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+2025-07-25,2025-07,Chinese,0,0,251,167,117,51 +2025-07-25,2025-07,English,0,0,318,166,141,50 +2025-07-25,2025-07,English,1,0,187,120,100,9 +2025-07-25,2025-07,Math,0,0,60,34,27,15 +2025-07-25,2025-07,Chinese,1,0,22,6,2,4 +2025-07-25,2025-07,Chinese,0,0,6,1,1,51 +2025-07-25,2025-07,Math,1,0,4,1,0,0 +2025-07-25,2025-07,Chinese,1,1,3,1,0,3 +2025-07-25,2025-07,Ace vocab,0,0,0,0,0,1 +2025-07-24,2025-07,English,1,0,327,214,183,11 +2025-07-24,2025-07,English,0,0,441,189,148,47 +2025-07-24,2025-07,Chinese,0,0,270,157,125,36 +2025-07-24,2025-07,Math,0,0,46,33,28,7 +2025-07-24,2025-07,Chinese,1,0,27,9,6,0 +2025-07-24,2025-07,Math,0,0,4,4,4,7 +2025-07-24,2025-07,Chinese,1,1,8,3,3,1 +2025-07-24,2025-07,Math,1,0,3,1,1,1 +2025-07-23,2025-07,English,1,0,348,243,213,12 +2025-07-23,2025-07,English,0,0,323,178,152,55 +2025-07-23,2025-07,Chinese,0,0,210,123,86,24 +2025-07-23,2025-07,Math,0,0,44,28,20,8 +2025-07-23,2025-07,Chinese,1,1,17,11,9,3 +2025-07-23,2025-07,Chinese,1,0,22,10,6,1 +2025-07-23,2025-07,Math,1,0,3,1,1,1 +2025-07-23,2025-07,Ace vocab,0,0,0,0,0,1 +2025-07-22,2025-07,English,1,0,489,339,268,13 +2025-07-22,2025-07,English,0,0,291,168,146,25 +2025-07-22,2025-07,Chinese,0,0,289,132,102,30 +2025-07-22,2025-07,Math,0,0,71,30,23,9 +2025-07-22,2025-07,Chinese,1,1,17,8,7,2 +2025-07-22,2025-07,Chinese,1,0,18,7,5,2 +2025-07-22,2025-07,Math,1,0,5,2,2,1 +2025-07-21,2025-07,English,1,0,539,356,281,10 +2025-07-21,2025-07,Chinese,0,0,366,199,136,63 +2025-07-21,2025-07,English,0,0,296,162,138,42 +2025-07-21,2025-07,Math,0,0,56,29,18,8 +2025-07-21,2025-07,Chinese,1,0,27,17,11,3 +2025-07-21,2025-07,Math,1,0,4,3,3,1 +2025-07-21,2025-07,Chinese,1,1,7,3,3,3 +2025-07-20,2025-07,English,1,0,494,333,272,11 +2025-07-20,2025-07,Chinese,0,0,409,214,126,55 +2025-07-20,2025-07,English,0,0,348,150,126,58 +2025-07-20,2025-07,Math,0,0,43,19,13,13 +2025-07-20,2025-07,Chinese,1,0,26,12,11,3 +2025-07-20,2025-07,Chinese,1,1,4,1,1,1 +2025-07-20,2025-07,Ace vocab,0,0,0,0,0,2 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+[已脱敏链接]" +2,,药品安全库存计算,合作开发,2026Q2-2026Q4,8,供应链,1.历史销售数据完整性达标（补充2023-2024年缺失的区域销售数据）；2.库存数据实时同步（打通ERP与WMS库存数据接口，解决现有数据延迟问题）；3.建立安全库存计算模型（结合季节、政策、促销等影响因子）,1.动态计算不同药品安全库存（如冷链药品、急救药品差异化阈值），库存周转率提升20%；2.缺货率从12%降至5%，减少因缺货导致的销售损失；3.避免盲目备货，库存成本降低15%,机器学习（回归分析）、时间序列分析、风险预警模型,小模型,1.内部：ERP销售数据（补充区域、季节维度）、WMS库存数据（实时同步库存位置、效期）；2.外部：历史促销活动数据、区域医药需求政策数据,可行性高：1.现有历史销售数据积累丰富，仅需补充少量缺失字段；2.时间序列算法成熟，适配药品销售周期性特征；3.现有WMS支持模块化扩展，可接入计算模型,供应链业务部门,1.数据补全：梳理2023-2024年区域销售数据，补全缺失的采购记录；2.模型构建：基于历史数据训练安全库存模型，纳入促销、政策（如集采扩围）影响因子；3.系统对接：将模型嵌入WMS系统，实现库存数据实时计算；4.试点验证：选取心血管类药品试点，对比原有静态阈值方案，优化后全量推广,"企业2医药零售连锁店——企业3供应链管理系统、ABC分类策略、ODBC数据库连接：减少库存积压86,000美元；通过安全库存设置和优化订购流程，提升了库存管理效率。 +[已脱敏链接]" +3,,合同要素智能提取,采购现有解决方案,2026Q2-2026Q4,8,供应链,合同电子化程度达80%以上，建立合同模板标准化体系,自动提取采购合同中的折让条款、返利政策，销售合同中的价格、折扣、付款条件，以及合同有效期等关键信息，方便后续审核以及自动化流程，预计每年降本150万元,OCR、NLP、知识图谱,大模型,公司内部合同管理系统、历史合同数据,可行性高：合同格式相对标准化，技术难度适中,供应链业务部门、财务管理部,1.文档电子化：扫描2022年前纸质合同，通过OCR初步识别文本；2.模板标准化：制定采购/销售合同统一模板，明确折让、返利等关键要素位置；3.模型开发：训练NLP模型提取关键要素，构建合同要素知识图谱；4.流程打通：用RPA将提取要素同步至ERP，实现“提取-审核-录入”自动化,"企业1的智能合同审核系统专注于确保医药流通合同的合规性。其系统能够从合同中提取超过50个关键要素，并与GSP规范的287条核心要求进行精准映射和校验。例如，系统会重点提取并核查运输条件（如冷链药品的温度监控要求）、药品有效期、追溯信息的上传与保存期限等关键条款，确保合同内容符合严格的行业监管要求。 +[已脱敏链接]" +4,,药品需求预测智能系统（批发）,合作开发,2026Q4-2027Q4,11,供应链,历史销售数据完整性达95%，建立品类管理标准化流程,基于历史销售、季节性、政策变化等多维度预测药品需求，库存周转率提升25%，缺货率降低40%,机器学习、时间序列分析,小模型,ERP销售数据、外部市场数据、政策信息,可行性中：需要大量历史数据训练，算法复杂度较高,供应链业务部门,1.数据整合：补全基层医疗机构销售数据，对接区域疾控发病率数据、集采政策平台；2.模型训练：基于历史数据训练LSTM需求预测模型，纳入季节、政策、疾病趋势因子；3.系统集成：将模型嵌入ERP采购模块，生成需求预测报表；4.迭代优化：每月对比实际销售与预测数据，调整模型参数,"企业名称：企业4 +应用的技术：智能预测系统（融合区域疾病趋势、医保政策等上百维数据） +达成的目标与效果：帮助合作药店（如企业5）库存周转效率提升30%；在流感季提前精准备货，避免缺货。 +网址：[已脱敏链接]" +5,,供应商风险智能预警助手（信用管理）,合作开发,2027Q3-2028Q3,11,供应链,供应商数据整合完成，建立风险评估指标体系,实时监控供应商经营状况、舆情信息，提前预警风险，预计避免损失200万元/年,NLP、知识图谱、机器学习,大模型+小模型,供应商财务数据、舆情数据、交易记录,可行性中：需要整合多源异构数据,供应链业务部门、风险管理部,1.数据打通：建立供应商数据中台，整合ERP、财务、法务数据；2.指标设计：制定财务（资产负债率）、舆情（负面投诉量）、履约（交货准时率）风险指标；3.系统开发：开发舆情爬取模块、风险分类模型，构建供应商知识图谱；4.预警落地：设置风险阈值，触发预警后推送至供应链部门，配套应对方案模板,"企业6企业7风险雷达、即时风险扫描、动态监测：提高了渠道准入门槛；对合作流通企业进行动态风险监测，提升了风险反应速度和应对能力 +[已脱敏链接]" +6,,创新药研发进展智能跟踪,合作开发,2026Q2-2026Q4,14,供应链,建立药品信息数据库，配置网络爬虫基础设施,自动跟踪创新药研发进展（含临床试验、审批进度），自动生成月度报告/调研报告，药品引进决策周期缩短50%,网络爬虫、NLP、Agent,大模型,国家药监局数据、医药研发平台数据,可行性高：信息源相对集中，技术实现难度适中,供应链业务部门,"AI知识库整合医药商业协会、药监局相关网站等数据，按“治疗领域-研发阶段-企业”分类追踪创新药动态。自动生成《月度创新药进展报告》，标注关键节点（如某PD-1抑制剂进入III期临床）并关联竞品分析，同步推送“潜在合作药企清单”。某企业应用后，创新药引进决策周期从3个月缩短至15天。 +1.爬虫部署：开发适配CDE、ClinicalTrials等平台的爬虫，定时抓取研发数据；2.数据清洗：用NLP提取关键信息（如试验阶段、适应症），标准化录入数据库；3.报告生成：配置报告模板，自动按“治疗领域-研发阶段-企业”分类，标注关键节点；4.推送落地：每月将报告推送至供应链部门，同步关联竞品分析与潜在合作药企清单","企业8HEC-PharmAI (全球首个药物制剂垂直领域自然语言大模型)构建了融入21万余条制剂配方、1.2万余篇期刊文献、2000余篇核心工艺专利的智能知识库，展示了利用AI聚合与解析研发知识的能力。 +[已脱敏链接]" +7,,采购价格智能比价系统,合作开发,2026Q2-2027Q2,8,供应链,供应商价格数据标准化，建立价格监控机制,实时比较不同供应商价格，优化采购决策，预计每年降本300万元,机器学习、数据挖掘,小模型,供应商报价数据、市场价格数据,可行性高：数据相对标准化，算法成熟,供应链业务部门,1.数据标准化：梳理现有报价数据，统一药品规格（如mg/片）、包装单位（如盒/箱）格式；2.接口对接：对接外部医药电商平台，获取实时市场均价；3.系统开发：开发比价模块，支持按药品品类、供应商等级筛选，自动生成比价报表；4.推广应用：先在抗生素品类试点，优化后覆盖全品类采购,"企业9：医药采购管理软件，支持自动抓取GSP认证供应商报价，一键生成价格-账期-质量三维度对比表。 +[已脱敏链接]" +8,,行业政策智能解读系统,合作开发,2026Q3-2027Q3,11,供应链,"建立政策文档标准化处理流程，配置自动化抓取工具； +集采、医保（目录变动）、监管政策内容具有固定网站信息源",自动抓取并解读集采、医保、监管政策，生成影响分析报告（含地区差异性分析与策略建议），政策响应速度提升80%,NLP、网络爬虫、知识图谱,大模型,政府采购平台数据、政策文件,可行性高：政策信息相对结构化,供应链业务部门、零售业务部门、法务部门、质量管理中心等,"AI知识库实时抓取医药商业协会、国家药监局等20+官方渠道政策，通过NLP技术拆解核心条款（如集采扩围品种、医保支付调整），自动生成“政策摘要-影响分析-应对方案”三维报告。例如：2025年某省集采政策出台后，系统1小时内完成120个中标品种的利润测算，推荐58个品种的库存调整方案。 +1.爬虫配置：开发工具定时抓取国家药监局、医保局等20+官方渠道政策；2.条款拆解：用NLP提取政策核心信息（如集采品种、执行时间），构建政策知识图谱；3.影响分析：关联内部销售/库存数据，测算政策对利润、库存的影响；4.报告推送：政策发布后1小时内推送报告至相关部门，配套库存调整、定价策略建议","企业10医药合规助手使用自然语言处理、规则引擎、大数据分析、流程自动化（RPA）技术，可实时抓取官方政策并解析关键条款，将法规匹配到具体业务场景（如处方流转、药品推广）并提供操作指南，并将合规要求通过系统审批流程进行自动化控制（如费用阈值），帮助某药企成功规避潜在处罚，节省法律成本超200万元。 +[已脱敏链接]" +9,,供应链协同智能调度,合作开发,2027Q3-2028Q3,14,供应链,跨区域数据打通，建立统一调度平台,优化跨区域库存调配，减少库存积压30%，提升供应链响应速度,优化算法、机器学习,小模型,各分子公司库存数据、销售预测数据,可行性中：需要复杂的系统集成,供应链业务部门、物流业务部门,1.数据整合：制定跨区域数据标准，打通各分子公司ERP/WMS/TMS接口，建立供应链数据中台；2.平台开发：开发统一调度平台，实现库存、运输数据可视化；3.算法部署：基于遗传算法开发调度模型，纳入运输成本、交货时间约束；4.试点运行：先在华东-华中区域试点，优化调度效率后推广至全国,"企业名称：企业11 +应用技术：九州云仓系统、实时数据监控、智能补货算法 +目标：优化库存周转，降低缺货与积压风险。 +降本/增效/提质：整合全国物流资源，实现库存信息共享；通过智能算法预测需求，药品周转率提升40%，库存周期缩短30%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +10,,药品质量追溯智能系统,采购现有解决方案,2027Q3-2028Q3,11,供应链,药品追溯码标准化，建立质量数据采集体系,自动追溯药品流向，快速定位质量问题，召回效率提升60%,区块链、OCR、物联网,小模型,药品追溯码数据、质量检验数据,可行性中：需要与监管平台对接,质量管理中心、供应链业务部门,1.追溯码补录：梳理2023年前药品库存，补录缺失的追溯码，确保全品类赋码；2.硬件部署：在冷链车、仓库加装温湿度传感器，实时采集环境数据；3.系统开发：开发追溯模块，用区块链存证流向数据，OCR识别追溯码；4.对接监管：与国家药品追溯平台对接，实现数据同步，测试召回流程,"企业名称：企业12 +应用的技术：智能合同、区块链存证、数据穿透、节点管控 +达成的目标与效果：合同履约透明度提升至100%，追溯效率提升500%；实现了从资质审核到结算付款的全流程可追溯。 +网址：[已脱敏链接]" +11,,首营资料智能审核,采购现有解决方案,2026Q3-2027Q1,8,供应链,首营资料电子化程度达90%，建立审核标准化流程,自动审核首营资料完整性和合规性，审核时间从2天缩短至2小时,OCR、NLP、规则引擎,大模型,首营资料档案、监管部门数据库,可行性高：审核规则相对固定,质量管理中心、供应链业务部门,1.资料电子化：扫描2022年前纸质首营资料，OCR识别并分类存储；2.规则配置：梳理审核规则（如证书有效期＞6个月、经营范围包含对应药品），录入规则引擎；3.系统开发：开发审核模块，自动比对资料与监管数据库，生成审核报告；4.试点推广：先审核新供应商资料，优化后覆盖历史资料复核,"企业名称：企业13-ERP（针对医疗器械经营企业） +应用的技术：首营数智化管理系统，通过数字化、自动化和智能化手段实现资料的快速收集、高效审核和智能管理。 +达成的目标与效果：实现了首营资料的电子化存储和自动化审核，提升了管理效率和合规性。 +[已脱敏链接]168.com/a2025/0218/6877/000006877724.shtml + +企业名称：企业11 +应用技术：数据要素产品“数药通”（药品数据集整合） +目标：优化首营业务流程，提升上下游协作效率。 +降本/增效/提质：通过统一数据标准，首营业务办理时间从30天缩短至3天，协作效率提升10倍。 +来源网址：[已脱敏链接] +[已脱敏链接]" +12,,药品分类智能管理,合作开发,2026Q4-2027Q4,8,供应链,药品基础数据完整，建立分类标准体系,自动对新增药品进行分类管理，分类准确率达95%，人工工作量减少70%,机器学习、NLP,大模型+小模型,药品基础信息数据、分类标准数据,可行性高：分类规则相对明确,供应链业务部门,1.数据补全：梳理现有药品数据，补全适应症、医保类型等字段，对接外部药品说明书数据库；2.模型训练：基于ATC编码、医保目录训练分类模型，纳入储存条件（如冷链/常温）因子；3.系统集成：将模型嵌入ERP，新增药品时自动生成分类结果；4.验证优化：人工复核前100个新增药品分类结果，调整模型参数,"企业14：基于深度学习的药品分类编码映射系统——将药品信息自动映射到ATC等标准分类编码，使用自然语言处理（NLP）、深度神经网络（如BERT、LSTM），该系统实现了药品分类的标准化和自动化，其原理同样适用于遵循国家药监局的分类规范（如药品本位码、分类大纲等）。 +[已脱敏链接]" +13,,供应商绩效智能评估助手,合作开发,2026Q3-2027Q1,8,供应链,供应商绩效数据标准化，建立评估指标体系,自动评估供应商交付质量、时效等绩效，优化供应商结构,机器学习、数据分析,小模型,供应商交付数据、质量数据、财务数据,可行性高：评估指标相对量化,供应链业务部门,1.数据打通：对接ERP、质量管理、财务系统，提取交付、质量、付款数据；2.指标定义：明确绩效指标计算口径（如交付准时率允许±1天误差）；3.模型开发：开发评分模型，按指标权重（交付40%、质量30%、服务30%）计算得分；4.应用落地：每月生成供应商绩效报表，标记优质（得分≥85）、待改进（60-84）、淘汰（＜60）供应商,"拓尔思为央企构建的供应商管理Agent，通过实时监测工商舆情、履约率、质量合格率等指标，自动生成绩效评分并动态调整供应商等级，风险预警响应速度提升。 +[已脱敏链接]" +14,,采购计划智能优化,合作开发,2027Q4-2028Q2,11,供应链,需求预测系统上线，库存数据实时同步,基于需求预测和库存状况优化采购计划，库存成本降低20%,优化算法、机器学习,小模型,需求预测数据、库存数据、供应商数据,可行性中：需要多系统协同,供应链业务部门,1.前置准备：确保项目4（需求预测系统）上线且稳定，打通ERP与WMS实时接口；2.规则梳理：收集采购约束条件（如供应商产能上限、最小订单量、运输周期）；3.模型开发：基于线性规划开发采购计划优化模型，纳入需求、库存、约束因子；4.试点验证：先在慢性病药品品类试点，对比人工计划，优化后全量推广,"企业1为某制造企业搭建的智能采购系统，结合历史消耗数据、季节性需求及库存状态，自动生成采购建议，库存周转率提升。 +[已脱敏链接]" +15,,药品召回智能管理,合作开发,2027Q3-2028Q1,8,供应链,药品追溯系统完善，建立召回流程标准化,快速定位需召回药品，自动生成召回方案，召回效率提升80%,机器学习、数据挖掘,小模型,药品流向数据、质量问题数据,可行性中：需要精确的追溯数据,质量管理中心、供应链业务部门,1.流程梳理：制定召回标准化流程（分一级/二级/三级召回），明确各部门职责；2.系统开发：基于追溯数据开发召回范围预测模型，用RPA自动生成召回方案、对接CRM发送通知；3.测试演练：模拟某批次药品召回，验证系统功能与流程衔接；4.上线应用：正式上线后，跟踪每起召回事件，优化模型与流程,"万里牛医药ERP解决方案：AI批号追踪、智能效期管理、冷链全链路监控，实现""一物一码""全链路追溯；效期异常自动锁定库存；召回事件响应速度从72小时提升至6小时。 +[已脱敏链接]" +16,,药品价格监控预警,采购现有解决方案,2027Q2-2027Q3,8,供应链,价格数据采集机制建立，市场价格监控体系完善,实时监控药品市场价格变化，及时预警异常波动,数据挖掘、异常检测,小模型,市场价格数据、供应商报价数据,可行性高：价格数据相对标准化,供应链业务部门,1.数据采集：开发价格采集工具，每日抓取电商平台、区域采购平台价格；2.阈值设置：按药品品类（如抗生素、心血管药）设置价格波动阈值（如±15%）；3.系统开发：开发异常检测模块，触发预警后推送至供应链部门；4.定价联动：对接ERP定价模块，提供价格调整建议，如市场降价时同步下调销售价,"企业/系统名称：国家医保局药品比价系统 +应用的技术：智能比价系统、药品价格异常预警模型、量价比较指数。 +达成的目标与效果：试点地区通过该系统已识别异常药品定价行为4.3万次，整改完成率达91%。 +[已脱敏链接]" +17,,采购合同智能生成,合作开发,2026Q4-2027Q2,8,供应链,合同模板标准化，法务审核流程电子化,基于采购需求自动生成标准化合同，合同生成效率提升70%,NLP、模板引擎,大模型,合同模板库、采购需求数据、法务条款库,可行性高：合同格式相对标准,供应链业务部门、法务部门,1.模板制定：联合法务部门制定采购合同统一模板，明确必备条款（如交货时间、质量标准、违约责任）；2.数据对接：打通ERP采购需求模块与合同系统，自动提取需求数据；3.系统开发：开发合同生成模块，用NLP填充模板、知识图谱校验合规性；4.审批对接：用RPA将生成合同推送至法务审批系统，跟踪审批进度,"企业名称：企业1（为某省级医药采购平台搭建系统） +应用的技术：智能合同、区块链存证、数据穿透、节点管控。 +达成的目标与效果：构建覆盖“资质审核-价格确认-订单执行-质量追溯-结算付款”的全流程可追溯体系，使医药采购的合同履约透明度提升至100%，追溯效率提升500%。 +[已脱敏链接]" +18,,供应链金融风险评估,合作开发,2027Q3-2028Q1,11,供应链,客户财务数据整合，风险评估模型建立,智能评估供应链金融业务风险，降低坏账率30%,机器学习、风险建模,小模型,客户财务数据、交易数据、外部征信数据,可行性中：需要复杂的风险建模,供应链业务部门、财务管理部,1.数据获取：与核心客户签订数据共享协议，对接其ERP、财务系统，补充现金流数据；2.模型训练：基于历史金融业务数据（成功/坏账案例）训练风险模型，纳入偿债能力（资产负债率）、履约记录（付款准时率）指标；3.系统开发：开发风险评估模块，对接外部征信平台，生成风险报告；4.试点运行：先在长期合作客户中试点，优化模型后推广至全客户,"企业名称：企业15 +应用的技术：自研的数据风控大模型。 +达成的目标与效果：基于医药B2B电商平台的交易场景，为下游药店提供数字信贷服务，融资利率低至3.9%，降低了平台的供应链金融服务融资成本。 +[已脱敏链接]" +19,,药品库存智能补货决策,合作开发,2026Q2-2026Q4,8,供应链,库存数据实时同步，需求预测系统稳定运行,基于销售预测和库存状况自动生成补货建议，缺货率降低50%,机器学习、优化算法,小模型,库存数据、销售预测数据、供应商数据,可行性高：补货逻辑相对清晰,供应链业务部门,1.接口优化：改造WMS与ERP接口，实现库存数据实时同步（延迟＜1小时）；2.规则配置：梳理补货规则（最小补货量、安全库存、交货周期）；3.模型开发：基于需求预测数据训练补货模型，生成补货建议（品种、数量、时间）；4.推广应用：先在零售门店试点，优化后覆盖仓库补货,"企业名称：企业4 +应用的技术：智能预测系统（融合区域疾病趋势、医保政策等上百维数据）。 +达成的目标与效果：帮助合作药店（如企业5）库存周转效率提升30%；在流感季提前精准备货，避免缺货。 +[已脱敏链接]" +20,,GSP质量飞检智能自查,合作开发,2026Q4-2027Q2,8,供应链,质量检测设备智能化改造，检测数据标准化。应对药监飞检的高频次、高标准合规要求，降低不合规风险。,利用AI技术提升药品质量检测精度和效率，检测效率提升40%,计算机视觉、机器学习,大模型+小模型,质量检测数据、药品图像数据,可行性中：需要硬件设备配合,质量管理中心,"AI知识库整合GSP全条款（含2025年最新修订版）、历史飞检案例（国家药监局公开通报1200+案例）、企业运营数据，构建“条款-数据-风险”映射模型。通过对接ERP系统自动抓取温湿度记录、药品存储台账、人员培训档案等数据，实时比对生成自查报告：标注“高风险项”（如冷链药品超温10分钟以上）并推送整改模板，同步模拟飞检流程生成迎检清单。 +1.硬件改造：在仓库、冷链车加装温湿度传感器、高清摄像头，实时采集数据；2.知识库构建：整理GSP2025版条款、历史飞检案例，建立“条款-数据-风险”映射关系；3.系统开发：开发自查模块，用计算机视觉识别违规行为，比对数据生成报告；4.整改落地：推送高风险项（如冷链超温）及整改模板，跟踪整改进度","企业1为某中药企业开发的合规自查系统，自动比对GSP条款与企业操作记录，标记高风险环节（如温湿度记录缺失），人工复核效率提升。 +[已脱敏链接]" +21,,采购订单智能匹配,合作开发,2027Q2-2027Q4,8,供应链,订单数据标准化，供应商产品目录完善,自动匹配采购需求与供应商产品，匹配准确率达95%,机器学习、相似度算法,小模型,采购需求数据、供应商产品数据,可行性高：匹配规则相对明确,供应链业务部门,1.数据标准化：梳理采购需求数据，统一药品规格（如mg/片）、质量要求（如GMP认证）格式；2.目录完善：收集供应商产品信息，补充规格、产能、价格字段，建立供应商产品库；3.系统开发：开发匹配模块，用相似度模型匹配需求与产品，规则引擎排序（价格40%、交期30%、绩效30%）；4.应用落地：先在常规药品采购中试点，优化后覆盖全品类,"企业名称：企业16 +应用的技术：该系统整合了采购计划管理、供应商分级评价、智能库存预警等核心模块。 +达成的目标与效果：系统能根据采购需求自动推荐符合资质的供应商，并支持历史交易数据对比。该系统的应用使得采购周期从平均15天缩短至7天（缩短50%），人力成本节约50%，同时库存周转率提高了30%。 +网址：[已脱敏链接]" +22,,供应链异常智能预警,采购现有解决方案,2027Q4-2028Q1,11,供应链,供应链数据监控体系建立，异常识别规则完善,实时监控供应链各环节，智能识别异常情况并预警,异常检测、机器学习,小模型,供应链全流程数据,可行性中：需要全链条数据整合,供应链业务部门,1.数据中台建设：整合ERP、WMS、TMS、CRM数据，建立供应链数据中台；2.规则梳理：制定各环节异常规则（如采购延迟＞3天、库存＜安全库存50%）；3.系统开发：开发异常检测模块（用孤立森林算法）、可视化预警平台；4.响应机制：设置异常分级（一般/重要/紧急），推送至对应负责人，跟踪处理进度,"企业名称：企业17（为新华制药、科伦集团等药企提供解决方案） +应用的技术：接入DeepSeek大模型，构建数字化智能中枢，用于偏差分析、风险预警等场景。 +达成的目标与效果：系统能实时分析生产、检验数据，提前72小时预警潜在偏差，使质量管控从“事后灭火”转向“事前防控”。 +网址：[已脱敏链接]" +23,,药品评审智能跟踪,采购现有解决方案,2026Q2-2026Q4,8,供应链,1.建立药品评审数据库（补充历史评审数据，如评审阶段、意见）；2.配置评审平台爬虫（定时抓取国家药品评审中心CDE数据）；3.构建评审阶段分类标准（如受理、审评、审批、上市）,1.自动跟踪国家药监局CDE药品评审进度，更新频率从每周1次提升至每日1次；2.评审关键节点（如发补通知、获批）自动提醒，避免错过跟进时机；3.生成评审进度报表，为药品引进决策提供支撑,网络爬虫、NLP（评审信息提取）、规则引擎（节点提醒）、数据可视化,大模型,1.内部：药品评审数据库（补充历史数据）；2.外部：国家药品评审中心CDE官网、医药研发平台（如药智网）,可行性高：1.CDE数据公开且格式规范，爬虫易抓取；2.评审阶段分类明确，NLP可精准提取关键节点；3.开发难度低，可复用项目6“创新药研发进展跟踪”的爬虫技术,供应链业务部门,1.爬虫开发：开发适配CDE官网的爬虫，每日抓取评审数据（药品名称、阶段、意见）；2.数据清洗：用NLP提取关键信息（如评审阶段、发补时间），标准化录入数据库；3.提醒配置：设置关键节点提醒（如获批前1周、发补通知），推送至供应链部门；4.报表生成：每月生成评审进度报表，按治疗领域分类展示,"企业名称：企业18 +应用的技术：基于人工智能的药品智慧审批系统，具备智能分派、智能审评等功能。 +达成的目标与效果：在药品上市后场地变更等场景中，系统能自动解析申报内容，精准触发审评、检查等流程。该系统实现试点审评事项效率提升30%以上，试点审批品种全流程时限缩短至以往的50%以内。 +网址：[已脱敏链接]" +24,,药品采购成本智能分析,合作开发,2026Q3-2026Q4,8,供应链,成本数据标准化，分析模型建立,深度分析采购成本构成，识别降本机会，预计每年降本200万元,数据挖掘、成本分析模型,小模型,采购成本数据、市场价格数据,可行性高：成本数据相对完整,供应链业务部门、财务管理部,1.数据标准化：梳理采购成本数据，统一构成字段（药品价、运费、税费、服务费）；2.模型开发：开发成本分析模型，分析成本结构、历史趋势，识别降本机会（如运费占比过高则建议集中运输）；3.报表生成：用BI工具制作成本分析报表，支持按品类、供应商筛选；4.降本落地：根据分析结果制定降本方案（如与3家供应商谈集中采购），跟踪效果,"企业名称：企业16 +应用的技术：数据分析看板，提供采购成本分析、供应商绩效评估等20+种报表模型。 +达成的目标与效果：系统通过数字化升级，助力217家医疗机构平均降低采购管理成本28%。 +网址：[已脱敏链接]" +25,,智能客服（批发）,合作开发,2026Q4-2027Q2,11,供应链,1.建立批发客服知识库（含订单查询、库存咨询、物流跟踪等常见问题）；2.对接ERP、WMS、TMS系统（获取订单、库存、物流数据）；3.配置多渠道接入（电话、企业微信、邮件）,1.24小时响应批发客户咨询，常见问题解决率达80%，人工客服工作量减少50%；2.客户咨询响应时间从30分钟缩短至1分钟，客户满意度提升25%；3.减少人工客服成本，每年节约30万元,对话系统（多轮对话）、NLP（意图识别、问答匹配）、知识图谱（客服知识库）、RPA（数据查询）,大模型,1.内部：ERP订单数据、WMS库存数据、TMS物流数据、历史客服对话记录；2.外部：无（知识库基于内部数据）,可行性中：1.批发客服知识库需覆盖多场景（订单、库存、物流），需长期积累；2.多轮对话功能开发难度高，需大量对话数据训练；3.多渠道接入需对接不同平台接口,供应链业务部门,1.知识库建设：收集批发客户常见问题（如“订单何时发货”“库存是否充足”），整理答案并结构化；2.系统开发：开发对话系统，实现意图识别、多轮对话，用RPA对接ERP/WMS/TMS查询数据；3.渠道接入：对接电话、企业微信、邮件渠道，实现统一响应；4.迭代优化：分析客服对话记录，补充知识库，优化意图识别准确率,"企业名称：企业4 +应用的技术：AI药师助手，基于企业19大模型技术。 +达成的目标与效果：助手能即刻调取专业资料解答用户关于药品的疑问，相当于给药师配了“小老师”，给顾客配了“随身医药顾问”。 +网址：[已脱敏链接] + +企业名称：企业11 +应用技术：RAG（检索增强生成）、知识图谱、跨系统操作优化 +目标：提升客服响应效率，缓解人工压力。 +降本/增效/提质：自研的药九九AI“虚拟客服”每年节省448万元坐席费用，客服坐席跨系统操作效率提升30%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +26,,供应商质量智能评估助手,合作开发,2026Q1-2026Q3,8,供应链,1.供应商质量数据整合（对接质量管理系统、采购验收记录、客户投诉数据）；2.建立质量评估指标体系（含验收合格率、投诉率、质量整改完成率）；3.对接外部质量监管数据（如药监局处罚记录）,1.自动评估供应商质量管理体系和能力，评估周期从20天缩短至5天；2.质量评估准确率达90%，精准识别低质量供应商（如验收合格率＜90%）；3.供应商质量问题减少30%，降低后续质量风险,机器学习（质量评分模型）、数据分析、可视化报表、风险预警,小模型,1.内部：质量管理系统验收记录、客户投诉数据（CRM）、供应商整改记录；2.外部：国家药监局处罚记录、行业质量排名,可行性高：1.内部质量数据集中在质量管理系统，易整合；2.评估指标量化（如验收合格率=合格次数/总次数），模型计算简单；3.外部监管数据公开，易获取,供应链业务部门、质量管理中心,1.数据整合：对接质量管理系统、CRM、供应商整改记录，提取质量数据；2.指标设计：制定质量评估指标（验收合格率50%、投诉率20%、整改完成率30%）；3.系统开发：开发评分模型，计算供应商质量得分，生成评估报表；4.应用落地：每季度生成供应商质量报告，作为合作续签、淘汰依据,"企业名称：企业20（服务全球制药公司） +应用的技术：QualityInsightsPlatform（质量洞察平台），基于来自4,500多次审计的专有数据库。 +达成的目标与效果：该人工智能平台能将新供应商资质认证及前瞻性质量现场风险管理所需的时间和成本降低至少65%。 +网址：[已脱敏链接]" +27,,品类动销智能分析,合作开发,2026Q1-2026Q2,8,供应链,1.完善品类数据（补全药品品类属性，如畅平滞分类、区域销售特征）；2.建立动销分析模型（含动销率计算、影响因子分析）；3.对接ERP销售数据、WMS库存数据,"根据影响采购周期的特征（畅平滞、省内省外、医院品种、预付款、核心品种），计算针对不同供应商最合适的采购周期 + +***供应商评价和管理： +***具体采购策略：销售预测（基于品类、周期、空间）——第一优先级、销售ROI（差价空间、回款周期、结算方式） +1.自动分析药品品类动销情况（如畅销品动销率＞90%、滞销品＜30%），分析周期从7天缩短至1天；2.识别滞销品类（如某抗生素动销率25%），制定清库存方案，库存积压减少40%；3.为采购策略提供支撑（如畅销品增加采购量），销售增长率提升5%",数据挖掘（动销率分析模型）、机器学习（影响因子识别）、可视化分析、策略推荐,大模型+小模型,1.内部：ERP销售数据（按品类、区域、周期）、WMS库存数据（滞销品库存）；2.外部：区域疾病发病率数据（影响动销）、竞品动销数据,可行性高：1.品类数据仅需补充畅平滞分类字段，易完善；2.动销率计算逻辑简单（动销率=销售数量/库存数量）；3.现有BI工具可支撑分析报表,供应链业务部门,1.数据补全：梳理药品品类，按销售情况分类（畅销/平销/滞销），补充区域销售特征字段；2.模型开发：开发动销分析模型，计算动销率，识别影响因子（如季节、疾病趋势）；3.报表生成：制作动销分析报表，标注滞销品类及建议（如促销清库存）；4.策略落地：根据报表调整采购策略（畅销品增加20%采购量），跟踪销售效果,"企业名称：企业4 +应用的技术：智能预测系统，融合区域疾病趋势、医保政策变化等上百维数据。 +达成的目标与效果：系统通过深度学习百万份临床数据，使药店库存周转效率提升30%，并在试运行期继续降低库存成本。 +网址：[已脱敏链接]" +28,,单据智能核对系统,采购现有解决方案,2026Q4-2027Q4,5,物流,1.部署智能扫描设备（OCR识别适配医药单据格式）；2.打通ERP、WMS、供应商电子单据系统接口；3.建立单据核对规则（如订单号、药品规格、数量匹配）,"使用OCR技术识别单据自动识别匹配； +可实现智能单据统一打印 +1.自动识别单据信息（采购单、入库单、出库单），核对时间从1小时/批次缩短至10分钟/批次；2.核对准确率达98%，减少人工核对错误（如数量不符）；3.自动生成收货记录并归档单据，单据管理效率提升80%",OCR、NLP（语义匹配）、RPA（系统查询/归档）、数据比对算法,大模型,1.内部：ERP订单数据、WMS库存数据、扫描设备OCR识别数据；2.外部：供应商电子单据系统（如采购单、发货单）,可行性高：1.OCR技术成熟，适配医药单据（含药品规格、数量字段）；2.核对规则明确（订单号、规格、数量一致），易配置；3.RPA可直接对接现有ERP/WMS接口,物流业务部门,1.设备部署：采购智能扫描设备，调试OCR识别功能（适配医药单据）；2.接口对接：打通ERP、WMS与供应商电子单据系统，实现数据互通；3.系统开发：开发核对模块，OCR识别单据→NLP语义匹配→RPA查询WMS验证；4.归档落地：核对成功后自动生成收货记录，单据电子化归档,"企业名称：企业21 +应用的技术：药械自动识别和数据采集系统，采用OCR（光学字符识别）技术和数据扩增方案。 +达成的目标与效果：该系统使药械信息复核工作效率提升50%，每单耗时从约两分半钟缩短至57秒，且复核准确度高达99.9%。 +网址：[已脱敏链接]" +29,,货物状态智能核验系统,合作开发,2027Q3-2028Q3,8,物流,1.部署图像识别设备（仓库入口、卸货区安装高清摄像头）；2.建立药品外观特征库（含批号、有效期、包装样式）；3.对接WMS订单数据,"利用图像识别技术比对到货商品与订单信息的一致性（如批号、有效期、包装完整性），替代人工肉眼判断，减少错收风险 +1.自动比对到货商品与订单信息一致性（批号、有效期、包装完整性），核验时间从30分钟/车缩短至5分钟/车；2.错收率降低90%，避免因错收导致的退货成本；3.减少人工肉眼判断，降低人力成本",计算机视觉（图像识别）、特征匹配算法、数据比对、异常预警,小模型,1.内部：WMS订单数据（药品批号、有效期、包装规格）、图像识别设备采集数据；2.外部：无（特征库基于内部药品数据）,可行性中：1.图像识别设备需硬件投入（高清摄像头、AI识别终端）；2.药品外观特征库需覆盖全品类，需人工录入（如特殊包装药品）；3.复杂场景（如包装破损轻微）识别准确率需优化,物流业务部门、质量管理中心,1.设备部署：在仓库入口、卸货区安装高清摄像头，连接AI识别终端；2.特征库建设：录入所有药品外观特征（批号位置、有效期格式、包装样式）；3.系统开发：开发核验模块，图像识别→特征匹配→与订单比对；4.异常处理：核验不一致时（如批号不符）触发预警，通知人工复核,"企业名称：企业22 +应用的技术：智慧医药供应链中心，使用唯一条形码、智能算法、温湿度传感器及全程数字化监控。 +达成的目标与效果：堆垛机通过扫描条形码自动匹配货架位置，误差率仅为十万分之一；冷库温度波动超过阈值时，系统会自动启动备用设备并推送预警。 +网址：[已脱敏链接]" +30,,仓储设备智能管理系统,合作开发,2027Q4-2028Q4,8,物流,设备物联网改造，设备运行数据采集，预测性维护体系建立,"根据自动化设备（如AGV小车、自动分拣系统）和智能仓储管理系统（WMS），评估设备的利用率，提高高效存储与调度。 + +***建设配置：选型配置调试（AI辅助） +***运营维护：应用、状态识别、维修保养——优先",机器学习、预测性维护,小模型,设备运行数据、维护记录、故障数据,可行性中：需要设备数据采集和建模,物流业务部门、设备维护部门,1.设备改造：为AGV小车、自动分拣系统加装传感器，实现运行数据实时采集；2.数据积累：采集设备运行、故障、维护数据，建立设备数据库；3.模型开发：训练预测性维护模型，设置故障预警阈值；4.调度优化：开发设备调度模块，基于利用率动态分配任务，推送维护提醒,"企业名称：企业22 +应用的技术：智慧医药供应链中心，采用自动化立体仓库、堆垛机、AGV（自动导引车）智能拣选机器人及智能调度系统。 +达成的目标与效果：实现了“货找人”的拣选模式，分拣速度飙升至2500件/小时，相当于15名熟练工人同时作业，物流成本预计降低30%以上。 +网址：[已脱敏链接]" +31,,运输路线智能优化,合作开发,2026Q2-2026Q4,11,物流,运输数据采集完善，地理信息系统建立，TMS系统升级,智能规划最优运输路线，运输成本降低20%，配送时效提升30%,优化算法、机器学习、GIS,小模型,运输路线数据、交通数据、客户地址数据,可行性高：路线优化算法相对成熟,物流业务部门,1.数据补全：梳理TMS历史运输数据，补全路线、时间、成本字段；2.接口对接：对接高德地图API，获取实时交通、天气数据；3.系统开发：开发路线优化模块，嵌入遗传算法，生成最优路线；4.应用落地：先在市内配送试点，优化后推广至跨市运输,"企业名称：企业23 +应用的技术：AI智能调度中枢，整合千万级历史运输数据、区域货量密度、订单波峰波谷与实时路况进行路径规划。 +达成的目标与效果：有效降低了车辆的空驶率，并极大提升了整体配送效率与服务稳定性。 +来源网址：[已脱敏链接] + +企业名称：企业11 +应用技术：九州云仓系统、AI算法、历史配送数据建模 +目标：降低车辆空置率，提升配送效率。 +降本/增效/提质：整合全国125个物流中心、1700余台车辆数据，优化配送路径；武汉至恩施的车辆空驶里程从全程缩减至部分路段，显著降低物流成本。 +来源网址：[已脱敏链接] +[已脱敏链接]" +32,,智能装车系统,合作开发,2026Q2-2027Q2,11,物流,车辆信息数据化，货品尺寸数据完善，装车算法开发,"通过机器识别等技术，检测并收集货车外形尺寸、药品大小等，实现自动分配装载药品位置和顺序，提高装车效率，减少人工错误。 +***发货装车：哪些车（自有+外派），车型车箱空间确定，药品包装件数、尺寸也是确定的，算法优化装车；需方给了一个接货清单，基于某辆车、某次需求清单，优化出装载清单。约束：车辆空间、药品包装尺寸（需求清单关联） +***上下货的智能化：装卸的智能化，空间位的规划、现场的上下料的智能化（机械臂、机器人、托盘）——硬件算法 +自动计算最优装车方案，车辆利用率提升25%，装车效率提升50%",优化算法、三维建模,小模型,车辆信息数据、货品尺寸数据、订单数据,可行性高：装车优化算法相对成熟,物流业务部门,1.数据录入：收集自有/外派车辆信息（长/宽/高、载重）、药品包装数据（尺寸、重量、堆叠限制）；2.算法开发：基于三维装箱算法开发装车模型，考虑卸货顺序（后装先卸）、承重限制；3.可视化展示：生成3D装车方案，指导工人装车；4.试点优化：先在常温药品装车试点，调整算法适配冷链药品（需预留制冷空间）,"宝佳智能为多家食品企业提供服务，基于视觉的并联机器人、高速码垛机器人、智能算法，实现智能分拣装箱，减少一线人员70%以上，生产节拍提升至280包/分钟。 +[已脱敏链接]" +33,,冷链运输智能监控,采购现有解决方案,2027Q3-2027Q4,8,物流,冷链设备物联网改造，温湿度传感器部署，监控平台建设,实时监控冷链运输温湿度，智能预警异常，冷链事故率降低80%,物联网、传感器技术、异常检测,小模型,冷链设备数据、温湿度数据、运输路线数据,可行性中：需要硬件设备改造,物流业务部门、安全生产部门,1.设备改造：为所有冷链车、冷藏箱加装温湿度传感器、GPS，确保数据实时传输；2.阈值设置：按药品类型设置温湿度阈值（如冷藏2-8℃、冷冻-18℃以下）；3.平台开发：开发监控平台，实时展示位置、温湿度，触发预警后推送至司机与调度中心；4.应急处理：制定异常处理流程（如温超标时就近停靠制冷），定期演练,"企业名称：企业24（为多家跨国药企和医药流通企业提供解决方案） +应用的技术：物联网控制器、工业级传感器网络、边缘计算、区块链存证。 +达成的目标与效果：实现全程温湿度秒级报警与云端存证，使药品货损率平均下降90%；人工巡检效率提升70%。 +来源网址：[已脱敏链接] + +企业名称：企业11 +应用技术：GPS定位、温湿度传感器、冷链车联网系统 +目标：保障冷链药品运输全程可追溯，提升质量安全。 +降本/增效/提质：实时监控车辆位置、温度等数据，确保疫苗等冷链药品运输合规；通过智能调度优化路线，降低运输损耗。 +来源网址：[已脱敏链接] +[已脱敏链接]" +34,,库房存储温湿度影响分析,合作开发,2026Q1-2026Q2,8,物流,1.仓库温湿度数据采集完善（加装传感器，补全历史数据）；2.建立温湿度影响模型（分析温湿度对药品效期、质量的影响）；3.对接WMS库存数据（药品存储位置、效期）,1.自动分析仓库不同区域温湿度差异（如靠近门口区域波动大），优化存储布局，药品效期延长10%；2.识别温湿度异常区域（如某货架温湿度超标），及时调整，质量问题减少40%；3.为仓库改造提供数据支撑（如加装空调、密封门）,数据分析（温湿度趋势分析）、机器学习（影响因子模型）、可视化报表、优化建议生成,小模型,1.内部：仓库温湿度传感器数据（历史+实时）、WMS药品存储数据（位置、效期、质量记录）；2.外部：药品说明书（温湿度要求）、GSP存储规范,可行性高：1.温湿度传感器部署成本低，历史数据可短期积累；2.影响分析逻辑简单（对比不同区域药品效期、质量差异）；3.现有BI工具可支撑报表生成,物流业务部门、质量管理中心,1.传感器部署：在仓库各区域（货架、门口、角落）加装温湿度传感器，采集历史数据（1个月）；2.模型构建：分析温湿度与药品效期、质量的关联（如温湿度高则效期短）；3.报表生成：制作温湿度影响分析报表，标注异常区域；4.布局优化：根据报表调整存储布局（如效期短药品存温湿度稳定区域），必要时改造仓库,"企业11广东30米超高立体库采用百奥除湿机，通过AI算法动态调节湿度至60%RH以下，保障冷链药品质量。 +[已脱敏链接]" +35,,配送车辆智能调度,合作开发,2026Q2-2026Q4,11,物流,车辆GPS定位系统完善，调度算法开发，实时数据采集,"通过人工智能算法和数据分析，实现精确的路线规划和共享车辆的调度，提高出行效率和资源利用率。 + +***排队叫号系统优化：考虑紧急程度/货源的满足程度（特殊例外）、预约-现场签到排队（考虑流量上限） +***共享车辆（自有+社会车辆——逐步扩大社会车辆，加入滴滴系统）：不同车的来源共享，送货如果有同一路线沿线订单，合并到同一辆车里 +***路线规划：常规情况不需要，异常情况下需要 +单一司机/特殊季节的配送 +***面向司机端的智能助理 + +实时优化车辆调度，提高车辆利用率30%，配送效率提升40%",优化算法、实时调度,小模型,车辆位置数据、订单数据、交通数据,可行性高：调度算法相对成熟,物流业务部门,1.GPS优化：检查所有配送车辆GPS，确保在线率100%，数据采集频率1次/2分钟；2.算法开发：开发实时调度模型，用聚类算法合并同路线订单，考虑订单优先级（如急救药品优先）；3.调度平台：开发可视化调度平台，展示车辆位置、订单状态，支持人工干预；4.应用推广：先在城市配送试点，优化后覆盖跨区域调度,"企业名称：企业25 +应用的技术：菜鸟无人车配送车队。 +达成的目标与效果：配送成本降低50%，配送效率提升70%。将以往""今天发货明日配送""变为""一日三配""，并开通了一小时紧急配送服务。 +来源网址：[已脱敏链接]" +36,,物流成本智能分析,合作开发,2027Q1-2027Q2,8,物流,物流成本数据标准化，成本分析模型建立,深度分析物流成本构成，识别降本机会，预计每年降本250万元,数据挖掘、成本分析模型,小模型,物流成本数据、运输数据、仓储数据,可行性高：成本数据相对完整,物流业务部门、财务管理部,1.数据标准化：梳理物流成本数据，统一构成字段（运输费、仓储费、人工费、燃油费）；2.模型开发：开发成本分析模型，分析结构、趋势，识别降本机会（如燃油费高则优化路线）；3.报表生成：制作物流成本报表，支持按环节、区域筛选；4.降本落地：根据分析结果制定方案（如与物流公司谈长期合作降运费），跟踪效果,"企业名称：企业26（应用药店智能车辆管理系统） +应用的技术：智能车辆管理系统，通过物联网与AI算法进行订单智能匹配、路径动态优化。 +达成的目标与效果：帮助企业26降低30%配送成本，车辆利用率提升85%。 +来源网址：[已脱敏链接]" +37,,智能分拣系统,合作开发,2026Q4-2027Q4,11,物流,分拣设备智能化改造，订单数据结构化，分拣算法开发,自动优化分拣路线和顺序，分拣效率提升50%，错误率降低70%,机器学习、计算机视觉、优化算法,小模型,订单数据、商品信息、仓库布局数据,可行性中：需要硬件设备配合,物流业务部门,1.设备改造：为现有分拣线加装扫码器（识别药品条码）、分拣机械臂（按区域分拣）；2.数据准备：统一订单分拣要求（如按区域、客户、药品类型）；3.算法开发：开发分拣优化模型，按订单优先级、设备负载动态调整顺序；4.调试上线：先在常规药品分拣试点，优化后覆盖特殊药品（冷链、易碎）,"企业名称：企业22 +应用的技术：自动分拣系统、高精度扫描仪。 +达成的目标与效果：分拣速度飙升至2500件/小时，相当于15名熟练工人同时作业。系统还能通过视觉识别实时监测并""自我纠错""，拦截错分药品。 +来源网址：[已脱敏链接] + +企业名称：企业11 +应用技术：AGV智能机器人、地空一体托盘穿梭车、货到人拣选系统 +目标：提升仓储物流自动化水平，降低人力成本。 +降本/增效/提质：武汉东西湖物流中心拣选效率达2000条目/小时，吞吐效率提升5倍；立体库单班仅需2名操作工，库容存储密度提高200%。 +来源网址：[已脱敏链接] +[已脱敏链接] +[已脱敏链接]" +38,,物流跟踪智能系统,合作开发,2026Q3-2027Q3,8,物流,物流节点数据采集，跟踪系统建设，客户接口开发,实时跟踪货物配送状态，提供精准的配送信息，客户满意度提升30%,物联网、实时数据处理,小模型,车辆位置数据、订单状态数据,可行性高：技术相对成熟,物流业务部门、客户服务部,1.设备部署：在仓库出库口、5个区域配送点加装扫码设备，调试数据采集功能（确保扫描后10秒内同步至系统）；2.系统对接：改造TMS与GPS接口，实现位置数据5分钟更新一次，关联运单号与节点时间；3.客户接口开发：开发企业微信小程序查询入口（支持运单号查询、状态实时显示、预计送达时间），官网同步嵌入查询模块；4.异常配置：设置节点超时规则（如出库后24小时未到中转点、派送前6小时未更新位置），RPA自动推送预警至物流调度员；5.试点推广：先在南京本地医院配送试点，收集客户反馈优化界面，1个月后覆盖江苏省内全线路,"重庆军卫医药：引入TMS运输管理系统，实现配送信息及轨迹的可视化查询，并对冷链药品进行在途温湿度监控. +[已脱敏链接]" +39,,仓库货品智能盘点,合作开发,2027Q4-2028Q2,8,物流,RFID技术部署，盘点系统开发，库存数据实时同步,"自动化库存盘点，盘点效率提升80%，准确率达99%以上； +利用AI视觉检测识别损坏、临期、过期药品并及时发出预警，提供处理建议。",RFID、计算机视觉、自动化技术,小模型,库存数据、商品信息、RFID标签数据,可行性中：需要RFID技术部署,物流业务部门,1.模型搭建：用激光扫描仪采集2个主力仓库数据，建立三维模型，标注温区、货架承重、通道宽度；2.数据训练：提取近3个月库存数据（销量TOP100药品、温区要求、拣货频次），训练存储优化模型，设置优先级规则（销量高＞温区严格＞拣货频次高）；3.系统开发：开发空间规划模块，嵌入WMS系统，入库时自动推荐存储位置，生成最优拣货路径；4.试点验证：选取常温区100种药品试点，对比原人工规划方案，空间利用率提升至80%后全仓库推广；5.迭代优化：每月分析空间利用率、拣货效率数据，调整模型中销量与温区的权重占比,"重庆军卫医药：通过部署WMS仓储管理系统，对药品进行跟踪、追溯和统计，提升了盘点等作业的准确性。 +[已脱敏链接]" +40,,智能货架管理系统,合作开发,2027Q3-2028Q3,8,物流,货架传感器部署，货架管理系统开发,实时监控货架库存状态，自动补货提醒，货架利用率提升30%,物联网、传感器技术,小模型,货架数据、库存数据、销售数据,可行性中：需要硬件设备改造,物流业务部门,1.设备配备：为20名拣货员、30名配送司机配备作业记录仪，设置数据采集频率（拣货员每完成1单上传1次，司机每完成1个配送点上传1次）；2.指标定义：联合HR部门制定绩效指标，明确计算口径（如拣货准确率=无差错拣货订单数/总拣货订单数，允许±1件误差），设置权重（拣货效率30%、准时率30%、货损率20%、客户评价20%）；3.系统开发：开发绩效评估模块，自动抓取作业数据计算得分，生成个人/团队绩效报表；4.薪酬对接：用RPA将每月绩效得分同步至HR薪酬系统，按得分区间（≥90分奖2000元，80-89分奖1500元）自动计算奖金；5.应用落地：先在南京本地物流团队试点，2个月后推广至江苏省内所有物流人员,"企业名称：企业22 +应用的技术：AGV（自动导引车）智能拣选机器人、""货到人""拣选系统。 +达成的目标与效果：实现了""货找人""的拣选模式，一名员工即可轻松应对，改变了传统仓库需多人拉车找货的局面，大幅提升了拣选效率。 +来源网址：[已脱敏链接]" +41,,物流异常智能处理,采购现有解决方案,2027Q2-2027Q4,8,物流,异常事件数据采集，异常处理流程标准化,智能识别和处理物流异常事件，异常处理效率提升60%,异常检测、机器学习、流程自动化,小模型,异常事件数据、处理流程数据,可行性高：异常处理流程相对标准,物流业务部门,1.数据整合：补全近2年冷链药品区域销售数据（重点补充苏北、苏中乡镇卫生院数据），对接区域疫情平台、气象数据接口，建立冷链需求数据库；2.模型训练：基于LSTM算法训练预测模型，纳入季节（夏季高温）、政策（集采扩围）、疫情（局部爆发）三大影响因子，设置动态权重规则；3.系统对接：将预测模型嵌入TMS冷链调度系统，每月生成冷链需求报表（区域需求分布、车辆需求数量）；4.资源调配：根据预测数据提前调配冷藏车（如夏季向苏南地区增配5辆冷藏车），设置应急储备车辆（2辆备用冷藏车）；5.验证优化：每季度对比实际需求与预测数据，调整模型中疫情、温度因子的权重,"四方麒麟物流大模型整合千万级历史运输数据，实时监控路况与车辆状态，自动推荐备选路线或承运商，异常处理响应速度提升。 +[已脱敏链接]" +42,,物流质量管理助手,合作开发,2026Q2-2026Q4,8,物流,质量监控指标体系建立，数据采集系统完善,"实时监控仓库人员操作合规性，含抽检行为合规性识别，保证物流仓储流程的质量合规性； +将验收过程视频片段、关键参数截图、环境监测数据打包上链，形成不可篡改的数字档案，为后续追溯提供可信依据",数据分析、质量管理,小模型,物流服务数据、客户反馈数据、质量指标数据,可行性高：质量指标相对明确,物流业务部门、质量管理中心,1.数据整合：对接现有物流管理系统，整合运输、仓储、配送全链路数据；2.算法开发：构建质量异常检测模型和预测分析算法；3.系统部署：开发质量管理仪表板和预警系统；4.试点验证：选择重点物流线路进行试点应用；5.全面推广：优化完善后在全公司物流网络推广应用,"企业名称：企业23 +应用的技术：物联网与人工智能技术融合，构建“动态监控-智能管控-流程优化-决策支持”体系，具备轨迹追踪、实时温控及合规监测功能。 +投资金额：未公开 +达成的目标与效果：系统可实时采集运输车辆温湿度数据，自动生成温度曲线并比对药品温度阈值，一旦偏移立即触发三级预警。通过质量数字化管理，在满足GSP法规要求的同时提升了运营效率。" +43,,智能仓储布局优化,合作开发,2027Q4-2028Q2,11,物流,仓库布局数据采集，优化算法开发,"根据订单计划、波次品类、分拣路径等，结合距离、热度、相关性的货位分配原则，实现自动规划货位及拣货路线。 + +***老库优化：根据进出频次、根据上下装载需求、存放本身的特殊性（摆放）；AGV小车路线（进出）；立库位置 +***新库设计：功能、品类、进出、储管要求 + +优化仓库布局设计，提高空间利用率和作业效率",优化算法、仓库设计,小模型,仓库布局数据、作业流程数据、商品数据,可行性中：需要仓库设计专业知识,物流业务部门,1.数据采集：收集现有仓储设施数据、货物特性数据、订单数据；2.算法设计：开发基于遗传算法和模拟退火的仓储布局优化模型；3.仿真验证：通过数字孪生技术进行布局方案仿真；4.试点改造：选择1-2个仓库进行实际改造试点；5.全面推广：总结经验后推广至全国仓库网络,"企业名称：企业27（智慧医药物流园项目） +应用的技术：智能化仓储管理系统（WMS）、物流机器人（AGV）、自动化分拣线及物联网传感设备。 +投资金额：未公开 +达成的目标与效果：实现了从传统“人找货”到智能“货到人”的根本性转变。项目投入运营后，已助力仁和实现新增销售收入1亿元，利润提升约1500万元，经济效益显著。 +[已脱敏链接]" +44,,智能订单合并系统,合作开发,2027Q2-2028Q2,8,物流,订单数据标准化，合并规则建立,智能合并同一客户的多个订单，降低物流成本和提高效率,规则引擎、数据分析,小模型,订单数据、客户数据、物流数据,可行性高：合并规则相对简单,物流业务部门,1.规则梳理：分析现有订单处理规则和业务流程；2.算法开发：构建基于机器学习的订单合并优化算法；3.系统集成：与现有ERP和WMS系统对接；4.灰度发布：先对部分区域订单进行智能合并试点；5.全面上线：根据试点效果优化后全面推广应用,"医药物流AI智能调度系统：链四方 (技术提供方） +✅ 订单聚合：融合多家客户订单。 +✅ AI智能调度：利用AI算法分析区域货量密度与波峰波谷，自动规划最优路线，实现智能排班与车货匹配。将单车配送装载率从不足40% 提升至80%以上，显著降低了物流成本。 +[已脱敏链接]" +45,,物流数据可视化平台,采购现有解决方案,2027Q1-2028Q1,5,物流,物流数据整合，可视化平台开发,实时展示物流运营数据，支持管理决策和优化,数据可视化、BI分析,小模型,物流全流程数据,可行性高：数据可视化技术成熟,物流业务部门、管理层,1.数据中台建设：构建物流数据仓库和数据集市；2.可视化开发：设计物流关键指标仪表板和分析报表；3.智能分析：集成AI算法实现异常检测和趋势预测；4.用户培训：对物流管理人员进行系统使用培训；5.持续优化：根据用户反馈不断完善可视化内容和分析功能,"重庆军卫医药：通过OMS、WMS、TMS系统，实现了对药品从验收、存储、分拣到配送全过程数据的优化和可视化管控。 +[已脱敏链接]" +46,,智能物流网点选址,合作开发,2028Q1-2028Q3,11,物流,市场数据采集，选址模型建立，成本效益分析,"通过建立混合整数线性规划（MILP）模型，结合仓库/工厂/供应商点位、运输信息、采购信息，成本信息等提供仓储布局智能选址。 + +***前置仓：本地化的前置仓选址方案 +***专业仓：器械类、特殊品 +***融合仓：多品类、多形态 +***立体仓 +智能分析和推荐最优物流网点地址，提高网络覆盖效率",优化算法、地理信息系统,大模型+小模型,市场数据、地理数据、成本数据,可行性中：需要复杂的地理分析,物流业务部门、战略与证券事务部,1.数据收集：整合地理数据、客户分布、交通状况、成本数据等；2.模型构建：开发基于多因素分析的网点选址决策模型；3.仿真评估：对不同选址方案进行经济效益和服务能力仿真；4.决策支持：为管理层提供选址决策建议和可视化分析；5.实施跟踪：对新选址网点的运营效果进行持续跟踪评估,"四方麒麟基于区域货量密度、交通网络等数据，为某药企推荐最优仓库位置，配送时效提升。 +[已脱敏链接]" +47,,物流服务智能评价助手,合作开发,2026Q2-2026Q4,8,物流,服务评价指标体系建立，客户反馈数据采集,智能评价物流服务质量，持续改进服务水平,数据分析、服务评价模型,小模型,客户反馈数据、服务数据、评价指标,可行性高：评价指标相对明确,物流业务部门、客户服务部,1.评价体系构建：建立物流服务质量评价指标体系；2.数据采集：整合客户反馈、运营数据、时效数据等；3.模型训练：开发服务质量评价模型和满意度预测模型；4.系统开发：构建服务评价分析平台和改进建议系统；5.闭环管理：建立评价-分析-改进-反馈的闭环管理机制,"FreightAmigo：侧重于物流运输过程的量化监测 +该平台通过传感器和AI算法，将运输过程中的温度、冲击等关键指标数字化并实时记录。这些客观、不可篡改的数据，使得对承运方的服务质量的评价不再是主观感受，而是有了精确的数据支撑，为后续的承运商选择、绩效考核乃至保险理赔都提供了坚实依据。 +[已脱敏链接] +链四方“四方麒麟”：内嵌了行业知识与评价规则 +这个AI大模型的特点在于它深刻理解医药物流的行业法规和业务流程。它可以自动识别合规风险，并通过智能调度算法优化运输路径和车货匹配。这意味着，它将行业的“好服务”标准（如合规、高效、低成本）内化到了系统功能中，从而能够自动执行符合这些标准的决策。 +[已脱敏链接] +[已脱敏链接] +国控广东与旷视的合作：实现了操作环节的自动化质检 +这个项目展示了AI在具体物流操作节点上的评价能力。在药品收货环节，系统通过AI视觉技术，自动、快速地对药品信息进行复核，准确率高达99%以上，效率提升超50%。这实际上扮演了“自动化质检员”的角色，确保每一步操作的准确率，从而保障整体物流服务的质量。 +[已脱敏链接] +[已脱敏链接] +[已脱敏链接]" +48,,患者助理/药事服务智能问答系统,合作开发,2026Q2-2027Q2,11,零售,药品知识库建设完成，药师专业知识数据化，客户服务平台建设,提供24小时在线用药咨询服务，提升客户满意度和专业服务水平，客户咨询响应时间缩短80%,NLP、知识图谱、对话系统,大模型,药品说明书数据、药师专业知识、客户咨询数据,可行性高：知识库技术相对成熟,零售业务部门,1.知识图谱构建：建立药品知识库、疾病知识库、用药指南库；2.NLP模型训练：开发针对医药领域的自然语言处理模型；3.系统开发：构建智能问答系统和用户交互界面；4.试点应用：在重点门店和线上渠道进行试点；5.持续优化：基于用户反馈不断扩充知识库和优化回答质量,"企业名称：企业28、企业29天衍实验室及英国多家顶尖医学机构 +应用的技术：基于知识协作机制的大语言模型药物分析系统（DrugGPT），包含问诊分析、知识获取与证据生成三大协同模块，整合权威知识库构建疾病-症状-药物知识图谱。 +投资金额：未公开 +达成的目标与效果：在药物不良反应、药物-相互作用等安全关键任务上，准确率较现有最强模型提高17.3–39.8%。外部验证表明，能将基层医生药物决策准确率从83.4%提升至91.2%。 +[已脱敏链接]" +49,,虚拟导购员（数字人）,合作开发,2027Q4-2028Q2,14,零售,商品信息数据库完善，语音交互技术部署，导购知识库建设,提供智能化导购服务，帮助客户选择合适商品，销售转化率提升30%,语音识别、NLP、推荐系统,大模型,商品信息数据、客户购买数据、导购知识,可行性中：需要语音交互技术支持,零售业务部门,1.数字人设计：根据品牌定位设计虚拟导购员形象和交互风格；2.技术开发：集成语音识别、NLP、计算机视觉等技术；3.知识库构建：建立产品知识、促销信息、健康知识等内容库；4.场景部署：在门店终端、官网、APP等渠道部署；5.运营优化：根据用户交互数据不断优化数字人表现和服务能力,"企业名称：企业30 +应用的技术：基于大模型的智能运营产品，具有文本理解、问答、情感分析等能力。 +投资金额：未公开 +达成的目标与效果：数字员工“一言如玉-小玉”能够实现智能应答、运营支持等多项功能，旨在释放生产力，帮助零售药店提升运营效能，实现增收降本。 +[已脱敏链接]" +50,,店员陪练智能助手,合作开发,2027Q1-2027Q3,8,零售,店员培训体系数据化，产品知识库建设，培训平台开发,提供个性化店员培训和指导，提升店员专业水平和销售技能,NLP、知识图谱、个性化推荐,大模型,产品知识数据、销售技巧数据、店员表现数据,可行性高：培训内容相对标准化,零售业务部门、人力资源部,1.培训体系梳理：分析店员培训需求和现有培训内容；2.场景构建：开发常见销售场景和顾客问答模拟场景；3.系统开发：构建交互式培训平台和反馈评估系统；4.试点培训：选择部分门店进行试点培训；5.全面推广：根据试点效果优化后在全公司推广应用,"企业名称：企业31 +应用的技术：以大语言模型和AIAgent技术为核心的“AI陪练”，构建“学、练、考、评”四维一体模式，实现个性化学习与实时反馈。 +投资金额：未公开 +达成的目标与效果：相较于传统耗资百万的线下培训，该助手能以更低成本提供高拟真角色扮演和合规演练，帮助学员快速构筑合规防线，适用于新品上市培训、拜访情景对话等多种场景。 +[已脱敏链接]" +51,,智能货架与商品管理,合作开发,2028Q1-2028Q3,8,零售,货架传感器部署，视觉识别技术实施，商品管理系统升级,实时监控货架库存，自动补货和优化陈列，缺货率降低60%,计算机视觉、物联网、机器学习,小模型,货架数据、商品销售数据、客户行为数据,可行性中：需要硬件设备改造,零售业务部门,1.物联网部署：在货架安装RFID、摄像头等智能设备；2.数据采集：收集商品销售数据、库存数据、顾客行为数据；3.算法开发：构建货架优化算法和商品关联分析模型；4.系统集成：与ERP、POS系统对接实现数据互通；5.智能管理：实现自动补货提醒、货架热力图分析、商品陈列优化,"企业名称：企业22 +应用技术：AGV智能拣选机器人、激光导航、智能调度系统、视觉识别技术 +投资金额：未公开 +目标：实现仓储物流自动化，提升分拣效率与精准度，降低人力成本。 +降本/增效/提质：分拣速度达2500件/小时（相当于15名熟练工人同时作业），物流成本预计降低30%以上，偏远地区药品配送时效从“按周等”提升至“按小时达”。 +来源网址：[已脱敏链接]" +52,,会员画像智能分析,合作开发,2026Q2-2026Q3,11,零售,会员数据整合，数据清洗和标准化，画像分析模型建立,构建精准的会员画像，实现个性化营销和服务，会员复购率提升40%,机器学习、数据挖掘、用户画像,小模型,会员消费数据、个人信息数据、行为数据,可行性高：会员数据相对完整,零售业务部门,1.数据整合：整合会员基本信息、消费记录、互动行为等多维度数据；2.标签体系构建：建立会员标签体系和画像模型；3.算法训练：开发会员分群算法和价值评估模型；4.应用开发：构建会员画像分析平台和可视化系统；5.精准营销：基于画像实现个性化推荐和精准营销,"企业名称：企业32（合作药店） +应用技术：中康资讯CMH大数据中心、机器学习算法、会员消费行为分析 +投资金额：未公开 +目标：构建会员画像，筛选高价值客户，实现个性化营销。 +降本/增效/提质：优惠券转化率提升6.5倍，精准营销精准率达到99%。 +来源网址：[已脱敏链接]" +53,,精准营销智能系统,合作开发,2026Q3-2027Q3,11,零售,会员画像系统上线，营销活动数据历史积累，效果评估体系建立,基于会员画像实现精准营销，提高营销效果和投入产出比，营销ROI提升50%,机器学习、精准营销、A/B测试,大模型,会员画像数据、营销活动数据、效果数据,可行性高：基于现有会员系统,零售业务部门,1.用户分群：基于会员画像进行用户分群和需求分析；2.策略制定：设计差异化营销策略和内容方案；3.渠道整合：打通线上线下营销渠道；4.系统开发：构建精准营销管理平台和效果评估系统；5.闭环优化：建立营销-反馈-优化的闭环管理机制,"企业名称：企业33 +应用技术：行业数据库整合、短信/彩信/传真群发、AI算法分析目标客户群体 +投资金额：未公开 +目标：打通药企到终端的信息壁垒，提升招商与品牌推广效率。 +降本/增效/提质：整合4000+制药企业、8000+医药商业公司数据，实现跨区域精准招商，加速产品流通。 +来源网址：[已脱敏链接]" +54,,电商智能推荐系统,合作开发,2027Q1-2028Q1,11,零售,电商平台数据整合，用户行为数据采集，推荐算法开发,为电商用户提供个性化商品推荐，提高转化率和客单价，电商销售额提升60%,协同过滤、深度学习、推荐系统,小模型,用户浏览数据、购买数据、商品数据,可行性高：推荐算法相对成熟,零售业务部门,1.数据收集：收集用户浏览记录、购买历史、商品属性等数据；2.算法开发：构建协同过滤、深度学习等推荐算法；3.系统实现：开发智能推荐引擎和前端展示界面；4.灰度测试：进行A/B测试优化推荐效果；5.个性化服务：实现千人千面的个性化推荐服务,"企业名称：企业34（服务某医药国企） +应用技术：机器学习算法、用户行为分析、场景化推荐模型 +投资金额：未公开 +目标：提升电商平台用户转化率，优化供需匹配。 +降本/增效/提质：订单处理效率提高30%，库存积压率降低20%；个性化推荐使相关商品销量提升20%以上。 +来源网址：[已脱敏链接] + +企业名称：企业35 +应用技术：京医千询医疗大模型、用户行为分析、三维一体知识库 +目标：提升用户转化率，优化供需匹配。 +降本/增效/提质：“AI营养师”覆盖200多个保健类目，累计服务超1000万家庭，用户转化率达45%以上；针对母婴场景，可提供分阶段科学喂养方案及一站式商品推荐。 +来源网址：[已脱敏链接] +[已脱敏链接]" +55,,智能客服（零售）,合作开发,2026Q2-2026Q4,11,零售,客户服务知识库建设，对话系统开发，多渠道接入,提供24小时在线客户服务，处理常见问题，客户服务效率提升70%,对话系统、NLP、意图识别,大模型,客户服务知识库、历史对话数据,可行性高：客服机器人技术成熟,零售业务部门、客户服务部,1.知识库构建：建立药品知识、促销信息、常见问题等知识库；2.NLP模型训练：开发医药领域专用的自然语言处理模型；3.系统开发：构建智能客服平台和多渠道接入系统；4.人机协作：设计人工坐席与AI协同工作机制；5.持续优化：基于用户反馈不断提升服务质量,"企业名称：企业35 +应用技术：京医千询医疗大模型、RAG（检索增强生成）、多模态交互 +目标：提升客服响应效率，缓解药师压力。 +降本/增效/提质：AI客服可承载高并发咨询，支持7×24小时服务；结合数字人技术，提供情感化陪伴式咨询，显著提升用户体验。 +来源网址：[已脱敏链接] +[已脱敏链接]" +56,,店铺运营智能分析,合作开发,2026Q4-2027Q1,8,零售,店铺运营数据整合，分析指标体系建立，数据可视化平台,深度分析店铺运营数据，提供优化建议，店铺盈利能力提升20%,数据分析、BI分析、机器学习,大模型+小模型,店铺销售数据、成本数据、客流数据,可行性高：店铺数据相对完整,零售业务部门,1.数据采集：整合销售数据、库存数据、客流量数据、营销数据等；2.指标体系构建：建立店铺运营关键指标体系；3.分析模型开发：构建销售预测、库存优化、人员配置等分析模型；4.可视化平台：开发店铺运营分析仪表板；5.决策支持：为店长提供数据驱动的决策建议,"企业名称：企业36（沪渝人工智能研究院） +应用技术：兆言大模型、基层医疗数据整合、智能补货算法 +投资金额：未公开 +目标：优化基层药房运营，提升药品周转效率与服务能力。 +降本/增效/提质：药品周转率提升40%，库存周期缩短30%，过期损耗率降低25%；已在2000多家药房落地应用。 +来源网址：[已脱敏链接]" +57,,商品陈列智能优化,合作开发,2028Q1-2028Q3,8,零售,商品销售数据完整，客户行为数据采集，陈列优化算法开发,智能优化商品陈列布局，提高销售转化率和客户体验,机器学习、优化算法、数据分析,小模型,商品销售数据、客户行为数据、陈列数据,可行性中：需要客户行为数据采集,零售业务部门,1.数据收集：收集商品特性、销售数据、顾客行为、空间布局等数据；2.算法开发：构建商品陈列优化算法和热力图分析模型；3.仿真验证：通过虚拟店铺模型进行陈列方案仿真；4.试点应用：在部分门店进行陈列优化试点；5.效果评估：分析试点效果并全面推广,"企业名称：企业37（服务日药本舖） +应用技术：3D建模、AI影像辨识系统、Beacon微定位技术 +投资金额：未公开 +目标：动态调整货架陈列，提升高毛利商品曝光率，减少人工操作。 +降本/增效/提质：自动更新货架标签，降低店员劳务成本；结合POS系统实时优化陈列，促进高毛利商品销售。 +来源网址：[已脱敏链接]" +58,,药品库存智能管理,合作开发,2026Q2-2026Q4,8,零售,店铺库存数据实时同步，销售预测模型建立,智能管理店铺药品库存，自动生成补货决策建议。减少积压和缺货，库存周转率提升30%,机器学习、需求预测,小模型,店铺库存数据、销售数据、季节性数据,可行性高：库存数据相对完整,零售业务部门,1.数据整合：对接POS系统、ERP系统、供应链系统数据；2.算法设计：开发库存预测模型和补货优化算法；3.系统开发：构建智能库存管理平台和预警系统；4.试点验证：选择部分商品品类进行试点应用；5.全面推广：优化完善后推广至全品类管理,"企业名称：企业22 +应用技术：自动化立体仓库、智能调度算法、温湿度传感器 +投资金额：未公开 +目标：实现药品库存实时监控，降低缺货与积压风险。 +降本/增效/提质：库存误差率仅为十万分之一，冷链药品全程温度可追溯，物流成本降低30%以上。 +来源网址：[已脱敏链接]" +59,,客户流失智能预警,合作开发,2026Q3-2026Q4,11,零售,客户行为数据采集，流失预测模型建立,提前识别潜在流失客户，实施针对性留存措施，客户留存率提升25%,机器学习、流失预测模型,小模型,客户消费数据、行为数据、交互数据,可行性高：流失预测模型相对成熟,零售业务部门,1.特征工程：构建客户流失预警特征体系；2.模型训练：开发客户流失预测模型和风险评估算法；3.系统实现：构建客户流失预警平台和干预管理系统；4.策略制定：设计客户挽留策略和个性化方案；5.效果跟踪：对挽留效果进行持续跟踪和优化,"鱼汛AI销冠系统（服务商：鱼塘软件） +✅ AI客户分析：深度挖掘客户数据，精准锁定高价值客户。 +✅ 销售沟通全流程管控：实时记录分析和留存沟通轨迹，违规行为即时预警。 +系统能帮助销售有针对性地跟进客户，提升转化。其防飞单功能使一家中型药业公司的月度飞单率从15%降至1%以下，间接保护了客户资源，季度业绩同比增长12%。 +[已脱敏链接]" +60,,店铺选址智能分析,合作开发,2028Q2-2028Q3,11,零售,市场数据采集，人口数据整合，选址模型建立,智能分析和推荐最优店铺地址，提高店铺成功率和盈利能力,机器学习、地理信息系统,小模型,人口数据、竞争对手数据、地理数据,可行性中：需要外部数据整合,零售业务部门、战略与证券事务部,1.数据收集：整合人口数据、消费数据、竞争数据、交通数据等；2.模型构建：开发门店选址评估模型和收益预测算法；3.可视化分析：构建选址决策支持系统和可视化平台；4.方案评估：对不同选址方案进行综合评估和比较；5.实施跟踪：对新开门店的运营效果进行持续跟踪,"企业名称：企业38（数说故事Datastory） +应用技术：地理信息系统（GIS）、AI选址模型、“人-货-场”大数据分析 +投资金额：未公开 +目标：优化门店布局，提升新开门店成功率。 +降本/增效/提质：通过智能算法识别潜力网点，支持全国2800+区县的“人-货-场”精准匹配，已服务医药零售等行业。 +来源网址：[已脱敏链接]" +61,,营销内容创作智能系统,合作开发,2026Q2-2027Q2,11,零售,营销内容模板库建设，创作工具部署，品牌规范数据化,自动生成营销文案、海报等内容，提高创作效率和质量,NLP、图像生成、模板引擎,大模型,营销材料数据、品牌规范、历史内容,可行性高：内容生成技术相对成熟,零售业务部门、市场部,1.内容体系梳理：建立营销内容分类体系和创作规范；2.模型训练：开发基于NLP的内容生成模型和优化算法；3.系统开发：构建智能内容创作平台和管理系统；4.多渠道适配：实现内容的多渠道自动适配和发布；5.效果分析：对内容效果进行数据分析和优化迭代,"企业名称：企业39 +应用技术：ChatGPT、医疗领域知识库 +投资金额：未公开 +目标：提升医疗营销内容创作效率，解决用语重复问题。 +降本/增效/提质：每月节省54小时工时，年度ROI达428.6%；营销人员可专注于策略性工作，内容创意性显著提升。 +来源网址：[已脱敏链接]" +62,,药品舆情智能监测,合作开发,2026Q2-2026Q4,11,零售,舆情数据源整合，舆情分析模型建立，预警机制完善,实时监测药品相关舆情，及时发现市场机会和风险,NLP、情感分析、网络爬虫,大模型,社交媒体数据、新闻数据、论坛数据,可行性高：舆情监测技术相对成熟,零售业务部门、市场部,1.数据源整合：对接社交媒体、新闻媒体、电商平台等多渠道数据源；2.NLP模型开发：构建医药领域舆情分析和情感识别模型；3.监测系统：开发药品舆情实时监测平台和预警系统；4.分析报告：自动生成舆情分析报告和应对建议；5.危机管理：建立舆情危机响应机制和处理流程,"企业名称：企业40 +应用技术：分布式数据采集、自然语言处理、AIGC自动生成报告 +投资金额：未公开 +目标：实现药品网络舆情全域监测，提升监管效能。 +降本/增效/提质：覆盖B2C、B2B、O2O、短视频等多平台数据，违规线索处置效率提升30%以上；AI生成报告准确率达92%，减少人工分析工作量。 +来源网址：[已脱敏链接]" +63,,智能价格策略系统,合作开发,2028Q1-2028Q4,11,零售,竞争对手价格数据采集，价格弹性分析模型建立,智能制定商品定价策略，优化价格竞争力和利润空间,机器学习、价格优化模型,小模型,竞争对手价格数据、销售数据、成本数据,可行性中：需要竞争对手数据,零售业务部门,1.数据收集：整合成本数据、竞品价格、销售数据、促销效果等；2.算法开发：构建动态定价模型和价格弹性分析算法；3.策略引擎：开发价格策略管理引擎和规则配置系统；4.系统集成：与ERP、POS系统对接实现价格自动调整；5.效果评估：建立价格策略效果评估体系和优化机制,"企业名称：企业34（服务某医药国企） +应用技术：机器学习算法、市场价格波动分析 +投资金额：未公开 +目标：优化药品定价策略，提升市场竞争力。 +降本/增效/提质：订单处理效率提高30%，库存积压率降低20%；个性化推荐使相关商品销量提升20%以上。 +来源网址：[已脱敏链接]" +64,,客户健康管理智能系统,合作开发,2027Q3-2028Q3,14,零售,客户健康数据采集权限获取，健康管理知识库建设,提供个性化健康管理和用药指导服务，提供慢病风险预测，提升客户粘性和满意度,机器学习、健康管理系统,大模型,客户健康数据、用药数据、健康知识库,可行性中：需要健康数据权限和隐私保护,零售业务部门、医疗器械中心,1.健康数据整合：收集客户健康档案、用药记录、生活习惯等数据；2.模型构建：开发健康风险评估模型和个性化健康建议算法；3.系统开发：构建客户健康管理平台和移动应用；4.服务设计：设计健康干预方案和个性化服务流程；5.运营体系：建立健康管理服务运营和评估体系,"企业名称：企业35 +应用技术：医疗大模型、用户健康档案分析、个性化干预方案 +目标：提供全生命周期健康管理服务，增强用户粘性。 +降本/增效/提质：整合体检、慢性病管理、营养咨询等模块，形成闭环服务；AI心理陪伴师“聊愈小宇宙”通过垂类大模型提供情感支持，推动心理健康服务规范化。 +来源网址：[已脱敏链接] +[已脱敏链接]" +65,,智能销售预测系统（零售）,合作开发,2027Q2-2028Q2,11,零售,历史销售数据完整，外部影响因子数据采集,精准预测商品销售趋势，优化库存和采购计划,时间序列分析、机器学习,小模型,历史销售数据、季节性数据、市场数据,可行性高：销售数据相对完整,零售业务部门,1.数据准备：整合历史销售数据、促销数据、季节性因素、市场趋势等；2.模型训练：开发时间序列预测模型和机器学习预测算法；3.系统实现：构建销售预测平台和可视化分析系统；4.库存联动：与库存管理系统对接实现智能补货；5.动态调整：建立预测模型动态优化机制,"企业名称：企业35 +应用技术：大数据分析、销售趋势建模、动态库存优化 +目标：提升库存周转率，降低缺货风险。 +降本/增效/提质：通过实时监控销售数据，优化备货策略；在抗疫药品保供中，实现一亿盒药品储备的精准调度，保障“不断供、不涨价”。 +来源网址：[已脱敏链接] +[已脱敏链接]" +66,,店铺效率智能分析,合作开发,2027Q2-2027Q3,8,零售,店铺运营数据标准化，效率评估指标体系建立,全面分析店铺运营效率，识别改进机会和优化方向,数据分析、效率评估模型,小模型,店铺运营数据、成本数据、效率指标,可行性高：效率指标相对明确,零售业务部门,1.指标体系构建：建立店铺效率评估指标体系；2.数据采集：整合销售数据、客流量、人效、坪效等多维度数据；3.分析模型：开发效率分析模型和优化建议算法；4.可视化平台：构建店铺效率分析仪表板；5.改进机制：建立效率改进跟踪和评估机制,"企业名称：企业41 +应用技术：视频点检平台、BI系统、智能排班算法 +投资金额：未公开 +目标：优化门店运营效率，降低巡检成本。 +降本/增效/提质：门店巡检成本降低52%，人效提升33%；通过热力图分析识别30%无效停留顾客，动态调整陈列布局。 +来源网址：http://m.163.com/dy/article/KBUCH6VG05568W0A.html" +67,,智能促销活动系统,合作开发,2027Q2-2028Q2,11,零售,促销活动数据历史积累，效果评估模型建立,智能设计和执行促销活动，提高活动效果和投入产出比,机器学习、促销优化模型,大模型+小模型,促销活动数据、销售数据、成本数据,可行性高：促销数据相对完整,零售业务部门,1.需求分析：分析促销活动目标和关键指标；2.策略引擎：开发促销策略生成引擎和规则配置系统；3.效果预测：构建促销效果预测模型和ROI分析算法；4.执行管理：开发促销活动管理平台和执行监控系统；5.评估优化：建立促销效果评估和持续优化机制,"企业名称：企业42 +应用技术：AI智能投流、场景化短视频生成 +投资金额：未公开 +目标：提升促销活动转化率，拓展新客群。 +降本/增效/提质：抖音渠道新客占比65%，带动O2O平台销量提升22%，电商平台销量提升71%；活动期间品牌曝光量增长200%。 +来源网址：http://m.163.com/news/article/KBUCH6VG05568W0A.html" +68,,客户满意度智能分析,合作开发,2027Q1-2027Q2,8,零售,客户反馈数据采集，满意度评估模型建立,智能分析客户满意度，及时发现和解决服务问题,情感分析、NLP、数据分析,大模型,客户反馈数据、评价数据、服务数据,可行性高：满意度分析技术成熟,零售业务部门、客户服务部,1.评价体系构建：建立客户满意度评价指标体系；2.数据采集：整合客户反馈、NPS评分、投诉数据、交易数据等；3.分析模型：开发满意度分析模型和影响因素识别算法；4.可视化平台：构建客户满意度分析仪表板；5.改进机制：建立满意度改进跟踪和闭环管理,"企业名称：企业43 +应用技术：AI大模型、智能客服系统 +投资金额：未公开 +目标：提升客服响应效率，增强用户体验。 +降本/增效/提质：人机协同处理咨询，客服响应时间缩短至20-90秒；客户满意度调查中“服务专业性”评分提升15%。 +来源网址：http://m.163.com/dy/article/KBUCH6VG05568W0A.html" +69,,智能补货提醒系统,合作开发,2027Q1-2028Q1,5,零售,库存数据实时同步，补货规则数据化,自动监控库存水平，智能提醒补货，减少缺货情况,规则引擎、自动化提醒,小模型,库存数据、销售数据、补货规则,可行性高：补货逻辑相对简单,零售业务部门,1.数据整合：对接销售数据、库存数据、供应链数据；2.算法开发：构建智能补货预测模型和库存优化算法；3.提醒系统：开发补货提醒引擎和任务管理系统；4.系统集成：与WMS、ERP系统对接实现数据互通；5.效果评估：建立补货准确率和库存周转率评估体系,"企业名称：企业44（服务某连锁药店） +应用技术：动态库存预警、智能补货算法 +投资金额：未公开 +目标：降低库存积压与缺货风险。 +降本/增效/提质：库存周转率提升35%，滞销品占比从30%降至15%；药品过期损耗率降低25%，库存周期缩短30%。 +来源网址：[已脱敏链接]" +70,,DTP药房用药指导助手,合作开发,2026Q2-2026Q4,11,零售,完成DTP药房现有用药数据梳理与整合，确定合作定制方并签订合作协议，组建包含临床药师、AI技术人员的项目团队。,提升DTP药房专业服务能力，增强患者用药依从性与满意度，减少用药风险，吸引更多患者选择，进而促进药房药品销售增长。,NLP、知识图谱构建、个性化推荐算法,大模型,需收集DTP药房现有患者基本信息、用药历史记录、药品说明书、临床用药指南、药物相互作用数据等。数据来源包括DTP药房内部数据库、合作医疗机构的共享病例资料、权威医药数据库（如药智网、PubMed等）以及公开的临床研究文献。,可行性高：数据层面，DTP药房已有内部数据积累，且可通过合作医疗机构及权威医药数据库补充所需信息，数据来源明确；技术层面，NLP、知识图谱构建等相关AI技术已较为成熟，合作定制方式可借助外部技术力量保障实现；业务层面，目标用户对专业用药指导需求迫切，相关业务板块为零售，项目收益能直接促进药房销售增长，符合业务发展方向；团队组建条件清晰，包含临床药师和AI技术人员的团队可确保项目专业落地。综合来看，项目在数据、技术、业务及团队等关键要素上均具备实施基础。,零售业务部门,1.知识库构建：建立DTP药房专业知识库和用药指导规范；2.NLP模型训练：开发医药专业问答模型和处方解析算法；3.系统开发：构建用药指导助手和患者管理平台；4.服务流程：设计AI辅助的用药指导服务流程；5.效果评估：建立用药指导效果评估和患者满意度调查机制,"企业名称：企业45 +应用技术：AI大模型、医药知识库、医保政策解析系统 +投资金额：未公开 +目标：提升DTP药师服务效率，优化患者用药体验。 +降本/增效/提质：药师回答医保政策问题效率提升80%，患者咨询等待时间缩短至5分钟内；覆盖15个城市，患者满意度达92%。 +来源网址：http://m.163.com/dy/article/KBEE16R30534Q32Z.html" +71,,订单录入流程自动化,采购现有解决方案,2027Q1-2028Q1,5,零售,完成零售订单系统数据接口对接，获取历史订单样本数据5000条以上，确定合作定制开发的技术服务商并签订合同。,自动核对订单编码与货品、数量信息，自动录入ERP系统,NLP、OCR、机器学习模型训练与优化,大模型+小模型,"历史订单样本数据（5000条以上），零售订单系统数据接口对接获取的订单相关数据（含订单编码、货品、数量等信息） +",可行性高：技术层面，项目涉及的NLP、OCR及机器学习模型训练与优化等AI技术已相对成熟，具备实施基础；数据层面，通过与零售订单系统数据接口对接可获取5000条以上历史订单样本数据，满足数据需求；合作定制开发的实施方式，能借助技术服务商的专业能力保障项目推进。整体来看，在完成数据接口对接、获取足够样本数据并确定技术服务商后，项目具备较高可行性。,零售业务部门,1.流程梳理：分析现有订单录入流程和痛点；2.OCR识别：开发订单信息自动识别和提取模型；3.RPA开发：构建机器人流程自动化解决方案；4.系统集成：与ERP系统对接实现数据自动录入；5.质量控制：建立订单信息验证机制和异常处理流程,"企业名称：企业34（服务某连锁药店） +应用技术：RPA机器人、OCR识别、结构化数据提取 +投资金额：未公开 +目标：减少人工录入错误，提升订单处理效率。 +降本/增效/提质：采购订单处理时间从2天缩短至3小时，数据准确率从85%提升至99.7%；人工处理成本降低60%，年节省约120万元。 +来源网址：[已脱敏链接]" +72,,智能退货管理系统,合作开发,2027Q2-2028Q2,8,零售,退货流程标准化，退货原因分类体系建立,智能处理客户退货申请，提高处理效率和客户满意度,流程自动化、规则引擎,小模型,退货申请数据、退货原因数据,可行性高：退货流程相对标准,零售业务部门、客户服务部,1.规则引擎：构建退货规则库和处理流程；2.智能审核：开发退货原因分析和自动审核模型；3.系统开发：构建智能退货管理平台；4.集成对接：与ERP、WMS系统对接实现数据互通；5.优化机制：建立退货数据分析和流程优化机制,"企业名称：企业11 +应用技术：AI图像识别、退货原因分析模型、自动审批系统 +投资金额：未公开 +目标：优化退货流程，降低人为干预成本。 +降本/增效/提质：退货审核效率提升40%，错误率从15%降至3%；通过智能分类滞销药品，库存周转率提升25%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +73,,智能财务票据处理系统,采购现有解决方案,2027Q2-2028Q2,8,运营管理,票据电子化程度达90%，OCR技术成熟，财务流程标准化,CV大模型实现发票验真、税额计算、凭证生成全流程自动化，提高财务处理效率，人工成本降低60%,OCR、RPA、机器学习,小模型,票据图像数据、财务规则数据,可行性高：OCR技术相对成熟,财务管理部,1.OCR识别：开发财务票据识别和信息提取模型；2.NLP处理：构建票据内容理解和分类算法；3.规则引擎：建立票据审核规则和异常检测机制；4.系统开发：构建智能票据处理平台；5.集成应用：与财务系统对接实现自动化处理,"企业名称：企业46（服务某连锁药店） +应用技术：OCR识别、智能校验规则、电子发票全流程管理 +投资金额：未公开 +目标：提升发票处理效率，降低税务风险。 +降本/增效/提质：单张发票处理时间从5分钟缩短至30秒，作废率从12%降至0.3%；年节省打印成本超12万元，税务稽查风险降低90%。 +来源网址：[已脱敏链接]" +74,,合同风险智能审核,采购现有解决方案,2026Q4-2027Q2,8,运营管理,合同数据电子化，法务知识库建设，风险评估模型建立,自动识别合同条款风险，提供风险评估和建议，降低法务风险,NLP、知识图谱、风险评估模型,大模型,合同数据、法务条款库、风险案例数据,可行性高：合同条款相对结构化,法务部门、审计内控部,1.知识库构建：建立合同风险知识库和条款库；2.NLP模型：开发合同文本分析和风险识别算法；3.规则引擎：构建风险评估规则和预警机制；4.系统开发：构建合同智能审核平台；5.流程优化：设计人机协同的合同审核流程,"企业名称：企业1（服务某医药国企） +应用技术：NLP文本分析、GSP合规规则库、智能预警系统 +投资金额：未公开 +目标：降低合同条款缺陷率，提升合规性。 +降本/增效/提质：合同审核效率提升50%，GSP合规缺陷率从38%降至0；通过智能校验冷链运输条款，减少药品损耗超200万元/年。 +来源网址：[已脱敏链接]" +75,,智能报表生成系统（ChatBI）,采购现有解决方案,2027Q1-2028Q1,8,运营管理,数据仓库建设完成，报表模板标准化，BI平台部署,自动生成各类管理报表，提高报表生成效率和准确性,BI分析、数据可视化、自动化,小模型,业务数据、财务数据、报表模板,可行性高：报表生成技术成熟,财务管理部、各业务部门,1.数据模型：构建企业数据模型和语义理解体系；2.NLP开发：开发自然语言查询和数据理解模型；3.可视化引擎：构建动态报表生成和可视化展示系统；4.系统集成：与数据仓库和业务系统对接；5.用户培训：提供自然语言查询使用培训,"企业名称：企业44（服务某连锁药店） +应用技术：大语言模型、自然语言查询、可视化分析 +投资金额：未公开 +目标：降低数据分析门槛，提升决策效率。 +降本/增效/提质：业务人员自主取数效率提升80%，报表生成时间从2小时缩短至10分钟；区域经理决策效率提升65%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +76,,智能招聘助手,合作开发,2027Q2-2028Q2,8,运营管理,人事数据整合，HR系统升级，智能化模块开发,参考目前公司内部类似岗位员工资料，自动生成对应招聘岗位JD,机器学习、NLP、数据分析,大模型+小模型,员工数据、绩效数据、招聘数据,可行性高：HR数据相对完整,人力资源部,1.需求分析：构建岗位需求模型和人才画像；2.筛选算法：开发简历自动筛选和匹配算法；3.面试辅助：构建智能面试问题生成和评估系统；4.系统开发：构建智能招聘管理平台；5.效果评估：建立招聘效果分析和优化机制,"企业名称：企业41 +应用技术：简历解析、智能匹配算法、面试调度系统 +投资金额：未公开 +目标：提升招聘效率，精准筛选人才。 +降本/增效/提质：简历处理效率提升3倍，面试周期从7天缩短至3天；通过AI分析候选人行为数据，新员工留存率提升15%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +77,,穿透式智能审计助手,采购现有解决方案,2027Q2-2027Q4,11,运营管理,审计数据整合，审计规则数据化，异常检测模型建立；构建企业全量业务-财务映射关系,自动识别账实不符、科目错配等深层问题，自动化审计流程，智能发现异常和风险，审计效率提升70%,数据挖掘、异常检测、机器学习,小模型,财务数据、业务数据、审计规则,可行性中：需要复杂的异常检测算法,审计内控部,1.风险模型：构建审计风险模型和异常检测指标；2.数据分析：开发穿透式数据分析和关联挖掘算法；3.可视化平台：构建审计分析仪表板和证据管理系统；4.流程设计：设计智能审计工作流程；5.结果应用：建立审计发现整改跟踪机制,"企业名称：企业6 +应用技术：区块链、AI异常检测、全流程追溯系统 +投资金额：未公开 +目标：提升审计效率，防范财务风险。 +降本/增效/提质：审计数据核查时间缩短60%，异常交易识别准确率达98%；通过智能监控冷链运输数据，减少药品质量风险事件超50%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +78,,智能决策支持助手（批发+零售）,合作开发,2027Q4-2028Q2,14,运营管理,数据仓库完善，决策模型建立，管理驾驶舱建设,为管理层提供智能化决策支持，提高决策质量和效率,机器学习、数据分析、决策模型,小模型,全业务数据、市场数据、外部数据,可行性中：需要复杂的决策模型,战略与证券事务部、管理层,1.决策模型：构建业务决策模型和指标体系；2.数据整合：整合各业务系统数据和外部市场数据；3.分析引擎：开发多维度分析和预测算法；4.可视化平台：构建决策支持仪表板和情景分析系统；5.应用推广：建立决策支持应用场景和使用规范,"企业名称：企业44（服务某医药流通企业） +应用技术：机器学习预测模型、动态库存优化算法 +投资金额：未公开 +目标：优化库存结构，提升供应链响应速度。 +降本/增效/提质：缺货率下降47%，库存周转率提升35%；通过智能预测促销需求，销售额增长22%。 +来源网址：[已脱敏链接] +[已脱敏链接]" +79,,综合风险管理平台,采购现有解决方案,2027Q4-2028Q4,14,运营管理,风险数据整合，风险评估模型建立，预警机制完善,全面监控和管理企业风险，提前预警和应对,风险评估模型、机器学习,小模型,业务风险数据、财务风险数据、外部风险数据,可行性中：需要全面的风险数据整合,审计内控部、风险管理部,1.风险地图：构建企业风险地图和评估体系；2.监测模型：开发风险监测指标和预警算法；3.分析引擎：构建风险分析和影响评估系统；4.可视化平台：开发风险管理仪表板和报告系统；5.应对机制：建立风险应对策略库和处理流程,"企业名称：企业47（服务某跨国药企） +应用技术：AI风险评估模型、实时监控系统、合规流程自动化 +投资金额：未公开 +目标：提升风险管理能力，降低合规成本。 +降本/增效/提质：风险事件响应时间缩短70%，合规成本降低30%；通过智能预警系统，减少药品召回损失超500万元/年。 +来源网址：[已脱敏链接]" +80,,智能成本收益分析,合作开发,2026Q3-2026Q4,8,运营管理,成本数据标准化，成本分析模型建立,智能分析和控制成本，评估项目收益，优化成本结构，预计每年降本500万元,数据分析、成本建模,小模型,成本数据、业务数据、预算数据,可行性高：成本数据相对完整,财务管理部、各业务部门,1.成本模型：构建成本结构模型和收益分析框架；2.数据整合：收集财务数据、运营数据、市场数据；3.算法开发：开发成本分析和收益预测算法；4.可视化平台：构建成本收益分析仪表板；5.决策支持：提供成本优化建议和投资决策支持,"企业名称：企业39 +应用技术：成本预测模型、收益优化算法、动态定价系统 +投资金额：未公开 +目标：优化定价策略，提升盈利能力。 +降本/增效/提质：采购成本降低18%，利润率提升5个百分点；通过智能分析促销活动ROI，营销费用利用率提高40%。 +来源网址：[已脱敏链接]" +81,,立项智能法务助手,合作开发,2026Q3-2027Q1,8,运营管理,完成法务数据接口对接、获取运营管理部合同样本及相关案例数据、确定合作定制开发厂商,项目初筛阶段解析合同条款（股权结构、业绩承诺、违约责任），提示潜在法律风险（如“股权质押未披露”“业绩承诺无法兑现风险”），提供行业法律法规速查与类似并购案例参考,NLP（合同条款解析、法律风险识别）、知识图谱（行业法律法规速查、类似并购案例参考）,大模型,合同样本、历史并购案例数据；法务部门的法律法规数据库及相关法律文书；通过合作定制开发厂商对接的外部行业法律案例库和法规更新数据源。,可行性高：技术层面，NLP技术可实现合同条款解析与法律风险识别，知识图谱技术能支撑法律法规速查及案例参考，相关技术成熟度较高。数据层面，已明确合同样本、历史案例、法务部门数据库及外部行业案例库等数据来源，可满足项目数据需求。实施方式采用合作定制，能借助厂商专业能力加速开发。目标用户运营管理部存在实际业务需求，项目收益显著，可在初筛阶段有效辅助合同审查，提示风险并提供参考。,运营管理部,1.知识库构建：建立立项法规库和风险案例库；2.NLP模型：开发立项文档分析和合规性检查算法；3.智能审查：构建立项材料自动审查和风险提示系统；4.流程设计：设计智能法务审查工作流程；5.效果评估：建立审查效率和质量评估机制,"企业名称：企业48（服务某医药流通企业） +应用技术：NLP文本分析、法律法规知识图谱、电子签章直连技术 +投资金额：未公开 +目标：提升合同审核效率，降低合规风险。 +降本/增效/提质：合同审核周期从5天缩短至1天，条款缺陷率从38%降至0；新增粤港澳大湾区政策库后，区域合规性响应速度提升70%。 +来源网址：[已脱敏链接]" +82,,招标投标智能生成系统,合作开发,2026Q2-2027Q2,8,运营管理,完成招标需求文档梳理、获取历史投标数据及关联企业信息库访问权限、确定合作定制开发厂商并签订合同,自动生成不同类别标书，识别投标方关联关系提示围标风险,自然语言处理（NLP）、信息抽取、文本生成、知识图谱（用于关联企业信息识别）、风险识别算法,大模型,数据需求包括：招标需求文档结构化数据、历史投标文档全文数据、企业工商注册信息、企业股权关系数据、企业关联交易数据、相似项目招标文件模板数据、投标风险案例数据。数据来源为：公司内部招标管理系统、历史投标档案库、第三方企业信息查询平台（如天眼查、企查查）、行业公开招标信息网站、合作定制开发厂商提供的相关案例数据库。,可行性高：技术层面，所涉及的自然语言处理、信息抽取、知识图谱等AI技术已相对成熟，且有合作定制开发厂商支持，能保障技术实现；数据层面，明确了招标需求文档结构化数据、历史投标文档等多类数据需求，来源涵盖公司内部系统、第三方平台及厂商案例库，数据获取渠道稳定；实施条件上，项目启动条件清晰，完成招标需求文档梳理等前期工作即可推进，实施方式为合作定制，可借助厂商经验加速落地。,各业务部门、法务部门,1.模板体系：构建招标投标模板库和条款库；2.智能生成：开发招标文件自动生成和优化算法；3.合规检查：建立招标内容合规性审查机制；4.系统开发：构建招标投标智能管理平台；5.流程优化：设计全流程电子化招标管理流程,"企业名称：企业1（服务某医药流通企业） +应用技术：NLP招标文件解析、知识图谱库、合规性检查引擎 +投资金额：未公开 +目标：提升投标文件制作效率，降低废标率。 +降本/增效/提质：标书制作周期从7天缩短至3天，废标率从18%降至2%；技术参数响应准确率从72%提升至96%。 +来源网址：[已脱敏链接]" +83,,智能续约管理系统,合作开发,2027Q1-2028Q1,5,运营管理,合同数据整合，续约规则数据化，预警机制建立,智能监控合同到期情况，提前提醒续约，避免合同断档,规则引擎、自动化提醒,小模型,合同数据、续约规则、历史数据,可行性高：续约规则相对明确,法务部门、各业务部门,1.合同管理：构建合同全生命周期管理体系；2.预警系统：开发合同到期预警和风险评估模型；3.智能分析：构建续约价值评估和条款优化算法；4.系统开发：构建智能续约管理平台；5.流程设计：设计续约审批和执行管理流程,"企业名称：企业49（服务某连锁药店） +应用技术：合同条款智能提取、自动续约规则引擎、电子合同签署 +投资金额：未公开 +目标：优化供应商续约流程，降低人工干预成本。 +降本/增效/提质：续约审批效率提升60%，合同遗漏率从15%降至3%；通过智能预警系统，关键条款遗忘率下降80%。 +来源网址：[已脱敏链接]" +84,,税务管理小助手,合作开发,2026Q1-2026Q3,5,运营管理,税务数据整合，税务政策知识库建设,结合税法知识库与历史稽查案例，推荐区域性税收优惠政策适用方案，避免人为误判导致的合规风险,RPA、税务计算、政策解读,大模型,税务数据、政策数据、业务数据,可行性高：税务规则相对明确,财务管理部,1.税务知识库：建立税收法规库和政策解读库；2.智能分析：开发税务风险识别和筹划建议算法；3.申报辅助：构建税务申报自动填写和审核系统；4.系统开发：构建税务管理小助手平台；5.培训支持：提供税务知识培训和咨询服务,"企业名称：企业11 +应用技术：OCR发票识别、税务规则引擎、智能风险预警 +投资金额：未公开 +目标：提升税务处理效率，降低稽查风险。 +降本/增效/提质：单张发票处理时间从5分钟缩短至30秒，税务合规风险事件减少50%；通过智能分析集采业务税收优惠，年节省税费超200万元。 +来源网址：[已脱敏链接]" +85,,智能绩效评估系统,合作开发,2027Q1-2028Q1,8,运营管理,绩效数据整合，评估指标体系建立,智能化员工绩效评估，提供客观公正的评估结果,数据分析、绩效评估模型,小模型,员工绩效数据、业务数据、评估标准,可行性高：绩效数据相对完整,人力资源部,1.KPI体系：构建绩效评估指标体系和权重模型；2.数据整合：收集员工绩效数据和业务数据；3.算法开发：开发绩效评估和预测分析模型；4.系统开发：构建智能绩效评估平台；5.反馈机制：建立绩效反馈和改进跟踪系统,"企业名称：企业50（服务某连锁药房） +应用技术：多维度指标分析、动态目标分解、智能评分模型 +投资金额：未公开 +目标：优化绩效考核体系，提升销售动力。 +降本/增效/提质：营业员全品类销售任务完成率提升40%，顾客投诉率下降52%；人效提升33%，库存周转率提高25%。 +来源网址：[已脱敏链接]-soft.cn/info/2025101135976.html" +86,,员工绩效智能助理,合作开发,2027Q1-2028Q1,8,运营管理,完成员工绩效相关数据接口对接，确保销售业绩、项目完成率、服务满意度等数据可实时获取；2.组建包含AI技术人员、人力资源专家、业务部门代表的项目团队；3.明确绩效评估指标体系及改进建议生成规则；4.获得公司管理层对项目资源支持的审批。,基于员工绩效数据（销售业绩、项目完成率、服务满意度），提供实时反馈（如“本月销售业绩未达标，建议重点跟进XX客户”）与改进建议，支持绩效面谈话术生成（如“如何沟通绩效短板”）,自然语言处理（NLP）、数据挖掘、机器学习模型（如回归分析、分类算法）、知识图谱,大模型+小模型,数据需求包括员工基本信息、销售业绩数据（如销售额、销售增长率、销售目标达成率）、项目完成率（如项目按时交付率、项目质量评分）、服务满意度数据（如客户满意度评分、服务投诉记录）；数据来源为公司CRM系统、项目管理平台、人力资源管理系统、客户反馈收集平台及业务部门定期上报的数据报表。,可行性高：从数据基础看，所需员工绩效相关数据（销售业绩、项目完成率等）明确且可从现有CRM、项目管理等系统获取，数据接口对接条件成熟。技术层面，自然语言处理、数据挖掘及机器学习模型等主流AI技术已具备成熟应用案例，合作定制模式可依托专业技术团队实现功能落地。业务价值显著，能为人力资源及业务部门提供实时绩效反馈与改进建议，提升绩效管理效率和面谈质量，符合公司运营管理优化需求。项目启动条件清晰，团队组建、指标体系及管理层审批等要求可通过常规项目推进流程达成，整体实施风险可控。,人力资源部,1.目标管理：构建绩效目标设定和跟踪体系；2.智能分析：开发绩效数据分析和趋势预测算法；3.反馈生成：构建个性化绩效反馈和改进建议系统；4.系统开发：构建员工绩效智能助理平台；5.应用推广：设计绩效辅导和提升流程,"企业名称：企业51（医药研发与流通一体化企业） +应用技术：AI教练对话系统、行为数据分析、个性化培训推荐 +投资金额：未公开 +目标：提升员工技能，优化绩效辅导。 +降本/增效/提质：新员工专业知识考核成绩平均提升20分，拜访技巧首次通过率从62%提升至97%；经理辅导时间节省40%。 +来源网址：[已脱敏链接]" +87,,公共知识库管理平台,合作开发,2028Q1-2028Q4,8,运营管理,知识资产梳理，知识分类标准建立，知识图谱构建,建设企业公共知识库（包含公司内部规章制度、操作流程、运营规范等），支持文档智能分类管理、文档检索与知识问答，实现知识共享和传承，提升组织学习能力,知识图谱、NLP、知识管理,大模型,企业文档、专业知识、经验数据,可行性中：需要大量知识数据整理,办公室、各业务部门,1.知识体系：构建企业知识分类体系和标签系统；2.智能检索：开发知识检索和关联推荐算法；3.内容管理：构建知识库内容审核和更新机制；4.系统开发：构建公共知识库管理平台；5.应用推广：设计知识共享和协作机制,"企业名称：企业52 +应用技术：医疗大模型、知识图谱构建、智能问答系统 +投资金额：未公开 +目标：提升内部知识共享效率，支持决策科学性。 +降本/增效/提质：员工知识查询响应时间从30分钟缩短至3分钟，跨部门协作效率提升50%；通过智能分析临床数据，新品研发周期缩短15%。 +来源网址：[已脱敏链接]" +88,,智能流程优化系统,合作开发,2027Q2-2028Q2,11,运营管理,业务流程数据化，流程分析工具部署,智能分析和优化业务流程，提高运营效率和质量,流程挖掘、优化算法,小模型,流程数据、业务数据、效率指标,可行性中：需要流程挖掘技术,运营管理部、各业务部门,1.流程挖掘：构建业务流程数据采集和分析体系；2.瓶颈识别：开发流程瓶颈识别和优化建议算法；3.模拟优化：构建流程改进方案模拟和评估系统；4.系统开发：构建智能流程优化平台；5.持续改进：建立流程优化闭环管理机制,"以顺丰""超脑""和观远数据的智能平台为代表，它们通过大数据、AI算法和数字孪生技术，将整个物流链条数字化、可视化。这使得企业能够进行精准的预测（如提前48小时预测货量）、模拟不同方案的效果，并实现毫秒级的智能调度，从而大幅提升决策效率和准确性。 +[已脱敏链接] +[已脱敏链接]" +89,,智能合规管理系统,合作开发,2026Q2-2027Q2,8,运营管理,合规规则数据化，合规检查流程标准化,自动化合规检查和管理，降低合规风险，提高合规效率,规则引擎、合规检查,大模型,合规规则数据、业务数据、检查记录,可行性高：合规规则相对明确,质量管理中心、审计内控部,1.合规框架：构建企业合规管理框架和标准；2.风险识别：开发合规风险识别和评估算法；3.监测系统：构建实时合规监测和预警系统；4.系统开发：构建智能合规管理平台；5.培训体系：建立合规培训和意识提升机制,"企业名称：企业53（服务某医药流通企业） +应用技术：AI前置审方、知识图谱、实时风险预警 +投资金额：未公开 +目标：提升医保合规性，降低审核成本。 +降本/增效/提质：医保审核效率提升3倍，违规行为识别准确率达98%；通过智能监控药品流通数据，质量风险事件减少60%。 +来源网址：[已脱敏链接]" +90,,智能供应商管理平台,合作开发,2027Q1-2028Q1,11,运营管理,供应商数据整合（批发+零售），管理流程数据化,全面管理供应商全生命周期，提高供应商管理效率,供应商管理、数据分析,小模型,供应商数据、交易数据、绩效数据,可行性高：供应商数据相对完整,供应链业务部门,1.评估体系：构建供应商评估指标体系和模型；2.数据整合：收集供应商绩效数据和风险数据；3.算法开发：开发供应商分类和优化算法；4.系统开发：构建智能供应商管理平台；5.协同机制：建立供应商协同和发展管理体系,"企业名称：企业54（服务某药企） +应用技术：AI智能拓客、供应商健康度评分、动态资源匹配 +投资金额：未公开 +目标：优化供应商全生命周期管理，降低合作风险。 +降本/增效/提质：潜在线索转化率提升50%，供应商合规风险事件减少70%；终端开发成本下降35%，首单上量周期缩短20%。 +来源网址：[已脱敏链接]" +91,,智能客户关系管理,合作开发,2027Q1-2027Q3,8,运营管理,客户数据整合，CRM系统升级，客户画像模型建立,智能化客户关系管理，提升客户满意度和忠诚度,客户管理、数据分析、机器学习,大模型,客户数据、交易数据、互动数据,可行性高：客户数据相对完整,客户服务部、销售部门,1.客户画像：构建360度客户视图和画像体系；2.智能分析：开发客户价值评估和需求预测算法；3.自动化营销：构建智能营销活动和客户互动系统；4.系统开发：构建智能客户关系管理平台；5.服务优化：建立客户服务质量监控和改进机制,"企业名称：企业55 +应用技术：AI大数据分析、多模态知识图谱、智能推荐算法 +投资金额：未公开 +目标：提升客户复购率，优化供需匹配效率。 +降本/增效/提质：通过智能推荐系统，客户精准匹配率提升40%，复购率提高25%；日均处理智能问答超万次，响应时间缩短60%。 +来源网址：[已脱敏链接]" +92,,智能财务分析助手,合作开发,2027Q2-2027Q3,8,运营管理,财务数据整合，分析模型建立，指标体系完善,深度分析财务数据，提供精准的财务洞察和建议,数据分析、财务建模,小模型,财务数据、业务数据、市场数据,可行性高：财务数据相对完整,财务管理部,1.财务模型：构建财务分析指标体系和分析模型；2.数据整合：对接财务系统、业务系统数据；3.算法开发：开发财务异常检测和趋势预测算法；4.可视化平台：构建财务分析仪表板和报告系统；5.决策支持：提供财务决策建议和风险预警,"企业名称：企业56 +应用技术：国产大模型（DeepSeek/Qwen）、智能校验规则、自动化对接系统 +投资金额：未公开 +目标：提升财务处理效率，降低合规风险。 +降本/增效/提质：单笔支付业务处理时间从2小时缩短至5分钟，预算指标校验准确率达100%；通过智能分析集采业务税收优惠，年节省税费超200万元。 +来源网址：[已脱敏链接]" +93,,智能资产管理,合作开发,2027Q1-2027Q3,8,运营管理,资产数据整合，资产管理流程数据化,智能化资产全生命周期管理，提高资产利用效率,资产管理、RFID、数据分析,小模型,资产数据、使用数据、维护数据,可行性高：资产数据相对完整,财务管理部、设备管理部,1.资产建模：构建资产分类体系和评估模型；2.数据采集：收集资产信息、使用数据、维护记录；3.算法开发：开发资产价值评估和优化算法；4.系统开发：构建智能资产管理平台；5.优化机制：建立资产配置优化和维护管理体系,"企业名称：企业57 +应用技术：远程自动监控系统、物联网传感器、AI异常检测 +投资金额：未公开 +目标：优化门店资产管理，降低人工巡检成本。 +降本/增效/提质：门店管理人员从25人减至3人，年人力成本节省200万元；配送差错率从0.03%降至0.0068%，库存周转率提升18%。 +来源网址：[已脱敏链接]" +94,,智能预算管理,合作开发,2027Q2-2027Q4,8,运营管理,预算数据历史积累，预算模型建立,智能化预算编制和执行监控，提高预算精度和执行效率,预算建模、数据分析,小模型,历史预算数据、业务数据、执行数据,可行性高：预算数据相对完整,财务管理部,1.预算模型：构建预算编制模型和审批流程；2.数据整合：收集历史预算数据和业务预测数据；3.算法开发：开发预算分配优化和预测算法；4.系统开发：构建智能预算管理平台；5.监控机制：建立预算执行监控和调整机制,"企业名称：企业56 +应用技术：预算管理一体化系统、AI预测模型、自动化校验引擎 +投资金额：未公开 +目标：提升预算编制准确性，优化资源配置。 +降本/增效/提质：预算编制周期从2周缩短至3天，预算执行偏差率从15%降至5%；通过智能预测药品采购需求，库存积压成本降低30%。 +来源网址：[已脱敏链接]" +95,,智能投资分析,合作开发,2027Q2-2027Q3,11,运营管理,投资数据整合，投资分析模型建立,智能化投资决策支持，提高投资回报率和降低投资风险,投资分析模型、机器学习,大模型+小模型,投资数据、市场数据、风险数据,可行性中：需要复杂的投资分析模型,投资发展部、战略与证券事务部,1.投资模型：构建投资评估模型和风险分析框架；2.数据收集：整合市场数据、财务数据、行业数据；3.算法开发：开发投资组合优化和风险评估算法；4.系统开发：构建智能投资分析平台；5.决策支持：提供投资决策建议和效果评估,"PharmAID决策智能体平台（复星医药）：深度融合大模型技术，用于药物商业价值辅助决策。在结合点位预测、毒理优化等方面提升研发效率。提升药物研发决策的准确性和效率，加速研发成果转化。 +[已脱敏链接] +[已脱敏链接] +[已脱敏链接] + +DARWEN™ AI 平台（HEALWELL AI）：利用AI生成监管级真实世界数据（RWD）。曾与武田制药合作，分析药物在溃疡性结肠炎和克罗恩病中的剂量优化效果。为药品的商业价值和临床价值提供数据洞察，支持患者准入和行业发展。 +[已脱敏链接]" +96,,智能市场分析,合作开发,2027Q4-2028Q1,8,运营管理,市场数据源整合，分析模型建立,深度分析市场趋势和机会，支持业务决策和战略规划,市场分析、数据挖掘,大模型+小模型,市场数据、竞争对手数据、行业数据,可行性中：需要外部市场数据,战略与证券事务部、市场部,1.市场模型：构建市场分析框架和指标体系；2.数据采集：收集市场数据、消费者数据、竞争数据；3.算法开发：开发市场趋势预测和机会识别算法；4.系统开发：构建智能市场分析平台；5.策略支持：提供市场策略建议和效果评估,"企业名称：企业55 +应用技术：AI供需分析模型、价格趋势预测算法、区块链溯源系统 +投资金额：未公开 +目标：优化市场供需匹配，提升交易透明度。 +降本/增效/提质：市场供需预测准确率提升35%，中药材价格波动风险降低40%；通过智能分析产区数据，交易撮合效率提高60%。 +来源网址：[已脱敏链接]" +97,,智能竞争情报,合作开发,2028Q1-2028Q3,11,运营管理,竞争情报数据源整合，情报分析模型建立,实时监控竞争对手动态，提供竞争策略建议,情报分析、网络爬虫、NLP,大模型,竞争对手数据、公开信息、市场数据,可行性中：需要外部数据整合,战略与证券事务部、市场部,1.情报体系：构建竞争情报收集和分析体系；2.数据采集：整合公开数据、行业报告、社交媒体数据；3.算法开发：开发竞争分析和趋势预测算法；4.系统开发：构建智能竞争情报平台；5.预警机制：建立竞争动态预警和应对策略系统,"智慧芽新药情报库 & AI助手“芽仔”：智慧芽生物医药大模型(PharmaGPT)、自然语言处理(NLP)、知识图谱—— +✅ 药物竞争格局分析：分析药物管线、临床结果、专利文献，支持项目估值和竞品调研 。 +✅ 智能情报监控：监控全球药政官网、临床试验、专利等数据，支持设置提醒 。 +✅ AI对话式检索：通过自然语言提问，快速获取药物作用机制、市场竞争力等多维情报 。 +[已脱敏链接] +[已脱敏链接]" +98,,OA智能员工助手,合作开发,2027Q2-2027Q4,8,运营管理,员工服务知识库建设，服务流程数据化,构建24小时在线的多模态交互助手，基于制度知识库，解答薪酬福利、假期申请等问题，并根据语音/文字指令完成入职、离职、请假、出差、报销流程等动作。,对话系统、知识库、智能客服,大模型,员工服务知识库、服务流程数据,可行性高：客服机器人技术成熟,人力资源部、办公室,1.需求分析：梳理员工日常办公需求和痛点；2.功能设计：设计智能问答、任务管理、信息检索等功能；3.技术开发：集成语音识别、NLP、知识图谱等技术；4.系统集成：与OA系统、邮件系统、日历系统对接；5.推广应用：制定推广策略和使用培训计划,"今日人才“会议大师”智能体实现会议全流程自动化（从议程生成到纪要督办），行政人力成本降低。 +[已脱敏链接]" +99,,会议管理智能体,合作开发,2027Q1-2027Q3,5,运营管理,会议管理流程数据化，会议室资源数据化；需提前预设会议名称/规则，提供模板,智能化会议安排和管理，提高会议效率和资源利用率：通过分析历史协作数据，智能推荐会议参与人、资源分配方案，并动态优化跨部门任务优先级（会议室编排与申请，关联会议配置，包括席卡、耳麦、茶水；生成各部门职责分工/进度）,智能调度、资源管理,大模型+小模型,会议数据、人员数据、资源数据,可行性高：会议管理逻辑相对简单,办公室、各业务部门,1.会议流程：梳理会议组织和管理流程；2.功能设计：设计议程生成、会议记录、任务分配等功能；3.技术开发：开发语音识别、NLP、智能摘要等技术；4.系统集成：与日历、邮件、OA系统对接；5.效果评估：建立会议效率评估和优化机制,"通达AI智能助手支持语音创建会议、自动分配资源，会议冲突率下降会议室利用率大幅提升。 +[已脱敏链接]" +100,,智能网络安全监控系统,合作开发,2027Q2-2028Q2,14,运营管理,网络安全设备部署，安全策略数据化,智能化网络安全防护，提高网络安全防范能力,网络安全、入侵检测、威胁情报,小模型,网络流量数据、安全日志数据,可行性中：需要网络安全专业技术,IT部门、安全生产部门,1.安全模型：构建网络安全风险模型和防护体系；2.数据采集：收集网络流量、系统日志、安全事件数据；3.算法开发：开发异常检测和威胁识别算法；4.系统开发：构建智能网络安全监控平台；5.响应机制：建立安全事件响应和处置流程,"企业名称：企业58 +应用技术：DeepSeek大模型、动态测绘技术、智能联动防御系统 +投资金额：未公开 +目标：提升网络安全防护能力，降低攻击风险。 +降本/增效/提质：网络攻击识别准确率达98%，平均响应时间从30分钟缩短至15分钟；通过智能联动防御，安全事件处置效率提升80%。 +来源网址：[已脱敏链接]" +101,,党委宣传智能助手,合作开发,2026Q1-2026Q3,8,运营管理,1.完成宣传文档数据整合（梳理近2年内部宣传稿、活动素材，补全非结构化数据标签）；2.适配现有私有化大模型（基于数创部已部署的内部大模型，开发宣传场景专用插件）；3.建立宣传内容合规知识库（整合党委宣传规范、医药行业宣传政策）,1.自动优化宣传文件（如新闻稿、活动通知），内容修改效率提升60%，避免合规风险；2.支持文生图/图生图功能（如宣传海报生成），设计周期从3天缩短至4小时；3.减少人工创作与审核工作量，每年节约人力成本8万元,NLP（文本优化）、文生图模型（StableDiffusion适配）、知识图谱（宣传合规规则）、RPA（文档分发）,大模型,1.内部：党委宣传文档库、历史活动素材、私有化大模型训练数据；2.外部：医药行业宣传政策文件、合规图片素材库（如无版权医药相关图片）,可行性高：1.已有私有化大模型基础，无需重新部署算力；2.宣传数据可通过内部整理补全，非结构化数据处理难度低；3.文生图、文本优化技术成熟，合作定制可快速适配业务场景,党务部门,1.内容库建设：构建党委宣传内容库和素材库；2.智能创作：开发宣传内容自动生成和优化算法；3.渠道管理：构建多渠道内容发布和管理系统；4.系统开发：构建党委宣传智能助手平台；5.效果分析：建立宣传效果评估和优化机制,"杭州医学院：党员教育创新——制作112个AI数字人微党课视频，方便碎片化学习。 +[已脱敏链接]" +102,,公文智能写作,合作开发,2026Q2-2026Q4,8,运营管理,1.公文模板标准化（梳理公司常用公文类型，如通知、报告、请示，制定统一模板）；2.对接现有知识库智能体（复用数创部已上线的知识库，补充公文写作规范）；3.打通OA系统接口（确保生成公文可直接同步至OA审批流程）,1.基于需求自动生成公文初稿（如“会议通知”“工作报告框架”），写作时间从8小时缩短至1小时；2.公文格式合规率达98%，避免格式修改反复；3.支持公文内容智能校对（如错别字、标点错误、表述规范），审核效率提升50%,NLP（文本生成与校对）、模板引擎、知识图谱（公文写作规范）、RPA（OA同步）,大模型,1.内部：公司公文历史档案、OA系统流程数据、知识库智能体中的公文规范；2.外部：国家行政机关公文处理办法、医药行业公文写作案例,可行性高：1.公文模板标准化难度低（公司已有固定公文类型）；2.可复用现有知识库智能体，减少开发成本；3.OA系统接口具备开放性，RPA对接难度小,办公室（公文写作组）、各部门行政岗,1.模板梳理：联合各部门整理10类常用公文模板，明确“标题格式”“正文结构”“落款要求”等要素；2.知识补充：将公文写作规范（如《党政机关公文处理工作条例》）录入知识库智能体，关联历史公文案例；3.系统开发：开发公文写作模块，支持“需求输入→模板匹配→初稿生成→智能校对”流程；4.流程对接：用RPA将生成公文同步至OA系统，触发审批流程；5.培训推广：组织公文写作人员开展1次操作培训，1个月内完成全公司推广,"今日人才“公文写作助手”支持自动生成会议纪要、合规报告等文档，格式错误率下降、写作时间大幅缩短。 +[已脱敏链接]" +103,,党群报表自动生成,采购现有解决方案,2027Q1-2027Q2,5,运营管理,1.党群数据整合（打通HR系统员工党建信息、党建活动记录系统、党员考核数据，解决跨系统数据孤岛问题）；2.报表模板标准化（制定党员人数统计、活动开展情况、考核结果等15类常用报表模板）；3.对接现有BI报表工具（基于公司已试点的BI工具，开发党群报表专用模块）,1.自动抓取数据生成党群报表，生成周期从5天缩短至2小时，报表准确率达99%；2.减少人工统计与核对工作量（如党员人数跨省统计），每年节约人力成本6万元；3.支持报表动态钻取（如“党员人数→部门分布→入党时间”），满足多维度分析需求,RPA（数据抓取）、BI分析（报表生成）、数据可视化、规则引擎（报表逻辑）,小模型,1.内部：HR系统（党员信息）、党建活动系统（活动记录）、党员考核系统（考核分数）、现有BI报表数据；2.外部：上级党委报表要求文档,可行性高：1.党群数据集中在内部系统，整合难度低（HR、党建系统均为公司自有）；2.已有BI工具基础，开发专用模块成本低；3.报表逻辑固定（如党员人数=在职党员+退休党员），规则引擎易配置,办公室（党群工作组）、各分子公司党群部门,1.数据打通：开发HR系统、党建活动系统、考核系统的数据接口，建立党群数据中台，确保数据实时同步；2.模板制定：根据上级党委要求与内部需求，制定15类报表模板，明确数据来源与计算逻辑；3.模块开发：在现有BI工具中开发党群报表模块，支持自动抓取数据、生成报表、导出Excel/PDF；4.钻取配置：设置报表动态钻取规则，支持从汇总数据下钻至明细数据；5.试点验证：先在江苏省内分子公司试点，优化后推广至全国，确保符合上级报表要求,"国药医疗健康产业有限公司——致远互联AI-COP智能协同运营平台，搭建党建管理系统，旨在提升党建工作水平，推动党组织规范化建设。 +[已脱敏链接]" +104,,行政费用异常检测,采购现有解决方案,2027Q1-2027Q3,8,运营管理,1.行政费用数据标准化（梳理财务系统中行政费用类目，统一“办公费”“差旅费”“招待费”等字段口径）；2.异常检测规则库建立（如“单次招待费超5000元”“差旅费超部门月度预算30%”）；3.对接财务报销系统,1.实时识别行政费用异常，异常识别率从60%提升至92%，避免不合理支出（如超标准招待）；2.异常处理时间从24小时缩短至2小时，减少人工排查工作量；3.每年减少不合理行政支出12万元，行政费用率降低2%,异常检测算法（孤立森林）、数据挖掘（费用趋势分析）、规则引擎（异常阈值）、可视化预警,小模型,1.内部：财务系统（行政费用报销数据）、OA系统（部门预算数据）、历史异常费用案例；2.外部：医药行业行政费用基准数据（如人均办公费标准）,可行性高：1.行政费用数据集中在财务系统，格式规范，标准化难度低；2.异常规则多为量化指标（如金额、预算占比），规则引擎易配置；3.孤立森林算法成熟，对数据量要求低，现有数据可支撑,财务管理部（费用管控组）、办公室（行政组）,1.数据标准化：联合财务与行政部门，统一行政费用类目与统计口径，补全历史费用数据中的缺失字段；2.规则制定：梳理18类异常场景，设置阈值（如“招待费人均超300元”“差旅费无明细支撑”），录入规则引擎；3.模型训练：基于近2年行政费用数据训练孤立森林模型，优化异常识别精度；4.系统对接：将检测模块嵌入财务报销系统，报销时实时触发异常检测，推送预警至费用管控组；5.效果复盘：每月分析异常检测准确率，调整规则阈值（如旺季适当放宽差旅费预算占比）,"汇联易「合小E」：AI大模型、RAG、风控模型MI三合一；多语言票据识别 +识别如“时间矛盾”、“空间穿越”、“重复报销”等违规操作，拦截率高达75%；帮助某企业年度节约违规支出超300万元。 +[已脱敏链接] +[已脱敏链接]" +105,,客户信用风险管理,采购现有解决方案,2027Q4-2028Q4,8,运营管理,1.客户数据整合（打通CRM系统客户信息、财务系统应收账款数据、销售系统交易记录，解决信息孤岛问题）；2.信用评估模型建立（含“偿债能力”“交易历史”“行业风险”3类10项指标）；3.对接外部征信平台（如企查查、信用中国）,1.智能评估客户信用等级（准确率85%），坏账率从8%降至3%，每年减少坏账损失150万元；2.信用风险预警提前1-2个月，避免高风险客户合作（如濒临破产的医疗机构）；3.客户信用评估周期从7天缩短至1天，提升合作决策效率,机器学习（信用评分模型）、风险建模（逻辑回归+随机森林）、知识图谱（客户-交易-风险关联）、实时数据处理,大模型+小模型,1.内部：CRM系统（客户规模、合作年限）、财务系统（应收账款账期、付款记录）、销售系统（交易金额、频次）；2.外部：企查查（客户工商信息、失信记录）、信用中国（行政处罚信息）、医药行业客户信用报告,可行性中：1.内部客户数据可通过接口整合，但需协调CRM、财务、销售跨部门数据，周期约1个月；2.外部征信平台接口开放，对接成本低，但需签订数据使用协议；3.信用评估模型需6个月以上历史数据训练，现有交易数据可支撑,风险管理部、销售部门（客户管理组）、财务管理部（应收组）,1.数据整合：开发CRM、财务、销售系统数据接口，建立客户信用数据中台，统一客户唯一标识（如客户编码）；2.指标设计：制定信用评估指标（偿债能力40%：资产负债率；交易历史30%：付款准时率；行业风险30%：医药行业景气度）；3.模型训练：基于历史坏账案例与优质客户数据，训练信用评分模型，划分A/B/C/D四级信用等级；4.预警部署：设置风险阈值（如C级客户超500万元授信），触发预警后推送至销售与风控部门，配套风险应对方案；5.迭代优化：每季度更新外部征信数据，调整模型指标权重（如集采政策影响下，医院客户风险权重提升）,"云南省生物医药可信供应链金融平台利用区块链数据可追溯且难以篡改的特性，使上下游中小药商的交易数据和信用数据更加透明、可信。 +[已脱敏链接]" +106,,应收账款风险管理,合作开发,2026Q3-2027Q1,8,运营管理,1.应收账款数据整合（打通ERP系统应收单据、财务系统账期数据、CRM系统客户信用数据）；2.账期管理规则库建立（如“公立医院账期≤90天”“连锁药店账期≤60天”）；3.对接客户信用风险管理系统（复用项目105的信用等级数据）,1.智能管理应收账款账期，逾期率从15%降至5%，每年减少逾期资金占用成本60万元；2.自动计算客户授信额度（基于信用等级与交易规模），避免超额授信；3.催款提醒自动化（如账期到期前3天推送提醒），催款效率提升70%,机器学习（逾期预测模型）、RPA（催款通知发送）、规则引擎（账期与授信规则）、数据关联分析（信用-账期-逾期关联）,小模型,1.内部：ERP系统（应收金额、单据日期）、财务系统（账期设置、付款记录）、CRM系统（客户联系方式）、客户信用系统（信用等级，项目105输出）；2.外部：客户财务状况数据（如医院年度预算）、医药行业应收账款基准账期,可行性高：1.内部应收账款数据集中在ERP与财务系统，接口标准化，整合周期2周；2.可复用客户信用系统数据，无需重复建模；3.账期规则明确（按客户类型划分），规则引擎配置难度低,财务管理部（应收组）、销售部门（客户维护组）,1.数据打通：对接ERP、财务、CRM与客户信用系统，建立应收账款数据中台，关联“客户-应收单据-信用等级”；2.规则配置：按客户类型（公立医院、连锁药店、个体诊所）设置账期与授信规则，录入规则引擎；3.模型开发：训练逾期预测模型，基于“信用等级+账期剩余天数+交易金额”预测逾期概率；4.自动化部署：RPA自动发送催款通知（短信+邮件），逾期风险高的客户推送至销售部门跟进；5.效果跟踪：每月分析逾期率与催款效果，调整账期规则（如对优质A类客户放宽账期至120天）,"国药集团建立客户价值度分析模型，通过资信一体化平台对客户进行统一授信，避免多头授信风险；每月逐笔制定回求求计划，并加强应收账款对账，建立逾期账款清收机制。 +[已脱敏链接]" +107,,对账流程自动化,合作开发,2027Q2-2027Q4,5,运营管理,1.对账数据整合（打通财务系统明细账、ERP系统交易记录、银行流水系统、客户对账数据）；2.对账规则库建立（如“财务明细账金额=银行流水金额±手续费”“交易记录单号=客户对账单号”）；3.异常处理流程标准化（明确“金额不符”“单边账”的处理步骤）,1.自动完成多维度对账（财务-银行、财务-客户），对账时间从5天缩短至3小时，财务对账工作量减少85%；2.对账准确率达99.5%，减少人工核对错误（如金额小数点偏差）；3.异常对账自动标记原因（如“银行扣手续费2元导致差额”），处理效率提升60%,RPA（数据抓取与比对）、NLP（对账差异原因识别）、数据比对算法、可视化对账报表,大模型,1.内部：财务系统（应收账款/应付账款明细账）、ERP系统（采购/销售交易记录）、银行流水系统（收支数据）；2.外部：客户对账系统（客户提供的对账单）、供应商对账系统（供应商提供的对账单）,可行性高：1.银行、客户/供应商对账系统多支持API接口，对接难度低；2.对账规则多为“金额一致”“单号匹配”，逻辑简单，RPA易实现；3.现有财务数据格式规范，无需大规模标准化处理,财务管理部（对账组）、供应链业务部门（供应商对账组）、销售部门（客户对账组）,1.接口对接：开发财务、ERP、银行及外部客户/供应商对账系统接口，实现每日自动抓取对账数据；2.规则制定：梳理8类对账场景规则，如“采购对账：ERP采购金额=供应商对账单金额”“销售对账：财务应收金额=客户对账单金额”；3.系统开发：开发对账自动化模块，实现“数据抓取→自动比对→差异标记→原因识别→对账报表生成”流程；4.异常处理：设置异常分级，小额差异（＜10元）自动生成调整单，大额差异（≥10元）推送至对账人员处理；5.试点推广：先在供应商对账场景试点，优化后覆盖客户对账与银行对账,"企业名称：企业59（服务中药控股） +应用技术：智能合并报表系统、动态建模、业财数据打通 +投资金额：未公开 +目标：提升对账效率，降低人工干预成本。 +降本/增效/提质：对账周期从10天缩短至3天，数据一致性达100%；通过智能分析，财务报表生成效率提升70%。 +来源网址：[已脱敏链接]" +108,,财务数据异常检测,采购现有解决方案,2026Q3-2027Q1,8,运营管理,1.财务数据标准化（统一ERP财务系统中“收入”“成本”“费用”等科目核算口径，补全历史数据缺失字段）；2.异常检测模型建立（基于历史异常案例，如“成本突增20%”“费用类目错记”）；3.对接ERP财务系统与BI报表工具,1.实时检测财务数据异常（如科目错记、金额异常波动），识别率从55%提升至90%，避免财务错报风险；2.异常排查时间从48小时缩短至3小时，减少人工核对工作量；3.每年避免因财务异常导致的审计调整或处罚损失30万元,异常检测算法（DBSCAN聚类+孤立森林）、机器学习（异常分类模型）、数据挖掘（财务趋势分析）、可视化预警,小模型,1.内部：ERP财务系统（各科目明细账、记账凭证）、BI报表历史财务数据、历史财务异常案例（如审计调整记录）；2.外部：医药行业财务指标基准（如毛利率均值、费用率范围）,可行性高：1.财务数据集中在ERP系统，核算口径可通过财务制度统一，标准化周期1周；2.异常检测模型对数据量要求低，近3年财务数据可支撑训练；3.可对接现有BI报表，直接展示异常数据与趋势,财务管理部（核算组、内控组）、审计内控部,1.数据标准化：联合财务核算组，统一科目核算口径（如“差旅费”不含业务招待费），补全2023年以来的缺失财务数据；2.模型训练：基于历史异常案例（如“将‘采购成本’错记‘期间费用’”），训练异常检测模型，设置异常阈值（如科目金额波动超30%）；3.系统对接：将检测模块嵌入ERP财务系统，记账后实时触发检测，异常数据标注颜色并推送预警；4.趋势分析：在BI报表中开发财务异常趋势看板，展示“异常类型分布”“月度异常数量”；5.验证优化：每月结合审计反馈调整模型，如新增“集采政策下收入结构变化”的正常波动规则,"企业名称：企业56 +应用技术：AI异常检测模型、实时监控系统、自动化校验规则 +投资金额：未公开 +目标：提升财务数据准确性，降低审计风险。 +降本/增效/提质：异常数据识别准确率达99%，年均减少审计调整超500万元；通过智能监控，数据处理效率提升60%。 +来源网址：[已脱敏链接]" +109,,简历智能筛选,采购现有解决方案,2026Q1-2027Q1,8,运营管理,1.岗位需求数据整合（梳理HR系统中各岗位任职要求，如“数据分析师需掌握SQL+Python”）；2.简历筛选规则库建立（如“学历≥本科”“相关工作经验≥3年”“技能匹配度≥80%”）；3.对接招聘平台接口（如智联招聘、猎聘，获取简历数据）,1.自动筛选符合岗位要求的简历，筛选时间从100份/2小时缩短至100份/10分钟，HR筛选工作量减少85%；2.简历匹配准确率达90%，避免优质候选人遗漏（如“隐藏技能未被人工识别”）；3.减少无效面试邀约，面试通过率从30%提升至50%，节约面试组织成本,NLP（简历信息提取）、机器学习（相似度匹配模型）、规则引擎（筛选条件）、知识图谱（岗位-技能-简历关联）,大模型+小模型,1.内部：HR系统（岗位任职要求、历史录用简历特征）、员工绩效数据（如“高绩效数据分析师的技能特征”）；2.外部：招聘平台简历数据（PDF/Word格式）、医药行业岗位技能标准（如“医药销售需掌握GSP知识”）,可行性高：1.岗位需求数据在HR系统中已标准化，规则库配置难度低；2.NLP提取简历信息（如学历、技能、经验）技术成熟，适配PDF/Word格式；3.招聘平台接口开放，可批量获取简历数据,人力资源部（招聘组）、各业务部门（招聘需求方）,1.需求梳理：联合各业务部门，明确12类核心岗位的任职要求，标注“必备条件”（如“执业药师证”）与“优先条件”（如“医药行业经验”）；2.规则配置：在筛选规则库中录入条件，设置权重（学历20%、经验30%、技能50%）；3.模型训练：基于近2年录用简历与高绩效员工特征，训练相似度匹配模型，计算简历与岗位的匹配分数；4.平台对接：打通招聘平台接口，自动获取简历并提取信息，生成匹配分数与“推荐理由”；5.试点推广：先在“医药销售”“数据分析师”岗位试点，优化后覆盖全岗位，支持HR手动调整匹配权重,"企业名称：企业60 +应用技术：简历解析、智能匹配算法、AI面试调度系统 +投资金额：未公开 +目标：提升招聘效率，精准筛选人才。 +降本/增效/提质：简历处理效率提升3倍，面试周期从7天缩短至3天；通过AI分析候选人行为数据，新员工留存率提升15%。 +来源网址：[已脱敏链接]" +110,,培训需求智能识别,合作开发,2026Q1-2027Q1,8,运营管理,1.员工数据整合（打通HR系统员工信息、绩效系统考核数据、培训系统历史参训记录）；2.培训需求模型建立（关联“岗位-绩效短板-培训内容”，如“销售绩效低→客户谈判培训”）；3.对接培训课程库（确保需求与课程匹配）,1.自动识别员工培训需求（准确率85%），避免盲目培训（如“为无需求员工安排冗余课程”）；2.培训针对性提升，员工绩效改善率从40%提升至65%；3.培训需求分析周期从15天缩短至2天，HR培训规划效率提升80%,机器学习（需求预测模型）、数据挖掘（绩效-需求关联）、知识图谱（岗位-能力-课程关联）、个性化推荐,大模型+小模型,1.内部：HR系统（岗位、职级、学历）、绩效系统（考核分数、短板评语）、培训系统（历史参训记录、课程评价）；2.外部：医药行业岗位能力标准（如“新版GSP要求的质量管理能力”）、外部培训课程库（如医药行业合规课程）,可行性高：1.员工数据集中在HR、绩效、培训系统，接口可打通，整合难度低；2.培训需求与绩效短板关联逻辑清晰（如“物流调度绩效低→优化算法培训”）；3.现有培训课程库可支撑需求匹配，无需大规模新增课程,人力资源部（培训组）、各业务部门（员工发展组）,1.数据整合：开发HR、绩效、培训系统接口，建立员工培训数据中台，关联“员工-岗位-绩效-培训”数据；2.模型训练：基于历史培训效果数据（如“参加‘客户谈判’培训后销售绩效提升20%”），训练需求预测模型，识别“绩效短板→培训内容”映射关系；3.需求生成：每月自动生成员工个人培训需求清单（如“张三：客户谈判培训（绩效短板：客户签约率低）”）；4.课程匹配：对接培训课程库，为需求推荐适配课程，支持员工自主选择；5.效果跟踪：每季度分析培训后绩效改善情况，调整模型（如“增加‘AI工具应用’培训对IT岗位绩效的权重”）,"云南白药“白小七”数字员工通过分析员工技能短板与业务需求，自动生成个性化培训计划。 +[已脱敏链接]" diff --git "a/file_generation/input/FG_28/\346\226\207\344\273\266-1119.xlsx" "b/file_generation/input/FG_28/\346\226\207\344\273\266-1119.xlsx" new file mode 100644 index 0000000000000000000000000000000000000000..4e9ac68e71431d5836b9da90cb78ef80e98aabaa Binary files /dev/null and "b/file_generation/input/FG_28/\346\226\207\344\273\266-1119.xlsx" differ diff --git "a/file_generation/input/FG_3/\346\225\260\346\215\256.csv" "b/file_generation/input/FG_3/\346\225\260\346\215\256.csv" new file mode 100644 index 0000000000000000000000000000000000000000..f90b171307bc48ca027d0bcf38fe0064d64f6c21 --- /dev/null +++ "b/file_generation/input/FG_3/\346\225\260\346\215\256.csv" @@ -0,0 +1,129 @@ +公司,事业部,站点,员工名称,出行方式,任务审核状态,是否活跃 +公司1,事业部1,站点1,员工1,电动车,未提交,沉默 +公司1,事业部2,站点2,员工2,公共交通,未提交,沉默 +公司1,事业部3,站点3,员工3,电动车,未提交,沉默 +公司1,事业部1,站点1,员工4,电动车,未提交,沉默 +公司1,事业部1,站点1,员工5,公共交通,未提交,沉默 +公司1,事业部4,站点4,员工6,电动车,未提交,沉默 +公司1,事业部5,站点5,员工7,电动车,未提交,沉默 +公司1,事业部6,站点6,员工8,电动车,未提交,沉默 +公司1,事业部1,站点1,员工9,公共交通,未提交,沉默 +公司1,事业部7,站点7,员工10,电动车,未提交,沉默 +公司1,事业部2,站点2,员工11,公共交通,未提交,沉默 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