Machine Learning Infrastructure
Build and run AI/ML pipelines on-premises,
close to your data
Save cloud cost for doing model training and inference.
Build Machine Learning Infrastructure
Where You Want
Machine learning infrastructure is the key requirement for any
AI/ML project in a company.
However building it is lot more challenging than it should be. We see people struggling to build it themselves using standard servers, Linux operating system, Nvidia drivers, custom package installs and tooling required to run AI/ML pipeline software. We simplify all that to bring an easy to build and consume infrastructure for AI/ML workloads
Bring Your Own GPUs
Instead of renting expensive GPU servers in the cloud, you can bring your own servers with GPUs and use those to run AI modeling or inference. This gives you choice and control at significantly lower cost.
Simplify Building and Operating Machine Learning Infrastructure
Instead of trying to stitch all the pieces together, we provide an end-to-end AI/ML infrastructure, where you can simply start by running your pipelines. We take care of the rest in terms of underlying operating system, driver setup, tooling set up and showing you how to run ML workloads within a few clicks. You can simply give access to your AI/ML engineers and have them operate in a self-service manner.
Build Hybrid AI/ML pipelines using Edge cloud and Public Cloud
Building and running the whole pipeline in the cloud can be very expensive due to GPU compute and data storage costs. We provide a unique model where you can offload expensive stage of the pipeline that do the training, to on-premises infrastructure. However, you can continue to consume some resources in the cloud if needed. This provides the best of both worlds in terms of cost and flexibility.
Built-in Object Store for Your Data
Most machine learning projects need to consume a lot of data for training and testing. This data is stored in an object store. In many cases this data is produced on the edge itself. We provide a built-in object store in Edgebricks cloud to store this data and run training jobs on the servers with very fast access to data on the same LAN. No need to pay high data storage or access costs in the cloud.
Built-in AI/ML Pipeline Templates
We provide built-in templates to get started. Your team can quickly see how to train YOLO based object detection models. These templates can also be customized to fit your needs. This is a quick way to get started and showing value for the edge cloud to your team.
Industry Specific Solutions
Building Models in Manufacturing
Manufacturing industry is adopting video and AI based quality or compliance testing. This requires machine learning models that are build specific to their needs based on their data. No outsider can build the model for them without access to their data and labeling which shows the high vs. low quality product. This data is also the core IP which cannot be shared outside or put in the public cloud in most cases. We provide a solution where your developers can collect data, label it and training AI models. These models can be retrained periodically as new data arrives, using AI/ML pipelines. We provide the most suited infrastructure for doing that. You can focus on building your models and running them instead of dealing with infrastructure issues.
Build Models for Healthcare
Healthcare industry is quickly adopting AI driven video or image analysis for detecting disease. AI/ML can be applied to most visual image analysis to assist doctors in finding problems. Any patient image data is quite sensitive and can’t be shared outside the hospital or region. In addition, these images tend to be very large due to their high resolution. Using Edgebricks you can build models to detect diseases using your data and labeling in an on-premises environment. Your team can focus on building the AI/ML models instead of dealing with infrastructure issues.