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Robotics System Integration Market to Grow by USD 6.18 Billion (2025-2029), Driven by Rising Demand for Cobots, AI-Powered Market Evolution – Technavio

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NEW YORK, Jan. 22, 2025 /PRNewswire/ — Report on how AI is driving market transformation – The global robotics system integration market size is estimated to grow by USD 6.18 billion from 2025-2029, according to Technavio. The market is estimated to grow at a CAGR of over 10.7%  during the forecast period. Increase in demand for cobots is driving market growth, with a trend towards increase in demand for application-specific industrial robots. However, high cost of services for robotic system integration  poses a challenge. Key market players include Amtec Solutions Group Inc., Burke Porter Group, CNC Robotics Ltd., Concept Systems Inc., FH Automation, Geku Automation, Hitachi Ltd., IPG Photonics Corp., JH Robotics Inc, MESH Automation Inc., Midwest Engineered Systems Inc., Mitsui and Co. Ltd., Motion Controls Robotics Inc., Peak Analysis and Automation Ltd., Phoenix Control Systems Ltd., Rhein Nadel Automation GmbH, Scott Technology Ltd., TASI Group, TW Automation, and United Robotics Inc..

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Robotics System Integration Market Scope

Report Coverage

Details

Base year

2024

Historic period

2019 – 2023

Forecast period

2025-2029

Growth momentum & CAGR

Accelerate at a CAGR of 10.7%

Market growth 2025-2029

USD 6.18 billion

Market structure

Fragmented

YoY growth 2022-2023 (%)

9.4

Regional analysis

APAC, Europe, North America, South America, and Middle East and Africa

Performing market contribution

APAC at 48%

Key countries

China, US, Japan, South Korea, Germany, UK, France, Canada, Brazil, and Saudi Arabia

Key companies profiled

Amtec Solutions Group Inc., Burke Porter Group, CNC Robotics Ltd., Concept Systems Inc., FH Automation, Geku Automation, Hitachi Ltd., IPG Photonics Corp., JH Robotics Inc, MESH Automation Inc., Midwest Engineered Systems Inc., Mitsui and Co. Ltd., Motion Controls Robotics Inc., Peak Analysis and Automation Ltd., Phoenix Control Systems Ltd., Rhein Nadel Automation GmbH, Scott Technology Ltd., TASI Group, TW Automation, and United Robotics Inc.

Market Driver

The Robotics System Integration market is experiencing accelerated adoption as industries seek to automate processes and increase efficiency. Industrial robots, including collaborative robots or cobots, are becoming more common in manufacturing units, automotive, electronics, aerospace and defense, and other sectors. Robotics system integrators provide consulting services to configure, optimize, and integrate hardware and software for cohesive robotic systems. Next-generation robots are transforming material handling applications, reducing labor costs and improving product quality. Advancements in robotics and AI are enabling real-time monitoring, data analytics, and IoT sensors for dynamic automation solutions. Skilled engineers and technicians are in high demand to implement these systems and ensure infrastructure and application integration. The robotic industry is expanding into new areas such as healthcare, defense, IT and telecom, data centers, network management, bomb disposal, reconnaissance, surveillance, banking, financial services, insurance, inspection maintenance, exploration, surgeries, medications, patient care, political stability, and more. However, cyberattacks pose a threat to operational costs and product quality, making security a priority. Dynamic Automation Solutions are key to staying competitive in today’s market. Advancements in robotics and AI are driving productivity and reducing costs, making it an essential investment for manufacturing and logistics industries. 

The industrial robot market is experiencing significant growth due to the increasing adoption of robots in industries that have historically relied on manual labor. This trend is particularly noticeable in sectors with labor shortages, such as construction. For instance, in regions like the Nordic countries, where construction is on the rise, there is an emerging need for robotics system integrators to optimize efficiency. Small and medium-sized enterprises (SMEs) represent a major growth opportunity for the global robotics system integration market, as they seek to automate processes and improve productivity. 

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 Market Challenges

•         The Robotics System Integration market is experiencing significant growth as more manufacturing units in industries like automotive, electronics, aerospace and defense, and healthcare adopt industrial robots for automating processes. However, challenges persist in integrating these robots, requiring programming expertise and infrastructure and application integration. Robotics system integrators like Mesh Engineering play a crucial role in creating cohesive robotic systems, optimizing hardware and software, and configuring robots for specific tasks. Next-generation robots, collaborative robots (cobots), and IoT sensors are driving the robotic industry forward, but advancements in AI and machine learning algorithms add complexity. Skilled robotics engineers and technicians are in high demand to manage these advanced technologies, while cyberattacks pose a growing threat. Dynamic Automation Solutions are accelerating the adoption of robotics, with real-time monitoring, data analytics, and AI enabling increased efficiency, productivity, and product quality. Industries from manufacturing and logistics to banking and financial services are benefiting from these advancements, with robotics playing a role in tasks from bomb disposal to surgeries and patient care. Operational costs and labor costs remain key considerations, with optimization a priority for manufacturers and service providers alike. As the robotic industry continues to evolve, the focus on collaboration between hardware, software, and human expertise will be essential for success.

•         System integrators play a crucial role in the deployment of industrial robots for businesses. The process of integrating robots involves various formalities, including contract signing, competitive bidding, and legalities. Vendors in the robotics system integration market must focus on streamlining these pre-purchase processes to save time and money for end-users. Innovations in the market include selling software packages for easy robot programming and integration. By improving the efficiency of these initial steps, vendors can provide significant value to their clients. Robotic integration is an essential investment for businesses aiming to enhance productivity and reduce labor costs.

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Segment Overview 

This robotics system integration market report extensively covers market segmentation by  

Application 1.1 Material handling1.2 Welding and soldering1.3 Assembly line1.4 OthersEnd-user 2.1 Electronics2.2 Automotive2.3 Healthcare2.4 Aerospace and defense2.5 OthersGeography 3.1 APAC3.2 Europe3.3 North America3.4 South America3.5 Middle East and Africa

1.1 Material handling-  The robotics system integration market for material handling is experiencing significant growth due to the increasing application of robots in material handling processes. Robots offer the advantage of working on multiple tasks simultaneously, improving process efficiency. The market holds great potential, particularly in countries like China, where there is a pressing need to enhance production efficiency and address the skilled labor shortage. Major robotic manufacturers are partnering with regional vendors to expand their market reach and support end-users’ service needs. Industries such as automotive, chemicals, electrical and electronics, industrial machinery, and food and beverage are major consumers of robotics system integration for material handling. In the automotive sector, robots are essential for handling bulk payloads, while the chemical industry requires robots to manage hazardous materials and reduce liability. The electrical and electronics industry seeks to maintain high throughput and reduce handling time with miniaturization trends. The industrial machinery industry aims to reduce worker fatigue and increase productivity by automating production processes. The food and beverage industry is adopting robots to improve efficiency in handling and packaging various SKUs within a short timeframe. For instance, Coop, a Norwegian grocery distribution center, automated its warehousing, distribution, and order fulfillment functions to address labor shortages, increasing wages, and consumer expectations. The facility handles approximately 480,000 cases daily and offers centralized distribution for expensive-to-transport and slow-moving items alongside regional distribution centers. The material handling segment of the robotics system integration market is expected to grow significantly due to the increasing demand from various industries worldwide.

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Research Analysis

Robotics system integration refers to the process of bringing together various components of industrial robotics, including hardware, software, and configuration, to create a cohesive and optimized robotic system. This integration involves programming units robots to automate tasks in manufacturing units across industries such as automotive, electronics, aerospace and defense, and material handling applications. Next generation robots, including collaborative robots, are increasingly being integrated into these systems to enhance efficiency and productivity. Robotic system integrators play a crucial role in this process, ensuring seamless infrastructure integration and optimization of the entire robotic system. The robotic industry continues to evolve, with a focus on advanced hardware, software, and automation solutions to meet the demands of modern manufacturing processes.

Market Research Overview

Robotics system integration refers to the process of bringing together industrial robots, collaborative robots (cobots), hardware, software, and various systems to create a cohesive automation solution. This integration involves programming, configuration, optimization, and infrastructure and application consulting to automate tasks in manufacturing, logistics, healthcare, defense, IT and telecom, data centers, network management, bomb disposal, reconnaissance, surveillance, banking, financial services, insurance, inspection maintenance, exploration, surgeries, medications, patient care, political stability, and more. Next-generation robots, including those with IoT sensors, data analytics, real-time monitoring, AI, and machine learning algorithms, are driving the accelerated adoption of robotics in various industries. Robotic system integrators play a crucial role in this process, ensuring optimal productivity, reducing operational costs, improving product quality, and enhancing efficiency. However, the increasing use of robotics also presents challenges, such as labor costs, cyberattacks, and the need for skilled robotics engineers and technicians. Advancements in robotics and AI continue to shape the robotic industry, with collaborative robots, dynamic automation solutions, and advancements in labor costs and cybersecurity being key areas of focus.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

ApplicationMaterial HandlingWelding And SolderingAssembly LineOthersEnd-userElectronicsAutomotiveHealthcareAerospace And DefenseOthersGeographyAPACEuropeNorth AmericaSouth AmericaMiddle East And Africa

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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BinBase Expands 2026 BIN Dataset with Instant Payout Intelligence for iGaming, Gambling, and Cross-Border Transfers

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BinBase updates its 2026 dataset with specialized Fast Funds, Visa Direct, and Mastercard MoneySend indicators to help iGaming operators and payout platforms execute seamless, instant card disbursements.

MIAMI, July 23, 2026 /PRNewswire-PRWeb/ — BinBase, a global provider of payment routing intelligence and card issuing data, has introduced specialized instant payout indicators as part of its upgraded 2026 BIN Database. Tailored for iGaming operators, online gambling platforms, crypto-to-fiat ramps, and payout aggregators, the updated dataset helps platform engineers streamline real-time card disbursements and Push-to-Card (P2C) transactions.

In high-velocity sectors such as online betting and gaming, instantaneous player payouts are a primary driver of customer retention. However, executing Push-to-Card transactions through protocols like Visa Direct and Mastercard MoneySend requires knowing whether the receiving card issuer supports Fast Funds for specific merchant category codes (MCCs). Attempting instant payouts on non-eligible cards leads to declined transactions, elevated processing fees, and poor user experiences.

The 2026 BinBase release solves this operational bottleneck by delivering dedicated attributes for real-time fund disbursements:

Fast Funds Eligibility: Granular indicators identifying domestic and cross-border Fast Funds support across global Visa and Mastercard ranges.Online Gambling Fast Funds (OG FF): Dedicated flags specifically identifying card ranges authorized to receive real-time gambling and betting payouts.Mastercard MoneySend & Visa Direct Indicators: Precise protocol compatibility markers (MS Ind & MT Ind) ensuring push transactions are routed only to eligible recipient cards.Direct Debit & Pull-Funds Support: Indicators for recurring collections and account-funding transactions.

“Player payouts in iGaming cannot wait for standard 2-to-3-day ACH settlements,” said a spokesperson for Damiko Inc. “By embedding our Fast Funds and Gambling FF flags into their payment engines, operators can instantly validate recipient cards before initiating a transfer, guaranteeing high success rates and instant liquidity for their users.”

Fintech engineers and payout architects can examine the full 29-field database schema and access a free 2026 sample dataset on GitHub.

To explore commercial licensing, bulk database downloads, or custom data feeds, visit BinBase at https://binbase.com.

About Damiko Inc

Damiko Inc is a US-based fintech data provider specializing in card issuer analytics, payment routing data, and global BIN database solutions. Operating through its flagship product, BinBase.com, the company supplies high-precision transaction intelligence to help merchants and payment facilitators worldwide optimize approval rates and mitigate processing fees.

Media Contact
Fedor Lavrikoff, BinBase, 1 7866133334, sales@binbase.com, www.binbase.com 

View original content:https://www.prweb.com/releases/binbase-expands-2026-bin-dataset-with-instant-payout-intelligence-for-igaming-gambling-and-cross-border-transfers-302829344.html

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Walnut Coding’s Young Coders Serve as ‘Instructors’ at Huawei Cloud Developer Training Camp

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Ages 8 and 15, students showcase AI-era project-building skills from concept to working application

BEIJING, July 23, 2026 /PRNewswire/ — Walnut Coding (the “Company”), a leading online platform for youth coding education, said two of its students – ages 8 and 15 – have joined the “instructor” lineup at Huawei Cloud Developer Training Camp, making them among the youngest “instructors” in the program’s history. The Company cites the pair as a prime example of how young learners can combine coding fundamentals with AI tools to turn ideas into working applications.

The two students, Bolin Du, 8, and Peiqi Gao, 15, built working applications using Huawei Cloud CodeArts, an AI coding assistant, then presented the projects to the training camp themselves – walking the audience through their design choices, technical builds, and debugging process.

The move lands at a moment when AI coding tools are forcing a rethink across the education sector. Tools that can generate functioning code from a plain-language prompt have undercut the traditional argument for teaching children to program – that they need the skill to build things themselves. Walnut Coding’s answer is that the more valuable skill now is judgment – knowing what problem to solve, breaking it into parts, and determining whether an AI’s output actually works.

Gao built a travel-planning application that generates routes, itineraries, and recommendations based on user input, handling the project end to end, from requirements and design through coding and debugging. Du, the younger of the two, built an interactive calendar application, using HTML for page structure, CSS for visual design, and JavaScript for interactive features. Both students then took on an instructor’s role at the camp, presenting their project goals and technical implementation to the audience – a step Walnut Coding says separated the work from a typical classroom assignment.

These were not classroom exercises but working projects, built and presented inside a professional developer-training environment. The experience demanded more from both students than simply producing something functional – they needed to articulate their reasoning, defend technical choices, and refine the final result under scrutiny. Their participation signals a broader shift underway in what youth coding education can deliver.

AI is making code generation easier, but it is also redrawing which skills actually matter. A student who relies only on one-click generation may get a rough prototype quickly, but still struggle to spot logical flaws, judge whether the output is reliable, or turn an abstract idea into a product that actually works. Students with programming foundations, by contrast, are better positioned to define requirements, evaluate what the AI produces, correct its errors, and treat the technology as a tool rather than a shortcut to lean on.

“AI can help children generate code faster, but it cannot decide for them what problem they should solve, nor can it make the final judgment about whether the result is truly effective,” said Pengxuan Zeng, founder and CEO of Walnut Coding. “What these two students demonstrated is not just coding technique, but the ability to define needs, break down tasks, verify outcomes, and turn an idea into a working product. That is why we believe young people still need to learn programming in the AI era.”

Walnut Coding structures its courses around that thesis, pairing student-led project work with teaching-assistant guidance and AI-assisted support. According to the Company, this data is continuously fed back into its systems to refine the personalization of AI-assisted feedback — a closed-loop process linking teaching, practice, feedback, and curriculum development.

The Company frames the payoffs less around producing professional software engineers than around a broader form of literacy. As AI continues to reshape how tasks get done, the ability to understand the technology, structure problems clearly and collaborate effectively with intelligent tools may prove one of the most durable skills a young learner can develop.

Walnut Coding says it plans to keep expanding opportunities for students to build practical projects, partner with industry technology platforms such as Huawei Cloud, and develop the core capabilities needed to build with technology in the AI era.

View original content:https://www.prnewswire.com/news-releases/walnut-codings-young-coders-serve-as-instructors-at-huawei-cloud-developer-training-camp-302833884.html

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MOREH Showcases High-Performance LLM Inference on AMD GPUs at AMD Advancing AI 2026

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SAN FRANCISCO, July 23, 2026 /PRNewswire/ — Moreh, an AI infrastructure software company, led by CEO Gangwon Jo, participated in AMD Advancing AI 2026, AMD’s flagship annual AI event held in San Francisco on July 22–23 (local time), where it demonstrated its distributed inference solution, the MoAI Inference Framework, running on AMD GPUs.

At the event, Moreh presented a live demonstration of the GLM-5.1 large language model (LLM) powered by the MoAI Inference Framework on a system equipped with 32 AMD Instinct™ MI300X GPUs across four nodes. Visitors experienced the chatbot firsthand, evaluating its response speed and service quality while observing performance across a range of real-world use cases.

Unlike conventional demonstrations that simply run an AI model, Moreh’s showcase displayed key inference service metrics in real time, including GPU utilization, Tokens Per Second (TPS), Time To First Token (TTFT), and Time Per Output Token (TPOT). This enabled attendees to directly verify both inference performance and GPU resource efficiency in a production-like service environment.

Global AI industry leaders and enterprise customers attending the event expressed strong interest in the system’s fast response times and stable performance. In particular, the live deployment of the computationally demanding GLM-5.1 model on AMD GPUs at production-grade service levels received positive feedback from visitors.

Moreh’s MoAI Inference Framework is widely recognized as the world’s first commercially deployed distributed inference solution built for the AMD ecosystem. Its distributed inference and heterogeneous computing technologies are designed to dramatically reduce AI service costs, enabling broader adoption of AI worldwide. The technology addresses one of the industry’s biggest challenges-the rapidly rising infrastructure and service costs caused by increasingly larger AI models-by delivering a more efficient inference infrastructure.

Moreh CEO Gangwon Jo stated, “This event provided an opportunity for global customers to verify firsthand that top-tier inference performance can be achieved on AMD GPU environments,” and added “We will continue advancing our AI infrastructure software so enterprises can operate AI services as efficiently as possible, regardless of the underlying GPU platform.”

Moreh develops its own AI infrastructure engine and has expanded its end-to-end AI capabilities through its foundation LLM subsidiary, Motif Technologies, covering both AI infrastructure and foundation models. The company is also strengthening its presence in the global AI market through strategic partnerships with leading technology companies, including AMD and Tenstorrent.

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