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From Delivery Rider to Model Worker: Quhuo “Empowering Workers” Sets Industry Benchmark

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BEIJING, Sept. 11, 2024 /PRNewswire/ — Recently, Song Penghua, a rider for Quhuo Limited (NASDAQ: QH) (“Quhuo” or “the company”), a leading gig economy platform focusing on local life services, was honored as the model worker, as the only delivery rider, in Henan Province. This accolade follows his previous recognition as a model worker in Zhengzhou City last year. These honors affirm his personal achievements and underscore the growing significance of new forms of employment in China’s economic and social development.

In recent years, roles such as delivery riders and ride-hailing drivers have become integral parts of China’s workforce. The Ninth National Workforce Survey conducted by the All-China Federation of Trade Unions reveals that out of a total workforce of approximately 402 million, 84 million, or 21%, are engaged in these emerging job categories. This trend underscores the role of new forms of employment as essential avenues for enhancing worker income and broadening career development opportunities.

Song Penghua’s journey vividly illustrates the evolution of these new employment forms. At the age of 26, he has spent four years in the on-demand delivery sector and currently serves as the deputy site manager at the Yingcai Station in Huiji District, Zhengzhou, Henan. Initially facing the typical challenges of crowdsourcing, namely fluctuating income and a lack of professional training, Song encountered significant hurdles in navigating unfamiliar areas and communicating effectively during service delays. His career trajectory took a positive turn when he joined Quhuo, which marked the beginning of a transformative chapter in his life.

Quhuo provided Song with comprehensive professional training and career guidance from the start. The company implemented a mentorship program that paired him with an experienced mentor who offered one-on-one guidance. With this support, Song quickly mastered the necessary application functionalities and efficient order handling, and he honed his communication skills with both merchants and customers. Quhuo also ensured that its riders were well-equipped with essential gears, including helmets, uniforms, food delivery bags, and motorcycles. This robust support system from training to daily operations exemplifies Quhuo’s commitment to empowering its workforce, laying a solid foundation for Song’s career in on-demand delivery services.

Leveraging his experience, Song mentored over 70 apprentices, teaching them to navigate various business districts and impart practical experience. During the pandemic, he consistently managed to deliver 30-40 orders daily, even through restricted areas, to ensure swift service. This commitment not only earned customer appreciation but also highlighted the success of Quhuo’s training programs, which seamlessly integrate professional ethics into the operational standards of its riders.

Furthermore, Quhuo is dedicated to fostering career growth, offering structured pathways for progression from delivery rider to management roles. Within just four years, Song advanced from a rider to deputy site manager, now leading a team of 40-50 people. He said, “The company has provided the opportunities for me to advance. I look forward to achieving even more and taking on greater responsibilities.”

Song Penghua’s success is not by chance. Wu Pengpeng, the city manager for Quhuo’s on-demand delivery service, said that the company is committed to enhancing the skills and overall capabilities of its riders. Song has exemplified outstanding work ethics and professionalism, setting a benchmark for his peers. The company places a high priority on identifying and cultivating such exceptional talent.

Quhuo, a leading gig economy platform in China focusing on local life services, boosts the professional development of its riders through online and offline training, as well as mentorship programs. With meticulous recruitment strategies, phased training, and stringent daily management, Quhuo ensures that every rider can efficiently complete their tasks. Committed to staff welfare and demonstrating social responsibility, Quhuo provides watermelons and drinks to mitigate the summer heat and organizes team-building activities to alleviate workplace stress. The company also creates special care initiatives for women and people with disabilities, prioritizing the physical and mental health of all its workers.

Currently, Quhuo’s on-demand delivery service spans over 30 provinces and 105 cities, employing more than 53,500 active workers monthly and completing an average of 38.1 million service orders. Quhuo riders excel in order acceptance, on-time delivery, and customer satisfaction rates, significantly surpassing industry averages by 15-30 percentage points.

Leslie Yu, Founder, Chairman, and CEO of Quhuo, stated, “Song Penghua’s success illustrates that every rider can find their own platform at Quhuo. As new forms of employment gain significance within the labor force, Quhuo continues to lead the industry. We provide extensive career development opportunities and actively promote the development of these new employment models, contributing to the nation’s economic and social progress.”

About Quhuo Limited

Quhuo Limited (NASDAQ: QH) (“Quhuo” or the “Company”) is a leading gig economy platform focusing on local life services in China. Leveraging Quhuo+, its proprietary technology infrastructure, Quhuo is dedicated to empowering and linking workers and local life service providers and providing end-to-end operation solutions for the life service market. The Company currently provides multiple industry-tailored operational solutions, primarily including on-demand delivery solutions, mobility service solutions, housekeeping and accommodation solutions, and other services, meeting the living needs of hundreds of millions of families in the communities.

With the vision of promoting employment, stabilizing income and empowering entrepreneurship, Quhuo explores multiple scenarios to promote employment of workers, provides, among others, safety and security and vocational training to protect workers, and helps workers plan their career development paths to realize their self-worth.

Safe Harbor Statements

This press release contains “forward-looking statements” within the meaning of Section 27A of the Securities Act of 1933, as amended and Section 21E of the Securities Exchange Act of 1934, as amended and the Private Securities Litigation Reform Act of 1995. All statements other than statements of historical or current fact included in this press release are forward-looking statements, including but not limited to statements regarding Quhuo’s business development, financial outlook, beliefs and expectations. Forward-looking statements include statements containing words such as “expect,” “anticipate,” “believe,” “project,” “will”and similar expressions intended to identify forward-looking statements. These forward-looking statements are based on Quhuo’s current expectations and involve risks and uncertainties. Quhuo’s actual results and the timing of events could differ materially from those anticipated in such forward-looking statements as a result of these risks and uncertainties, which include, without limitation, risks and uncertainties related to Quhuo’s abilities to (1) manage its growth and expand its operations, (2) address any or all of the risks and challenges in the future in light of its limited operating history and evolving business portfolios, (3) remain in its competitive position in the on-demand food delivery market or further diversify its solution offerings and customer portfolio, (4) maintain relationships with major customers and to find replacement customers on commercially desirable terms or in a timely manner or at all, (5) maintain relationships with existing industry customers or attract new customers, (6) attract, retain and manage workers on its platform, and (7) maintain its market shares in relation to competitors in existing markets and its success in expansion into new markets, as well as the development of the COVID-19 pandemic and its impact on Quhuo’s business and industry. Other risks and uncertainties are included under the caption “Risk Factors” and elsewhere in the Company’s filings with the Securities and Exchange Commission, including, without limitation, the final prospectus related to the IPO filed with the SEC on July 10, 2020 and the Company’s latest annual report on Form 20-F. You are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date of this press release. All forward-looking statements are qualified in their entirety by this cautionary statement, and Quhuo undertakes no obligation to revise or update any forward-looking statements to reflect events or circumstances after the date hereof.

View original content:https://www.prnewswire.com/news-releases/from-delivery-rider-to-model-worker-quhuo-empowering-workers-sets-industry-benchmark-302244786.html

SOURCE Quhuo Limited

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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View original content:https://www.prnewswire.co.uk/news-releases/jams-launches-ai-for-enterprise-job-scheduling-jax-and-jams-mcp-on-the-model-you-choose-302833908.html

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Video: CNPC offers green chemical answer

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

View original content to download multimedia:https://www.prnewswire.com/apac/news-releases/video-cnpc-offers-green-chemical-answer-302834036.html

SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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