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IoT, supply chain, and smart manufacturing solutions
In an on-demand industrial landscape, businesses face unprecedented challenges in managing complex supply chains, processing vast amounts of data, and staying competitive in dynamic markets. By harnessing the power of IoT and edge computing, you can quantify long-term business risks, maximize equipment and workforce efficiency, and dramatically cut operational costs. Consolidated data tools provide a complete, accurate view of your inventory, equipment, and processes across all channels and locations.
From predictive maintenance to AI-driven supply chain optimization, these solutions empower you to make data-driven decisions that prevent disruptions and propel your business forward. The future of efficient, innovative operations is here—are you ready to lead the charge?
Supply chain systems
Gain unprecedented visibility and control over your entire supply network. From real-time inventory tracking to predictive demand forecasting, these platforms enable you to optimize stock levels, reduce waste, streamline processes, and drive informed decisions that boost efficiency and improve customer satisfaction.
IoT and edge platforms
Unlock your connected devices' potential with robust IoT and edge computing platforms. Enable seamless data collection, processing, and analysis at the edge, reducing latency and boosting security. Implement predictive maintenance, optimize production, and ensure quality with intelligent, data-driven operations.
Pricing and promotion
Analyze vast amounts of market data, consumer behavior, and competitive intelligence in real time to set optimal prices and create targeted promotions that maximize revenue and market share. Advanced algorithms continuously learn and adapt, ensuring your pricing strategy remains effective in dynamic market conditions.
Our IoT and edge computing technology partners
Case studies
IoT and edge computing starter kits
Get started on your IoT and edge computing journey with our range of reference implementations, designed to streamline implementation and accelerate time-to-market
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Explore IoT and edge computing insights across industries
Cross-industry
Learn how our IoT and edge computing services can be leveraged across multiple industries
IoT platform: A starter kit for AWS
IoT platform: A starter kit for AWS
The global market for the Internet of Things (IoT) is expected to reach $413.7 billion by 2031, with key industries driving this growth including manufacturing, supply chain and logistics, energy, and smart cities. Building an IoT platform can be challenging due to the complexity of integrating data collection, IoT device management, and machine learning platforms, but AWS offers a solution with their IoT Platform Starter Kit.
IoT platform: A starter kit for Azure
IoT platform: A starter kit for Azure
Learn more about the IoT Platform Starter Kit for Microsoft Azure, which provides best-in-class cloud-native services for IoT and a reference implementation to accelerate the delivery of applied IoT projects.
Building an IoT platform in GCP: A starter kit
Building an IoT platform in GCP: A starter kit
Grid Dynamics has developed a starter kit for building an IoT platform from scratch in Google Cloud Platform (GCP), specifically tailored for smart manufacturing enterprises. The kit includes modular components for data collection, deployment to the edge, IoT device management, and more, reducing the time-to-market for developing an IoT platform.
Inventory allocation optimization: A pre-built solution for Dataiku
Inventory allocation optimization: A pre-built solution for Dataiku
Learn more about a solution for inventory allocation optimization in complex environments that was jointly developed by Grid Dynamics and Dataiku.
Digital Commerce
Learn how our IoT and edge computing services create delightful e-commerce customer experiences
Transform your product design processes and personalization services with generative AI
Transform your product design processes and personalization services with generative AI
Ideate, customize and prototype new product designs in seconds. Enable customers and marketing teams to personalize style, color, texture, and even environment and lighting.
Inventory allocation optimization for membership-based wholesale retailers
Inventory allocation optimization for membership-based wholesale retailers
In the dynamic realm of supply chain and inventory management, where decisions shape the balance between profit and loss, inventory distribution stands out as a key driver of revenue growth. This white paper explores the strategic significance of optimizing inventory allocation, emphasizing its transformative power for businesses. The crucial role of inventory distribution High-performing supply
How explainable AI helped reduce warehouse order picking time by 1/4
How explainable AI helped reduce warehouse order picking time by 1/4
This article discusses how a machine learning model was used to optimize the order picking process in a warehouse, resulting in a 23% reduction in average order picking time. The model predicted the order picking time based on the storage location of products, and suggested new storage locations to improve efficiency.
Manufacturing
Learn how our IoT and edge computing services can augment the manufacturing value chain
8 supply chain trends and strategies every manufacturer needs to know
8 supply chain trends and strategies every manufacturer needs to know
Unlock supply chain excellence: eight 2024 trends & strategies for manufacturing business. Download eBook.
Manufacturing trends for 2024
Manufacturing trends for 2024
How AI, connectivity, automation, security, resilience, and personalization are redefining the potential of manufacturing
Closing the loop: Integrating contract management and supply chain systems for future-ready manufacturing
Closing the loop: Integrating contract management and supply chain systems for future-ready manufacturing
Integrate contract management with supply chain systems with AI. Discover strategies to boost efficiency, decision-making, and reduce costs in manufacturing.
The rise of industry electrification in supply chain and manufacturing: Leveraging AI and digital capabilities
The rise of industry electrification in supply chain and manufacturing: Leveraging AI and digital capabilities
Discover industry electrification insights, trends, and actionable steps for sustainable adoption in the manufacturing supply chain. Download the white paper
Supply chain resilience: A modular framework for sailing through disruption
Supply chain resilience: A modular framework for sailing through disruption
In this white paper, we introduce a modular, “lego brick” approach to supply chain digital transformation for resilience and the technology framework elements.
Quality 4.0: Reimagining AI-powered quality control for smart manufacturing
Quality 4.0: Reimagining AI-powered quality control for smart manufacturing
This whitepaper explores the benefits and implementation of AI-powered quality control in smart manufacturing, including anomaly detection, predictive maintenance, and visual inspection. It also discusses the technology foundations necessary for successful implementation.
Building a visual quality control solution in Google Cloud using Vertex AI
Building a visual quality control solution in Google Cloud using Vertex AI
In this blog post, we consider the problem of defect detection in packages on assembly and sorting lines.
Visual quality control with AWS Lookout for Vision
Visual quality control with AWS Lookout for Vision
Originally published on the AWS Partner Network blog Conveyor belts are an essential material handling tool for various industrial processes, and one of the most effective ways to quickly and continuously transport large amounts of materials or products. However, high throughput rates make it difficult for operators to detect defective products and remove them from
Anomaly detection in industrial IoT data using Google Vertex AI: A reference notebook
Anomaly detection in industrial IoT data using Google Vertex AI: A reference notebook
This blog post discusses the challenges of IoT data analysis for system health monitoring and provides a reference pipeline for anomaly detection using machine learning techniques. The pipeline includes training regression models, computing anomaly scores, and making binary decisions to detect anomalies in IoT data.
Detecting anomalies in high-dimensional IoT data using hierarchical decomposition and one-class learning
Detecting anomalies in high-dimensional IoT data using hierarchical decomposition and one-class learning
This article discusses a methodology for designing machine learning-based health monitoring systems for complex industrial systems. It emphasizes the use of hierarchical decomposition and one-class learning to address challenges such as high dimensionality, high data rates, and qualitative and quantitative inhomogeneity of sensor readings.
Anomaly detection in industrial applications: Solution design methodology
Anomaly detection in industrial applications: Solution design methodology
This article discusses the importance of anomaly detection in technical systems and outlines a solution design methodology based on the types and availability of labeled data. It highlights the pitfalls of using unsupervised methods and recommends the use of one-class learning approaches, even in situations where two-class labeling is available or no labeled data is present.
Visual quality control in additive manufacturing: Building a complete pipeline
Visual quality control in additive manufacturing: Building a complete pipeline
Learn about an innovative visual quality control approach using synthetic data generation that holds significant potential for enhancing defect detection processes in additive manufacturing.
Anomaly detection for Industry 4.0
Anomaly detection for Industry 4.0
The article discusses the availability of a white paper that provides an overview of supported use cases, solution features, architecture, and deployment process for a particular solution.
Pharma and Life Sciences
Learn about our groundbreaking IoT and edge computing innovations in the pharma and life sciences sectors
Financial Services and Insurance
Learn how our IoT and edge computing services are transforming the financial services and insurance industries
Other industries
Learn how technology, telecom, automotive and other industries can leverage our IoT and edge computing services
Software-led transformation of modern automobiles
Software-led transformation of modern automobiles
Explore the transformative journey of modern automobiles, where software-led innovations reshape Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs). Dive into the pivotal role of software, AI, and partnerships in creating connected, sustainable, and user-centric automotive ecosystems.
How cloud-based automotive experience engineering ensures integrated ecosystems for a superior ride
How cloud-based automotive experience engineering ensures integrated ecosystems for a superior ride
In the past decade, the automotive industry has witnessed a revolution, prioritizing an enjoyable and seamless user experience. Whether it’s EVs, internal combustion engines, or hybrids, performance and quality have become key value propositions of this automotive evolution. With embedded systems taking center stage, a vehicle’s value and success are now defined by its software,
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