金十数据7月10日讯，国有企业采购评审专家共享平台今天（10日）正式上线。据介绍，国有企业采购 评审专家共享平台坚持公益性定位，共建企业免费使用。中国物流与采购联合会作为"运营中枢"，负责 平台建设、运维与安全保障。参与共建的央国企则承担专家推荐、信息更新及合规使用职责。中国物流 与采购联合会相关负责人表示，该平台的上线，通过打破专家资源壁垒、促进高水平人才高效流动、统 一评价标准，将显著提升国企采购的评审质量、效率和合规水平。 （央视新闻） 国有企业采购评审专家共享平台上线 ...

Core Viewpoint - Deutsche Bank maintains an optimistic outlook for Zhenkunhang (ZKH.US) in the second half of the year, keeping a "Buy" rating with a target price of $4.5, citing the company's long-term growth potential driven by the digital transformation of China's MRO procurement services [1][2] Group 1: Financial Performance - The company's Q1 2025 performance met expectations, with GMV growth expected to accelerate quarter by quarter [1] - Revenue from the U.S. business doubled month-on-month in Q1, with further acceleration anticipated in the second half [2] Group 2: AI and Technology Integration - AI technology has significantly enhanced customer service efficiency, with a 60.4% increase in the average order handling capacity per customer service team member in Q1 [1] - The AI product recommendation engine has provided purchasing demand analysis and product pool management services to over 200 clients since its launch in September 2024, generating additional revenue exceeding RMB 34 million [1] - The company plans to expand the coverage of the AI product recommendation engine to 14,000 clients by 2025 to further unlock its value [1] Group 3: Product and Market Expansion - As of the end of March, Zhenkunhang's U.S. independent site has launched over 500 SKUs across various categories, including PPE, hand tools, power tools, packaging materials, and HVAC systems [1] - The company aims to launch a mobile application in the second half of the year and increase the SKU count to 1,500 to enhance product coverage and user experience [1] - Zhenkunhang is strengthening its global supply chain by expanding its quality supplier network in Southeast Asia to address potential geopolitical uncertainties [1] Group 4: Private Label Strategy - In Q1 2025, the transaction volume of private label products grew approximately 40% year-on-year, accounting for 8.7% of the company's total GMV [2] - Deutsche Bank views the development of private label products as a core strategy for the company this year, with significant growth potential as the current share is still far from the long-term target of 30% [2]

Investment Rating - The report emphasizes that AI is transforming procurement from a tactical function to a strategic core, indicating a positive investment outlook for AI applications in procurement [2]. Core Insights - The report identifies 101 practical AI use cases across the procurement lifecycle, highlighting the significant role of AI in enhancing efficiency, compliance, and supplier collaboration [2][3]. - Autonomous AI systems are emerging as a key development, enabling real-time monitoring, automation of repetitive tasks, and intelligent decision-making throughout the Source-to-Pay (S2P) lifecycle [5][7][8]. Summary by Sections Spend Analysis and Category Management: Use Cases 1-10 - AI unlocks deeper insights into spending patterns and category performance, enabling smarter strategies and faster analysis [10]. - Use Case 1: Automated spend classification using NLP and machine learning improves accuracy over time [11]. - Use Case 2: Predictive spend forecasting helps procurement plan activities and align with financial goals [13][15]. - Use Case 3: Spend anomaly detection identifies unexpected peaks and duplicate payments in transactions [17]. - Use Case 4: Category opportunity identification reveals potential savings through bundling and competitive sourcing [19]. - Use Case 5: Market price benchmarking assesses whether payments are above or below market averages [21][23]. Procurement and Contracts: Use Cases 11-20 - AI accelerates procurement cycles and enhances supplier negotiations [37]. - Use Case 11: Automated supplier discovery expands procurement reach and ensures diverse supplier inclusion [38][40]. - Use Case 12: Intelligent RFx generation streamlines the creation of procurement documents [43]. - Use Case 13: Supplier bid evaluation provides ranking suggestions based on various criteria [45]. - Use Case 14: Contract term extraction enhances contract searchability and audit readiness [47][49]. Supplier Management: Use Cases 21-30 - AI enhances supplier evaluation, management, and collaboration capabilities [71]. - Use Case 21: Supplier risk monitoring detects risk signals using internal and external data [72]. - Use Case 22: Supplier performance scoring creates dynamic scorecards based on various metrics [74]. - Use Case 23: Document verification automates the review of supplier submissions for compliance [76]. Purchasing and Receiving: Use Cases 31-40 - AI simplifies purchasing processes and enhances compliance [100]. - Use Case 31: Guided purchasing assistants provide real-time suggestions during demand creation [101]. - Use Case 32: Purchase request classification automates routing and policy checks [103]. - Use Case 33: Emergency request triage identifies high-priority requests for expedited processing [108]. Invoicing and Payments: Use Cases 41-50 - AI reduces friction in invoice processing and payment workflows [128]. - Use Case 41: Intelligent invoice data capture improves accuracy and reduces manual entry [129]. - Use Case 42: Duplicate invoice detection flags potential duplicates for review [134]. - Use Case 43: Invoice and purchase order line matching optimizes matching accuracy [136]. Compliance and ESG Monitoring: Use Cases 51-60 - AI shifts compliance work from passive to proactive, revealing ESG risks [161]. - Use Case 51: Contract compliance violation detection identifies deviations from contract terms [162]. - Use Case 52: ESG risk scanning categorizes suppliers based on environmental and social governance risks [164]. Procurement Intelligence and Planning: Use Cases 61-70 - AI empowers procurement teams to adapt strategies based on market conditions [190]. - Use Case 61: Category spend forecasting models predict future spending based on various factors [191]. - Use Case 62: AI-driven savings opportunity detection uncovers unexploited savings [197]. Data and Analytics: Use Cases 71-80 - AI enhances data quality and accelerates analysis [225]. - Use Case 71: Procurement data quality scoring engine assesses the accuracy and completeness of records [226]. - Use Case 72: Master data deduplication identifies and merges duplicate records [228]. Chatbots/Help Desk/Assistance: Use Cases 81-90 - AI assistants improve responsiveness and efficiency in procurement queries [255]. - Use Case 81: Procurement policy assistants answer user questions about procurement guidelines [256]. - Use Case 82: Guided purchasing chat assistants help users create requests [258]. Workflow Orchestration and Intelligent Agent-Based AI: Use Cases 91-101 - Intelligent agent-based AI enables goal-driven automation across workflows [285]. - Use Case 91: Cross-system procurement agents coordinate actions across various systems [286]. - Use Case 92: Exception management agents detect process anomalies and suggest solutions [293].