Jesta I.S. has been in business for over 50 years. Jesta I.S. is a global provider of enterprise software solutions to retailers, etailers, wholesalers and brand manufacturers, specializing in apparel and footwear. The Vision Suite is a cloud-based, organically engineered platform that optimizes back/front-end supply chain operations. This includes everything from trade/product/demand management to merchandising and POS. It eliminates inefficiencies caused by disjointed apps and provides real-time visibility into enterprise inventory, cross-channel orders and AI-driven CRM data. It supports multiple brands, currencies, languages, and helps businesses create seamless omnichannel shopping experiences.
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Epicor Connected Process Control (CPC) is a flexible no-code/low-code MES and manufacturing operations platform that helps manufacturers standardize production and assembly processes, improve quality, and increase visibility across the shop floor.
Using digital work instructions with multimedia content, manufacturers can guide operators through critical tasks, enforce process control, and improve consistency across products, workstations, and production lines.
CPC connects equipment and devices to collect production and quality data in real time, helping manufacturers identify issues faster, reduce waste, and support continuous improvement.
CPC provides product traceability with a complete historical record of each product's build and inspection history. Manufacturers use CPC to support assembly verification, error proofing, quality inspections, operator guidance, and other connected manufacturing initiatives.
For manufacturers with complex product variations, CPC can dynamically present the correct work instructions based on the product or configuration being built, helping ensure products are assembled accurately and consistently.
Available on-premises or in the cloud, CPC scales from a single work cell to enterprise-wide deployments.
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Google Cloud Vision AI
Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.
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NeuralVision
NeuralVision represents a cutting-edge machine vision platform that integrates deep learning and artificial intelligence capabilities specifically for the field of industrial inspection. This innovative system empowers companies to fully manage the efficiency of their machine vision applications without needing to rely on external experts for modifications or the introduction of new product lines. In contrast, conventional machine vision heavily relies on well-controlled environments, strict positional tolerances, and the expertise of skilled vision programmers. Engineers typically bear the responsibility of devising every necessary algorithm to accurately inspect various aspects of a part, including measurements, color, and precise locations. Cyth Systems developed NeuralVision to enable individuals with no prior machine vision knowledge to effectively inspect and categorize products. Traditionally, machine vision systems require a seasoned programmer to select from numerous analysis algorithms to analyze an image, leading to a bottleneck in efficiency and adaptability. With NeuralVision, the process is streamlined, making it accessible for a broader range of users and significantly increasing operational flexibility.
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