Our Solutions

Overview

Zeblok's enterprise-ready turnkey Ai Platform-as-a-Service (AI PaaS or Ai-MicroCloud^®) helps you develop, customize and deploy Ai projects quickly, generate new insights and enhance decision-making capabilities. Our platform has been built from the ground up for collaboration from composable foundational components, which makes it easy to deploy and satisfy a multitude of challenges that enterprises, data center operators and Edge operators face.

Zeblok Computational offers enterprise clients a shared utility platform. CIOs, CTOs and Innovation Offices have the opportunity to combine and create a community comprised of data scientists, data engineers and Ai engineers, as well as various lines of business analysts, to collaborate on AI development in a single platform. Furthermore, Ai innovation labs outside of the enterprise, including student interns from strategic academic partnerships, can be brought onto the same platform.

Enterprise Ai

Zeblok Computational deploys its Ai-MicroCloud^® to wherever the data resides – enterprise data centers, public clouds and Edge locations. Users determine the appropriate mix of Ai-MicroCloud^® composable foundational components, based on their needs and the specific line of business applications and AI/ML models they are developing.

Once implemented, enterprises become truly multi-cloud and are able to execute on numerous enterprise infrastructure strategies due to the flexibility in the deployment architectures afforded by the Ai-MicroCloud^®.

For example, if an enterprise has a deep relationship with AWS and application teams require some data to be kept within the enterprise data centers, then some data can be moved into AWS. Then the development team can decide where to launch the foundational components. It can be launched within the enterprise data center or in AWS, with comprehensive audit trails supporting any regulatory requirements.

Edge Ai

Zeblok Computational deploys its Ai-MicroCloud^® to wherever the data resides – enterprise data centers, public clouds and Edge locations. Users determine the appropriate mix of Ai-MicroCloud^® composable foundational components, based on their needs and the specific line of business applications and AI/ML models they are developing.

Once implemented, enterprises become truly multi-cloud and are able to execute on numerous enterprise infrastructure strategies due to the flexibility in the deployment architectures afforded by the Ai-MicroCloud^®.

For example, if an enterprise has a deep relationship with AWS and application teams require some data to be kept within the enterprise data centers, then some data can be moved into AWS. Then the development team can decide where to launch the foundational components. It can be launched within the enterprise data center or in AWS, with comprehensive audit trails supporting any regulatory requirements.