Comprehensive Multimodal Edge Ai
With the Power of an Open Ecosystem
Shopping malls and brick-and-mortar retailers face increased competition from online shopping. Offering a better customer experience has never been more important. Retailers know they can thrive with consistent traffic, but they must convert foot traffic to active patrons by getting people into the store. They must then determine the best way to optimize each patron visit to maximize returns.
Retailers are struggling with labor shortages along with everyone else, which requires finding new ways to increase efficiency. Operational decision-makers in such consumer-centric sectors are exploring how solutions that incorporate Artificial Intelligence (Ai) can increase volumes, streamline operations, and grow revenues. The most successful Ai leveraging industry leaders across multiple sectors, are rapidly seeking to learn from others that have achieved success by leveraging Ai.
Zeblok's Ai-in-a-Box for Retail provides a commercial-ready packaging of an Ai-Platform-as-a-Service paired with your choice of hardware and ISVs. Zeblok securely installs the Ai-MicroCloud® within your IT perimeter to fit any topology, fully integrated with key enterprise systems to provide complete lifecycle management. The Ai-MicroCloud® powers an open multi-class Cloud-to-Edge ecosystem comprising certified hardware SKUs and Ai ISVs, providing workflows for Ai workload optimization for heterogenous chipsets, methodologies to automate deployment to Edge locations via our Ai-API™ Engine to simplify scaling at the Edge locations. This comprehensive solution to leverage Ai to address domain-specific Retail use cases is market-ready for production through global distribution channels.
Ai has the potential to create $2.2 trillion worth of value in retail and wholesale by 2035 by boosting growth and profitability.
The Power of an Open Cloud-to-Edge Ecosystem
The creation of a rich Ai offering is an ecosystem play. By bringing together the diverse set of technologies and vendors one can deliver end-to-end Ai solutions, whether an Edge or enterprise Ai deployment. This requires seamless integration between cloud service providers (CSPs), communications service providers (CoSPs), managed service providers (MSPs), Edge data center and network operators, original equipment manufacturers (OEMs), and the independent software vendors (ISVs) that develop Ai algorithms and Ai applications. Bespoke integration lacks standardization and scalability, while efforts to integrate each new Ai solution can take six to eight months of additional engineering, dramatically increasing costs and time to market.
Zeblok's Ai-MicroCloud® provides the glue to build such an open cloud-to-Edge ecosystem. Zeblok’s standard certification methodology for both Edge servers and Ai applications enables enterprises to mix and match hardware and software of their choice or to accommodate the hardware that is available at the Edge locations they have chosen, dramatically simplifying and accelerating complex Ai deployments.
Turnkey Platform for End-to-End Ai-in-a-Box
Zeblok's Ai-MicroCloud® is an Ai Platform-as-a-Service that streamlines Ai delivery by providing a single, cohesive, turnkey, cloud-native Ai environment—acting as end-to-end Ai middleware that unifies the development, testing, training, optimization, and deployment of Ai/ML solutions, from core to Edge.
Zeblok’s Ai-MicroCloud® architecture leverages popular open source frameworks to deliver a comprehensive platform. Advanced extensions improve simple Kubernetes orchestration, compute, and network virtualization, with high-performance computing (HPC) orchestration. Key innovations include significant shrink-wrapping of cloud-based technologies as Ai middleware, which is installed in various environments, including kiosks, MEC hubs, public clouds, on-premises data centers, and different hardware platforms.
Ai-MicroCloud® aggregates several composable foundational components, which deliver ML DevOps, Ai- WorkStations, software distribution via automated Ai-API deployment, and workflows enabling socket-specific optimization of Ai/ML models.
Automation to Scale at the Edge
Beyond the proof of Concept at a handful of locations, enterprises need help to scale their AI solution to tens of thousands of geographically disperse edges to reap the benefits of AI. Manual installation of OS, infrastructure Orchestration software and Ai inference engine components is cumbersome and time consuming.
Zeblok has built the necessary automation tools into the Ai-MicroCloud® and includes workflows to scale to thousands of Edge locations. This helps IT organizations’ efforts to increase standardization, improve manageability, and enhance support.
Enterprise Security, Compliance & Continuous Governance at the Edge
Enterprises, having expended significant efforts to secure their IT environments, including data centers and cloud based services, must now extend their security framework to include Edge locations. A plethora of solutions provide integrated & continuous governance across a well-architected framework for public cloud deployments.
Zeblok follows an integration methodology to bring third-party solutions into a specific company’s Ai-MicroCloud® that helps them rapidly achieve continuous and autonomous governance and compliance across their Ai-MicroCloud®, including Hub and satellite Edge deployments. It extends enterprise-grade security constructs, such as RBAC, AD integration, network security for physical networks, and service mesh architecture security, to containers, microservices, Ai applications, and Ai-APIs.
A Streamlined Ai Delivery Experience
Ai ISVs build and train their Ai applications in the public cloud or in their own data center. However they face challenges in deploying these inferences at the Edge.
Zeblok's Ai-API™ Engine enables the deployment of a completed Ai/ML inference engine as an AI-API™ in production anywhere, supporting industry-standard protocols such as RESTful HTTPS services or Google RPC. It bridges the gap between data science and DevOps, and enables teams to deliver prediction services in a fast, repeatable and scalable way from cloud to Edge.
Modern workloads are incredibly diverse—and so are processor architectures. No single architecture is best for every workload. Maximizing performance, whether for training of an Ai/ML model or for Ai inferencing in production, requires a mix of scalar, vector, matrix, and spatial (SVMS) architectures deployed in CPU, GPU, FPGA, and future accelerators.
By integrating developer-friendly model optimization and distribution workflows, with tools such as the Intel OpenVINO™ toolkit and the Intel® oneAPI toolkits, the Ai-MicroCloud® provides enterprises with Ai-Optimization-as-a-Service™ that helps improve efficiency and innovation.
A Full Lifecycle Management Platform
Enterprises must effectively manage every IT system, resource, and workload from provisioning through operations, support and retirement. An Edge Ai open ecosystem adds complexity, even as it glues together multiple IT systems from different vendors to enable deploying digital assets across geographically dispersed locations.
Our lifecycle management approach is integrative from the outset to help track and account for all systems, assets and subscriptions consistently, while helping to automate and scale. Zeblok's Ai-MicroCloud® provides software-defined infrastructure for complete lifecycle management, to fit for any topology, Ai/ML model development/testing/training, Ai inference optimization, and deployment of Ai applications, all on one cohesive platform, with Ai-driven integration hooks for security, infrastructure, and software monitoring and help desk support.
Multi-Class Domain-Specific Retail Use Cases
Time Series Data Analytics
Marketing & Advertising
Supply Chain Optimization
Edge Video Analytics
Store Aisle Monitoring
Store Traffic Monitoring
Shopper Gaze Monitoring
Dwell Time Monitoring
Take a 21-Day Trial @ Edge Lab
Our Edge Labs provide a "Try-&-Buy" approach to Ai— access to certified hardware SKUs and curated ISV applications specifically built for retailers in a lab environment.