AI PaaS for Edge Operators

Participate in AI/ML ecosystem to build the next generation models

Overview: 

  

Edge ecosystems are constantly evolving and today many comprise of collation of multiple organizations offering different services to provide an end to end solution. This ecosystem comprises of diverse set of companies viz. 5G National carriers, rural telco's, low latency Internet providers, IOT solution providers, AI/ ML service providers and  data center & Edge operators. Edge computing creates a sprawling data footprint across a distributed architecture and would need Cloud Native solutions that support heterogeneity of location, remote management and autonomy at scale; enables developers; and integrates well with core processing (in the cloud or data center). IOT devices are generating enormous amounts of data that are required to be processed in real time by AI-inference engines at the edge to enable quick decision making. With the advent of 5G networks and availability of low-latency internet backbone services the need for integrating AI and analytics Platform is more immediate.  

Z.ai is an enterprise-ready turnkey AI Platform-as-a-Service (PaaS) that helps data scientists and data engineers develop, customize, and deploy AI projects quickly, generate new insights and enhance decision-making capabilities. Edge Operators can deploy Z.ai Composable Foundational Components in their own enterprise data center and extend AI-Inferences to any Edge location enabling them to offer a single cohesive AI/ML development platform across the entire Edge ecosystem. Z.ai Platform supports open source frameworks, provides multi-class & multi-cloud orchestration, enables accelerated AI-pipeline management and a repository of curated proven Al Algorithms. Our API based approach enables quick integration with existing IaaS orchestration systems as well as Billing and metering processes. 

Get ready to deploy AI and Machine Learning based services within 8-10 weeks by deploying Cloud Native Z.ai PaaS and start offering high value services at the Edge that will help enterprise clients in their Digital Transformation journey.    

Challenges

Edge Ecosystem 

  • Multi-Cloud technology that supports sprawling data footprint across a distributed architecture

  • Ability to run on or interoperate with edge OSs and gateways.

  • Need for Cloud Native programmable software platform on the edge computing nodes

  • Need for real-time AI-inference at the edge for data collected from IOT devices for quick decision making

  • Need for integrating AI/ML Platform with low-latency network fabric for data traffic

Data Scientists

  • Flexibility to push AI-Inferences to any Edge location

  • Need data flow efficiency from Edge to Cloud for training

  • AI/ML Platform with support for Edge-Machine Learning

  • Need better data comprehension

  • Need better AI algorithms

Solution Implementation for an Edge Operator

Infrastructure resources

  • Edge Operator IT Managers to allocate IT resources Compute, Memory, Storage and accelerated compute resources as recommended by Zeblok from their single or multiple data centers to deploy Zeblok's AI Platform-as-a-Service's Composable Foundational Components. Infrastructure resources at each Edge location to be allocated based on the use case and AI-Inference. 

Select Composable Foundational Components you need based on your AI/ML development needs

  • AI-Workstation (mandatory to install)

  • AI-HPC (optional)

  • AI-Data Lake (optional)

  • AI-AlgoStore (optional)

Select Multi-Cloud options

  • Multi-Edge locations

  • AWS

  • GCP

  • Azure

Select API's integration to third party or home grown applications

  • Billing and metering

  • IaaS Orchestration engine

Benefits

  • Unified single AI/ML Platform across the Edge ecosystem from Core to Edge

  • Deployed in your own data center with your existing Security, Audit and Compliance processes

  • Supports Multi-Cloud into AWS, GCP and Azure

  • Cloud Native

  • Multi-Class Orchestration including turnkey GPU supercomputing

  • Support for all Open Source frameworks

  • API integration with existing billing and infrastructure orchestration applications

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