Wavelabs Insight is our end-to-end expertise in data processing, model training, and serving that helps you realize the true potential of your AI initiatives. It brings together the understanding and know-how of diverse technologies, tools, platforms, and frameworks to make it easy to build, train, and deploy AI models at scale.
Wavelabs Insight leverages open source software modules and custom-built components to accelerate the time-to-deployment of AI solutions. Our systematic approach of identifying business needs through use case discovery and designing and building innovative AI solutions for deployment and scale translates data insights into business value.
High-quality data is imperative for building successful artificial intelligence models. But the process to identify, aggregate, clean, label, and store the available data is often expensive, complicated, and time-consuming. Wavelabs Insight is designed to build and manage end-to-end data pipelines feeding into the AI models, making the process fast, easy, and highly scalable.
Wavelabs Insight Reference Architecture
Training AI models involves several iterations to isolate and measure the impact of changing datasets, algorithm versions, and model parameters. Wavelabs Insight is designed to help organize, track, evaluate, and scale AI model training to ensure that the training pipelines run seamlessly and efficiently.
Wavelabs Insight Reference Architecture
Wavelabs Insight makes it easy to deploy trained models into production and sets up the data flows for inferencing and prediction on real-time or batch data. The flexible architecture helps in deploying and scaling the AI models for high throughput inferencing with fully integrated logging and monitoring dashboards.
Wavelabs Insight Reference Architecture
Wavelabs Insight framework has been validated with multiple use cases across diverse industries. The workflow is implementation-agnostic, and we augment support to all new algorithms and AI frameworks.
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