (for example) the model metrics, and all pre-built visualizations can be directly used by a user in a block. Adding new visualizations is straightforward when a simple template is followed.more...
The Log Server is a central store for all logs generated on RZT aiOS and is built to scale based on expected load. It captures a wide variety of logs to monitor the following:
The Log Server comes pre-built with different log tags such as Debug, Info, and Warning, which users can use in their Block code.
RazorThink guides you through each stage of the AI development lifecycle.
As a data scientist, engineer, or analyst, you need rapid exploration of data and the primary drivers of intelligence. RazorThink gives you rapid development tools for fast model prototyping and building at this stage.
Exploratory work has been done, and it’s time to build and tune your models. Because experiments are expensive, you need RazorThink aiOS cost control and analysis tools to scale and track your experiments.
Putting your AI into production requires extensive testing and analysis around scalability and robust performance. The RazorThink aiOS gives you tools for measurement, logging, and deployment automation. And when the pipeline is in production, use RazorThink tools to ensure performance, keep track of versioning, and respond quickly to any issues.
Now the pipeline is in production and stable. Are the models performant? Are there issues of bias and dysfunctional predictions? You need the powerful governance capabilities of the RZT aiOS to assist in explainability, retraining, monitoring, measurement, traceability, and versioning.
It's time to rethink the way you use artificial intelligence software. Are you ready to get started?