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Edge AI Software Market Analysis And Trends By Segmentations, Top Key Players, Geographical Expansion, Future Development & Forecast -2028

Edge AI Software Market Analysis And Trends By Segmentations, Top Key Players, Geographical Expansion, Future Development & Forecast -2028
Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), TIBCO (US), Octonion (Switzerland), Imagimob (Sweden), Anagog (Israel), Veea (US), Gorilla Technology (China), Azion (US), Bragi (Germany), Tact.ai (US), Ekinops (France), Clearblade (US), Alef Edge (US), Adapdix (US), byteLAKE (Poland), and Blaize(US).

Edge AI Software Market by Offering (Solutions (Standalone and Integrated) and Services), Data Type (Video & Image Data, Audio Data, Text & Language Data, Biometric Data, and Multi-modal Data), Vertical and Region – Global Forecast to 2028

The global Edge AI Software Market is projected to grow from USD  1.1 billion in 2023 to USD 4.1 billion by 2028, at a CAGR of 30.5% during the forecast period. Edge AI software is rapidly gaining traction in various industries, revolutionizing how businesses operate and interact with their customers. This technology enables real-time data processing and decision-making at the edge of the network, closer to the data source, reducing latency and improving efficiency. Its applications span across diverse sectors, from manufacturing and healthcare to retail and transportation, optimizing processes, enhancing customer experiences, and driving innovation. The edge AI software market is poised for significant growth, fueled by advancements in hardware, the rise of IoT devices, and the increasing demand for intelligent, real-time solutions.

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Solutions segment to account for the largest market size during the forecast period.

Based on the offering segment, solutions are anticipated to hold the largest market size during the forecast period. Edge AI software solutions are being rapidly adopted across various industries, driving significant advancements and enhancing operational efficiency. From manufacturing to healthcare, transportation to agriculture, edge AI is empowering businesses to optimize processes, personalize experiences, and improve safety. For instance, in manufacturing, edge AI enables real-time monitoring, predictive maintenance, and anomaly detection, leading to reduced downtime and improved quality control. Retailers leverage edge AI for targeted promotions, personalized recommendations, and optimized store layouts.

Managed service to account for higher CAGR during the forecast period.

Based on the services, managed services are anticipated to hold the highest CAGR during the forecast period. Edge AI managed services are gaining popularity as organizations seek to harness the power of edge AI without the burden of in-house expertise and infrastructure management. These services provide comprehensive solutions, encompassing hardware, software, deployment, and ongoing maintenance, enabling businesses to focus on their core competencies while leveraging edge AI’s transformative capabilities.

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Unique Features in the Edge AI Software Market

AI capabilities on devices with restricted computing resources are made possible by software solutions created especially for resource-constrained edge devices, guaranteeing effective use of processing power, memory, and energy.

The capacity to do inference in real-time on edge devices, enabling prompt decision-making independent of cloud-based processing. Applications that need minimal latency, such industrial automation or driverless cars, depend on this.

smooth interface with cloud-based AI platforms, enabling edge devices to retain local real-time processing capabilities while utilising cloud resources for activities like model training.

Devices can process and analyse data locally without having to send massive volumes of raw data to the cloud thanks to advanced analytics capabilities at the edge. Applications that have bandwidth or privacy restrictions should pay special attention to this.

The ability for edge devices to learn and adjust to changing circumstances without depending on constant cloud connectivity is made possible by support for on-device machine learning models. This is useful in situations where connectivity is patchy or nonexistent.

Robust security measures to safeguard private information handled at the edge. To guarantee the integrity and privacy of insights produced by AI, this involves encryption, secure boot procedures, and other precautions.

Major Highlights of the Edge AI Software Market

Combining cloud and edge computing to build an AI architecture that is scalable and frictionless. This keeps edge devices’ local processing power while enabling them to outsource labor-intensive activities to the cloud.

Edge AI is being used more and more in applications like autonomous systems, augmented reality, and virtual reality (VR) where low latency is essential.

AI algorithms on edge devices can be performed more efficiently through the development and application of specialised hardware accelerators, such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units).

Adoption of federated learning techniques, which prevent the centralization of sensitive data and enable training of models across a number of edge devices. Security and privacy are improved by this.

Intelligent data processing at the source is made possible by the incorporation of AI capabilities into Internet of Things devices. IoT applications including wearables, smart homes, and industrial IoT are especially pertinent here.

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Top Key Companies in the Edge AI Software Market

Key players operating in the Edge AI Software market across the globe are Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), TIBCO (US), Octonion (Switzerland), Imagimob (Sweden), Anagog (Israel), Veea (US), Gorilla Technology (China), Azion (US), Bragi (Germany), Tact.ai (US), Ekinops (France), Clearblade (US), Alef Edge (US), Adapdix (US), byteLAKE (Poland), Reality AI (US), Deci (Israel), Edgeworx (US), Swim (US), Invision AI (Canada), Horizon Robotics (China), Kneron (US), DeepBrainz (India), Johnson Controls(Ireland), and Blaize(US). These Edge AI Software vendors have adopted various organic and inorganic strategies to sustain their positions and increase their market shares in the global market.

Nutanix, a prominent enterprise cloud computing solutions provider, operates in two core business segments: products and support, entitlement, and other services. Their Enterprise Cloud OS software utilizes hyper-converged technology to deliver agility and simplicity. Nutanix offers a wide array of solutions, ranging from data recovery to server virtualization and Virtual Desktop Infrastructure (VDI), customized to meet the diverse needs of end-users. With the most diversified end-user portfolio in the ecosystem, Nutanix caters to a broad customer base, including Toyota, Telstra, Yahoo, Deloitte, AirBus, and NASDAQ. Their services span multiple industries, including education, financial services, energy and utilities, manufacturing, public sector, retail, consumer goods, and healthcare. In the Edge AI software market, Nutanix introduces the Nutanix Xi IoT Edge Computing solution, featuring a SaaS control plane and the Xi Edge platform, designed to run on edge devices.

IBM, a global technology company, founded in 1911, is known for its work in computing, including the creation of the first programmable computer. In the modern era, IBM is a leader in various technology domains, including cloud computing, artificial intelligence, and quantum computing. In the Edge AI market, IBM is a prominent player. They offer a range of solutions that harness the power of AI and data analytics at the edge, enabling real-time decision-making and insights. IBM’s edge AI solutions find applications in industries such as manufacturing, healthcare, and telecommunications, where low latency and local processing are crucial. Their offerings include hardware, software, and services that empower businesses to leverage the potential of Edge AI for improved efficiency, productivity, and innovation. IBM’s experience, global presence, and comprehensive approach to technology make them a significant contender in the Edge AI market, addressing the growing demand for decentralized and intelligent computing at the edge of networks.

Microsoft is an American multinational technology corporation headquartered in Redmond, Washington. The company’s best-known software products are the Windows line of operating systems, the Microsoft 365 suite of productivity applications, and the Edge web browser. Microsoft also produces a wide range of other consumer and enterprise software for desktops, laptops, tabs, gadgets, and servers, including Internet search (with Bing), the digital services market (through MSN), mixed reality (HoloLens), cloud computing (Azure), and software development (Visual Studio). In the Edge AI software market, Microsoft is offering various solutions for edge computing and AI. The company’s Azure IoT Edge platform enables customers to deploy cloud workloads, including AI and machine learning, to run on local devices. Microsoft’s Azure Machine Learning service provides a cloud-based environment for developing, training, and deploying machine learning models. The company also offers Azure Stream Analytics, which enables real-time analytics and complex event processing on streaming data from various sources. Microsoft’s solutions are widely used in various industries, including healthcare, manufacturing, and retail.

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