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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.

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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.

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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.

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Our IoT and edge computing technology partners

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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

Pricing Optimization for Microsoft Azure

STARTER KIT

Pricing Optimization Starter Kit for Microsoft Azure

Take the guesswork out of pricing and promotion decisions with this AI-based Pricing Optimization Starter Kit for Microsoft Azure.

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STARTER KIT

Accelerate the development of IoT analytics solutions in Google Cloud

Grid Dynamics and Google teamed up to create a starter kit for industrial IoT analytics using Vertex AI platform.

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Generative AI Product Design Starter Kit

STARTER KIT

Generative AI Product Design Starter Kit

The starter kit provides Generative AI models for rapid prototyping of new product designs based on sketches, references, and textual descriptions. Product designers can leverage these capabilities to facilitate ideation sessions and create design variants in the blink of an eye.

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STARTER KIT

Demand Sensing and Forecasting Starter Kit

Discover how the Demand Sensing and Forecasting Starter Kit helps retailers, brands and manufacturers make accurate and comprehensive procurement, transportation, workforce allocation, inventory, pricing, and promotion decisions.

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STARTER KIT

AI-Assisted Price Management and Optimization Solution

Explore how the AI-assisted Price Management and Optimization Starter Kit can improve the quality of your pricing decisions and workflow automation.

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STARTER KIT

AI-Assisted Promotion Management and Optimization Solution

Discover how the AI-assisted Promotion Management and Optimization Starter Kit can improve your promotion ROI, prevent hidden profit losses, find profit opportunities, and automate promotion management workflows.

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Pricing Optimization for Google Cloud

STARTER KIT

Pricing Optimization Starter Kit for Google Cloud

Grid Dynamics and Google Cloud teamed up to create an AI-based Pricing Optimization Starter Kit to take the guesswork out of pricing and promotion decisions.

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Explore IoT and edge computing insights across industries

All 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

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.

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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

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

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.

Manufacturing

Learn how our IoT and edge computing services can augment the manufacturing value chain

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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

Integrating contract management supply chain systems concept

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

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.

Two workers using AI-powered quality control for smart manufacturing

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

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

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

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

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

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.

additive manufacturing

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

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.

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