# MAAS Inc. — AI and Energy Solutions > Curated AI-readable full-content file for Maase Inc. (NASDAQ: MAAS). This file prioritizes authoritative company, business, technology, product, case-study, FAQ, and investor-relevant information over duplicated navigation, images, partner-logo markup, sitemap data, and full news-article boilerplate. ## Company Overview Maase Inc. (NASDAQ: MAAS) is an AI-driven, end-to-end digital system integrator and operator. The company describes its strategy as combining intelligent technology with strategic M&A / ecosystem integration to advance AI deployment from algorithms and computing infrastructure into practical industry scenarios. - Founded: 2010 - Listed: 2019, NASDAQ - Core platforms: Lingyan Miaoyu Large Model; EMAI industrial agents - Core technology system: computing foundation, MoE models, intelligent BMS, IoT connectivity, CW-MQL green manufacturing - Energy products: mobile charging robots, V2V rescue charging, commercial and industrial storage cabinets, fixed chargers, lithium starting and auxiliary batteries - Contact: ad@maaseai.com - Investor relations: https://ir.maaseai.com/ MAAS positions its ecosystem across computing infrastructure, AI models and algorithms, intelligent hardware, energy services, and scenario-based AI applications. ## Business Landscape ### Lingyan Miaoyu Large Model Lingyan Miaoyu is MAAS's proprietary large language model developed by its subsidiary Huazhi Future. The model has 9 billion parameters and uses a lightweight Mixture-of-Experts (MoE) architecture. The company states that the architecture dynamically activates selected expert networks during inference, aiming to improve inference efficiency, reduce computing costs, and support local deployment and vertical-industry adaptation. For enterprise and government clients, Huazhi Future provides customized AI solutions covering requirements analysis, model and algorithm work, data engineering, application development, system integration, deployment, and ongoing operations. ### Stars Distributed Intelligent Computing Center The Stars Distributed Intelligent Computing Center project is MAAS's distributed AI-computing infrastructure initiative. The company describes a three-tier architecture of “Dual-Core + Multi-Level Edge Nodes + Unified Platform.” The project plans dual-core intelligent computing centers in Yinchuan (Ningxia) and Yiwu (Xinjiang), with centralized training, unified resource pooling, cross-regional disaster recovery, and elastic scalability. It also describes deployment of 50–100 containerized edge intelligent-computing nodes in regions including Beijing, Shanghai, Hangzhou, Chongqing, Ningxia, and Shanxi. The infrastructure is intended for scenarios including government administration, industrial quality inspection, smart transportation, smart parks, and cultural tourism. ### AI + Energy “DianGaiTong” focuses on enterprise electricity-cost optimization through market-based power trading mechanisms. The company states that it can help enterprises achieve sustained electricity-cost reductions of approximately 5%–10% without changing the user's billing counterparty, consumption patterns, or distribution facilities. “Smart Refueling” is designed for individuals and micro users, using AI pricing algorithms, energy-consumption behavior analysis, nearby fuel-discount information, station navigation, and personalized recommendations. ### EMAI Industrial Application Agent EMAI is described as an enterprise marketing and AI-agent platform integrating more than 1,500 functional modules. It supports multi-agent collaboration, AI digital humans, AI customer service, AI livestreaming automation, content production, interactive services, and commercial conversion. The platform is positioned to provide enterprise AI support from design, R&D, and operations through market expansion. ## Intelligent Mobile Energy Ecosystem MAAS describes an intelligent mobile-energy ecosystem centered on proactive energy service. ### Xiaoli Mobile Charging Robot A mobile charging robot designed to deliver energy to vehicles on demand, supporting mobile charging and emergency replenishment. ### V2V Mutual Assistance Charging Rescue Vehicle-to-vehicle charging equipment designed to allow one vehicle to provide emergency charging support to another vehicle. ### Commercial and Industrial Energy Storage Cabinet Energy-storage equipment positioned for peak shaving, off-peak charging, and energy-value optimization. ### Xiaoli Fixed EV Charger Fixed EV charging equipment positioned as infrastructure for EV charging networks. ### Lithium Starting and Auxiliary Power Battery Lithium battery products designed for starting and auxiliary power applications. The company's smart-lithium technology is based on LiFePO4 battery systems combined with smart BMS, modular design, and IoT connectivity. ## Core Technology ### Lingyan Miaoyu Large Model A proprietary 9-billion-parameter MoE model designed for lower inference cost, high-concurrency processing, and enterprise-oriented deployment. ### Cryogenic Minimum Quantity Lubrication (CW-MQL) MAAS describes CW-MQL as cryogenic minimum-quantity lubrication technology operating at -90°C and integrated with 5G and edge computing for green manufacturing and intelligent equipment management. ### Battery Safety Technology For mobile charging, energy storage, and starter-battery applications, MAAS describes a three-layer safety system covering cells, mechanical structure, and system control. It combines automotive-grade LFP cells, structural protection, thermal management, insulation monitoring, and millisecond-level BMS response. The stated protection scope includes overcharge, over-discharge, overcurrent, short circuit, and overheating. ### Long-Life Battery Technology The company describes battery-life optimization through material modification, cell-formulation optimization, system balancing, and continuous BMS monitoring. Stated reference metrics include 4,000 cycles and 80% retention. ### High-Rate Performance Technology High-rate cells, low-resistance connections, thermal structures, and BMS discharge strategies are designed for emergency replenishment, rescue starting, and high-power mobile terminals. The source states a 15C discharge capability. ### Modular and Fast Charging Technology Independent PACK boxes, standardized interfaces, maintainable structures, 1C–2C fast charging, and rapid battery swapping are used to improve expansion, servicing, and operational recovery. ### Environmental Adaptability The technology is intended for parking facilities, campuses, outdoor rescue, mining sites, and long-haul transport. The source highlights wide-temperature operation, IP protection, salt-spray resistance, and redundant checks for critical components. ### Lightweight Technology High-energy-density cells, lightweight frames, structural topology optimization, and compact system layouts are used to reduce equipment weight while maintaining safety and strength. ### V2V Multi-Protocol Compatibility Software-defined protocol adaptation, charging-handshake control, and vehicle-side status recognition are designed to improve interoperability across EV brands and interface standards. The source states support for more than 30 automakers. ### AI Dispatch Algorithm for Energy Storage The algorithm combines electricity prices, load curves, device status, weather, and operating constraints to optimize peak shaving, demand management, and storage-charging coordination. ### Full-Scenario Powertrain Tuning Power response, energy recovery, torque output, and operating modes are optimized for UTVs, go-karts, motorcycles, rescue equipment, and mobile-energy terminals. The source describes 0.1-second response and multi-mode switching. ## AI Industry Solutions and Case Studies MAAS states that it connects AI technology to concrete project outcomes across computing, energy services, and mobile charging. ### Smart Mining Safety MAAS built an AI anti-violation safety platform for a large mining investment company in Xinjiang. The platform combines computer vision with mine-site supervision rules and supports violation recognition, real-time alerts, analysis, traceability, and video archiving. URL: https://maaseai.com/en/cases/smart-mining-safety ### Solid Compute Infrastructure MAAS entered a compute technology service cooperation with a Chongqing blockchain technology company centered on NVIDIA A100 SXM4 80GB resources. The project provides long-term compute support for model training, inference, high-concurrency scheduling, resource monitoring, operations, and technical support. URL: https://maaseai.com/en/cases/compute-infrastructure ### Digital Carbon Transformation MAAS delivered a digital dual-carbon signing system for an industrial IoT enterprise, covering dashboards, templates, approvals, files, arbitration, and system settings. The platform brings signing, evidence preservation, review, archiving, and dispute handling into a standardized workflow. URL: https://maaseai.com/en/cases/digital-carbon-transformation ### Mobile Charging Network MAAS helped a ride-hailing rental operator build a mobile charging service network in which users place orders and mobile charging robots travel to parked vehicles. URL: https://maaseai.com/en/cases/mobile-charging-network ### Roadside Rescue Upgrade A roadside rescue operator adopted vehicle-mounted mobile charging robots that can add about 200 kilometers of emergency range in around 30 minutes, according to the company's case description. URL: https://maaseai.com/en/cases/roadside-rescue-upgrade Reusable capabilities described by MAAS include field-data access, edge-inference deployment, and operational-loop optimization. ## Frequently Asked Questions ### What advantages does an MoE architecture have over a Dense architecture for enterprise deployment? MoE (Mixture of Experts) preserves large knowledge capacity and complex-task capability while dynamically activating selected expert networks during inference. MAAS describes this as a way to reduce per-inference cost and lower the hardware threshold for private or hybrid enterprise deployment. MoE can also support multi-task and multi-tenant workloads through expert routing and targeted industry adaptation. ### How can an AI computing foundation be deployed for enterprise digital transformation? MAAS describes a five-layer enterprise AI foundation covering IaaS for GPU, CPU, storage, and networking; PaaS for cloud-native orchestration, scheduling, training, inference, and AI middleware; DaaS for enterprise data; and higher-level model and application services. The company recommends starting from high-value business scenarios and expanding through unified scheduling, model services, and data feedback loops rather than building an oversized infrastructure platform at the outset. The source states that small companies can start with public cloud or rented compute and launch pilots in roughly 3–7 days, while mid-sized companies may use hybrid cloud for sensitive data and core inference. ## About MAAS MAAS describes itself as an AI trailblazer and an end-to-end digital system integrator and operator. Its ecosystem spans computing infrastructure, intelligent hardware, energy dispatch, commercial network operation, and full-scenario services. ### Management - Min Zhou — CEO; financial-industry and corporate-management experience with investment-project operations and supervision expertise. - Guotao Liu — Co-CEO; more than 15 years of enterprise-management experience focused on automotive services, smart technology, and new energy. - Jiaxing Shi — CFO; listed-company financial-control experience focused on strategic investment and capital-market operations. ### Technical Team - Zhifeng Li — Ph.D. in Quantum Physics from the University of Vienna; postdoctoral research in Biophysics; focuses on quantum information technology and industrial AI applications. - Xiuguo Jiang — more than 12 years of smart-hardware and team-management experience; automotive startup battery R&D, supply-chain collaboration, and new-energy charging. - Yu Chen — 13 years of product-management and entrepreneurship experience spanning blockchain, quantitative trading, AI, and related fields. - Jun Yang — enterprise payment settlement, industrial finance, industrial digitalization, and AI+industry. - Lingping Min — manufacturing management, quality systems, lean production, process optimization, and automotive-grade product delivery. - Zhonghe Tian — new-energy charging-equipment field service, fault diagnosis, remote O&M, and technical support. ## Contact and Partnership ### Business Contact - Phone: +86-532-66030885 - Email: ad@maaseai.com - Address: Building 48, Zhixin Intelligent Manufacturing Valley Industrial Park, No. 52 Yangzhou Road, Laixi Economic Development Zone, Qingdao, Shandong, China ### Partnership Areas - AI compute foundation - Lingyan Miaoyu large model - Xiaoli mobile charging - CW-MQL green manufacturing - Smart lithium BMS - Investor relations Investor relations: https://ir.maaseai.com/ ## Selected Partners and Ecosystem Organizations The source lists organizations associated with MAAS's partner ecosystem, including Asia International School Limited, BDEX, MRANTI, Nanyang Technological University Singapore, National University of Singapore, STM, Singapore Institute of Management, Shanghai Cooperation Organization National Multifunctional Economic and Trade Platform, China Broadcasting Network, China State Construction, China Telecom, China Electronics Corporation, State Grid, China Mobile, Sugon, UGREEN, Peking University, Beijing Super Cloud Computing Center, Huawei, Huaheshuzhi, Huaxin Future, Nanjing Juli Holding Group, Harrow LiDe School, SenseTime, Baode, Xunkun Construction, Shujubao, Schneider Electric, Yibaoquan, Smart Vision, Chenergy, Wall New Energy, Inspur, Shenzhen Institute of Computing Sciences, Tsinghua University, China Unicom, Infinova Source Technology, Jingji Bird Technology, Chongqing University, Chongqing University of Foreign Economics and Trade, Chongqing Institute of Engineering, Chongqing Vocational Institute of Architectural Science and Technology, Chongqing University of Electronic Science and Technology, Chongqing University of Posts and Telecommunications, Jinlin Capital, Alibaba Cloud, Hong Kong Chinese Manufacturers' Association, Hong Kong Chuangsheng Holdings, and Gaojie Intelligent Manufacturing. ## Selected Recent Corporate Updates The source contains a large news archive. To keep this file useful for AI retrieval, full press-release boilerplate, repeated company descriptions, images, and forward-looking-statement text are intentionally omitted. The following recent updates are retained as concise factual signals. ### 2026-08-11 — AI Computing Services Contract Delivered MAAS announced that its subsidiary Huazhi Future completed delivery and client acceptance of an AI-computing technology service contract with a total tax-inclusive value of RMB 1.65 million. The project delivered five computing-service nodes and included compute-resource activation, account delivery, network access, operating-system/driver/CUDA/container/deep-learning-framework setup, monitoring, troubleshooting, technical consulting, performance optimization, and operations support. URL: https://maaseai.com/news/maas-completes-delivery-and-client-acceptance-of-rmb1-65-million-ai-computing-services-contract-full-payment-received ### 2026-08-04 — CTO Appointment MAAS announced the appointment of Dr. Zhifeng Li as Chief Technology Officer, effective August 4, 2026. His responsibilities include technology strategy, AI roadmaps, core platform architecture, R&D management, and engineering execution. URL: https://maaseai.com/news/maas-appoints-dr-zhifeng-li-as-chief-technology-officer-to-lead-ai-technology-strategy-and-platform-innovation ### 2026-07-28 — Kazakhstan AI Data Center Exploration Huazhi Future signed a memorandum with KT-Telecom LLP to explore a large data-center project in Ekibastuz Data Center Valley, Kazakhstan, using the proposed Stars Distributed Intelligent Computing infrastructure architecture. The source explicitly states that the memorandum is non-binding and that commercial terms and final arrangements remain subject to further negotiation. URL: https://maaseai.com/news/maas-subsidiary-huazhi-future-signs-mou-to-explore-ai-data-center-development-in-kazakhstan ### 2026-07-21 — Enterprise AI Large-Model Custom Development Huazhi Future signed an agreement with Zhongchuang Liankong to develop a customized enterprise AI application system based on the Lingyan Miaoyu model. The stated scope includes model customization, algorithm optimization, data engineering and governance, application development, system integration, localized secure deployment, compliance, operations, and iterative upgrades. The contract value is stated as more than RMB 10 million. URL: https://maaseai.com/news/maas-subsidiary-huazhi-future-signs-strategic-enterprise-ai-solutions-development-agreement-with-zhongchuang-liankong ### 2026-07-17 — Sale of 49% Stake in Laixi Intelligent MAAS announced an agreement to sell its indirect 49% stake in Qingdao Huiju Laixi Intelligent Technology for US$17 million. The transaction was described as a strategic move to focus capital and management resources on AI infrastructure, distributed computing, large models and algorithms, intelligent hardware, and industrial AI applications. URL: https://maaseai.com/news/maas-to-sell-49-stake-in-laixi-intelligent-further-sharpening-its-focus-on-ai-strategy ### 2026-07-14 — Lingyan Miaoyu Consumer Access MAAS announced the opening of a consumer-facing access portal for Lingyan Miaoyu. The source describes capabilities including intelligent dialogue, multilingual interaction, content generation, knowledge assistance, creative collaboration, and scenario-based AI services. It reiterates the model's 9-billion-parameter MoE architecture. URL: https://maaseai.com/news/maas-launches-consumer-access-portal-for-its-large-language-model-lingyanmiaoyu-accelerating-ai-commercialization-across-consumer-markets ### 2026-06-15 — 800VDC Green Energy Infrastructure Research Huazhi Future established a green-energy infrastructure research group with 800VDC technology as a core research direction, focusing on AI computing centers, new industrial parks, and distributed renewable-energy access. ### 2026-06-02 — ESG Report The source lists a 2026 ESG report focused on mobile energy, distributed energy storage, social responsibility, and long-term governance. ## Investor and ESG Information MAAS is listed as NASDAQ: MAAS. The source states that the company was founded in 2010 and listed on NASDAQ in 2019. Investor relations website: https://ir.maaseai.com/ The source includes an ESG overview centered on mobile charging and distributed energy storage, with themes covering environmental impact, energy accessibility, emergency resilience, battery lifecycle management, governance, supply-chain responsibility, stakeholder engagement, data privacy, cybersecurity, and digital ethics. ## Canonical Site Sections For page-level detail and the latest updates, use the following canonical site sections: - Business: https://maaseai.com/en/business - Technology: https://maaseai.com/en/tech - Cases: https://maaseai.com/en/cases - News: https://maaseai.com/en/news - About: https://maaseai.com/en/about - Contact: https://maaseai.com/en/contact - FAQ: https://maaseai.com/en/faq ## 核心技术（中文） ### 灵言妙语大模型 9B 参数、MoE 架构，面向低推理成本、高并发处理和企业级 AI 部署。 ### 低温微量润滑 CW-MQL 以 -90°C 低温微量润滑为核心，并与 5G + 边缘计算结合，面向绿色制造和智能设备管理。 ### 极致安全技术 面向移动充电、储能和启动电池场景，建立覆盖电芯、机械结构和系统控制的三层安全体系，结合磷酸铁锂电芯、结构防护、热管理、绝缘监测和毫秒级 BMS 响应。 ### 超长寿命技术 通过材料改性、电芯配方优化和系统均衡控制降低容量衰减，并持续监测电芯电压、温度和充放电状态。 ### 高倍率性能技术 面向应急补能、救援启动和高功率移动终端，采用高倍率电芯、低阻连接、热结构和 BMS 放电策略。 ### 智能锂电技术 基于磷酸铁锂材料体系，结合智能 BMS、模块化设计和 IoT 通信，覆盖移动充电、驻车储能和户外休闲等场景。 ### 模块化与快充技术 采用独立 PACK 箱、标准化接口、可维护结构以及 1C–2C 快充和快速换电设计。 ### 环境适应性技术 面向停车场、校园、户外救援、矿区和长途运输，支持宽温运行、IP 防护和抗盐雾能力。 ### 轻量化技术 结合高能量密度电芯、轻量化车架、结构拓扑优化和紧凑系统布局，提升移动设备的续航、操控和部署灵活性。 ### V2V 多协议兼容技术 通过软件定义协议适配、充电握手控制和车辆状态识别，提高不同品牌和接口标准之间的兼容能力。 ### 工商业储能 AI 调度算法 综合电价、负荷曲线、设备状态、天气和运行约束，进行削峰填谷、需求管理和储充协同优化。 ### 全场景动力调校技术 针对 UTV、卡丁车、摩托车、救援设备和移动能源终端，对动力响应、能量回收、扭矩输出和工作模式进行优化。 ## AI 落地项目（中文） ### 夯实算力底座 MAAS 与重庆市区块链科技公司开展算力技术服务合作，以 NVIDIA A100 SXM4 80GB 为核心配置，提供五年期稳定算力支撑。项目围绕模型训练、推理服务和高并发任务调度提供算力资源交付、运维保障、资源监控和技术支持。 ### 赋能智慧矿山 MAAS 面向新疆某大型矿业投资公司打造 AI 反三违平台，融合计算机视觉与矿区监管规则，实现违规识别、实时预警、分析追溯与视频存档。系统将井下与地面作业视频接入统一算法管线，围绕人员行为、设备状态、作业区域和安全规范建立识别模型。 ### 升级救援体系 道路救援公司采购车载救援版移动充电机器人，为亏电新能源汽车提供应急补能。案例描述称设备可在约 30 分钟为亏电车辆补充约 200 公里续航。 ### 数字碳转型 MAAS 为工业物联网企业交付数字双碳签约系统，覆盖数据看板、模板管理、审批流程、文件管理、仲裁管理和系统设置，将签署、存证、审核、归档和争议处理整合到统一平台。 ### 移动充电网络 MAAS 帮助网约车租赁运营商建设移动充电服务网络，用户通过小程序下单，移动充电机器人前往车辆停放位置提供补能。