[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"appearance-override":3,"footer-products":36,"solutions":677,"footer-solutions":891,"footer-tagline":980,"products":1064},{"hero":4,"colors":14,"fonts":17,"radius":21,"darkMode":23,"sections":24},{"title":5,"subtitle":8,"badge":11,"imageKeyword":13},{"zh":6,"en":7},"一个平台，构建所有业务系统","One platform for every business system",{"en":9,"zh":10},"Enterprise agent platform: agents that remember, measurable and governed. Build systems by sentence, query data by question, refine workflows by chat — modeling, data chat, AI and orchestration chained into one pipeline. Agent Factory ships 60 business agents out of the box","企业级智能体平台：智能体会记忆、可评测、受管控。一句话建系统、问一句查数据、聊着改流程——建模、问数、AI、编排四样能力装进一条链路；智能体工厂 60 个业务智能体开箱即用",{"en":12,"zh":12},"OntoX AI Platform","modern AI technology company office with holographic data dashboards",{"primary":15,"secondary":16},"#00BCD4","#26C6DA",{"family":18,"headingFamily":19,"baseSize":20},"ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, 'PingFang SC', 'Microsoft YaHei', sans-serif","",16,{"base":22,"large":20},8,"always",[25,28,30,32,34],{"id":26,"visible":27},"hero",true,{"id":29,"visible":27},"products",{"id":31,"visible":27},"solutions",{"id":33,"visible":27},"stats",{"id":35,"visible":27},"cta",[37,105,170,235,300,360,418,483,545,612],{"id":38,"slug":39,"name":40,"tagline":43,"description":46,"image_url":49,"pairs_with":50,"features":53,"icon":97,"color":98,"sort_order":99,"cross_border":100,"price":101,"badge":102},"5","oms",{"zh":41,"en":42},"OMS 对象建模","OMS Modeling",{"zh":44,"en":45},"一句话建模，60秒从想法到产品","One sentence to a working system in 60 seconds",{"zh":47,"en":48},"用自然语言描述业务需求，60秒生成生产级管理系统：数据库表、增删改查接口、管理界面、筛选分页、字段校验一次到位。传统开发新增一个业务对象要 10-18 天 4-5 人，OMS 一句话 1 分钟 0 行代码。配套状态机引擎管理对象生命周期，关联导航让对象之间的关系一眼穿透，数据导入导出开箱即用。","Describe your business need in natural language and get a production-ready system in 60 seconds: database tables, CRUD APIs, admin UI, filtering, pagination, and validation—all at once. Traditionally a new business object takes 10-18 days with 4-5 people; with OMS it is one sentence, one minute, zero code. Includes a state-machine engine for lifecycle management, cross-object navigation, and built-in import\u002Fexport.","\u002Fgenerated\u002Fsite-1-product-5-1790131085497.webp",{"zh":51,"en":52},"数据建好，交给 Loom 定时跑、DBChat 随口问，就是一条完整业务链","Once modeled, hand it to Loom for scheduling and DBChat for questions — a complete chain",[54,62,69,76,83,90],{"icon":55,"title":56,"description":59},"carbon:checkmark-outline",{"zh":57,"en":58},"自然语言建模","Natural-language modeling",{"zh":60,"en":61},"说一句\"帮我建患者管理\"即可生成完整系统","describe \"patient management\" and get a full system",{"icon":55,"title":63,"description":66},{"zh":64,"en":65},"全自动接口","Automatic CRUD",{"zh":67,"en":68},"定义即用,增删改查零代码","zero code from definition to API",{"icon":55,"title":70,"description":73},{"zh":71,"en":72},"状态机引擎","State machine",{"zh":74,"en":75},"业务对象生命周期可视化管理","visual lifecycle management",{"icon":55,"title":77,"description":80},{"zh":78,"en":79},"关联导航","Linked navigation",{"zh":81,"en":82},"对象间关系穿透查询","drill across related objects",{"icon":55,"title":84,"description":87},{"zh":85,"en":86},"数据质量检查","AI data quality",{"zh":88,"en":89},"自然语言描述规则,AI自动生成检查","describe rules in plain language",{"icon":55,"title":91,"description":94},{"zh":92,"en":93},"导入导出","Import & export",{"zh":95,"en":96},"CSV\u002FJSON批量处理开箱即用","built-in CSV\u002FJSON batch processing","i-carbon-model-alt","#1E40AF",1,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":103,"en":104},"核心引擎","Core Engine",{"id":106,"slug":107,"name":108,"tagline":111,"description":114,"image_url":117,"pairs_with":118,"features":121,"icon":164,"color":165,"sort_order":166,"cross_border":167,"price":168,"badge":169},"6","dbchat",{"zh":109,"en":110},"DBChat 数据对话","DBChat",{"zh":112,"en":113},"问数不写 SQL，人人自助取数","Ask your data questions, no SQL required",{"zh":115,"en":116},"连上数据库就能用自然语言问数，不写 SQL 不依赖数据分析师。系统先理解你的库表结构，再自动生成并执行查询，结果配图表直接可读。权限、脱敏、审计内置——该看到的人看到该看的数，问数全程留痕。业务人员自助取数，IT 不再被临时报表需求淹没。","Connect a database and ask questions in natural language—no SQL, no analyst queue. The system understands your schema, generates and executes queries, and returns charts ready to read. Permissions, data masking, and audit are built in: people see what they should see, and every question leaves a trail. Business users self-serve reporting; IT stops drowning in ad-hoc requests.","\u002Fgenerated\u002Fsite-1-product-6-1790131105541.webp",{"zh":119,"en":120},"配合 Loom 可把临时取数变成定时报表；数据结构用 OMS 建更顺","Pair with Loom to turn ad-hoc queries into scheduled reports; model structures in OMS first",[122,129,136,143,150,157],{"icon":55,"title":123,"description":126},{"zh":124,"en":125},"自然语言问数","Ask in plain language",{"zh":127,"en":128},"用日常话问业务问题,自动生成查询","everyday questions become queries",{"icon":55,"title":130,"description":133},{"zh":131,"en":132},"多数据源","Multi-source",{"zh":134,"en":135},"PostgreSQL\u002FMySQL\u002FOracle 异构库即插即问","PostgreSQL\u002FMySQL\u002FOracle out of the box",{"icon":55,"title":137,"description":140},{"zh":138,"en":139},"权限与脱敏","Permissions & masking",{"zh":141,"en":142},"行列级权限,敏感字段自动脱敏","row\u002Fcolumn-level control,sensitive fields masked",{"icon":55,"title":144,"description":147},{"zh":145,"en":146},"可视化呈现","Visual answers",{"zh":148,"en":149},"结果自动配图表,支持追问","charts auto-selected,follow-up supported",{"icon":55,"title":151,"description":154},{"zh":152,"en":153},"全程审计","Full audit",{"zh":155,"en":156},"谁问了什么、跑了哪条 SQL 全留痕","who asked what and which SQL ran",{"icon":55,"title":158,"description":161},{"zh":159,"en":160},"查询护栏","Read-only guardrails",{"zh":162,"en":163},"防误删误改,只读问数","no accidental writes","i-carbon-chat-bot","#0F766E",2,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":103,"en":104},{"id":171,"slug":172,"name":173,"tagline":176,"description":179,"image_url":182,"pairs_with":183,"features":186,"icon":229,"color":230,"sort_order":231,"cross_border":232,"price":233,"badge":234},"7","cortex",{"zh":174,"en":175},"Cortex AI推理","Cortex AI",{"zh":177,"en":178},"一个网关调所有大模型，坏了自动切","Every model through one gateway, auto failover",{"zh":180,"en":181},"统一的大模型推理网关，让平台上每个应用共享同一套模型能力：智能分析、报告生成、内容理解、辅助甄别。多模型自动降级——主模型超载或不可用时无缝切换，业务不中断。提示词集中管理版本化，调用统一计量。反洗钱 AI 甄别、尽调报告生成等场景都跑在这层之上。","A unified LLM gateway that lets every application on the platform share the same model capabilities: intelligent analysis, report generation, content understanding, and assisted review. Multi-model automatic failover keeps business running when a provider is slow or down. Prompts are versioned and centrally managed; usage is metered in one place. AI-assisted AML screening and due-diligence reports all run on this layer.","\u002Fgenerated\u002Fsite-1-product-7-1790131128963.webp",{"zh":184,"en":185},"所有引擎的 AI 能力都从它出：Loom 流程里嵌它，DBChat 问答用它","All AI capabilities flow from it: embedded in Loom steps, used by DBChat answers",[187,194,201,208,215,222],{"icon":55,"title":188,"description":191},{"zh":189,"en":190},"统一网关","One gateway",{"zh":192,"en":193},"一个入口调所有模型,应用零耦合","every model through one entry,zero app coupling",{"icon":55,"title":195,"description":198},{"zh":196,"en":197},"多模型降级","Auto failover",{"zh":199,"en":200},"主模型异常自动切换,业务不中断","seamless switch when a provider fails",{"icon":55,"title":202,"description":205},{"zh":203,"en":204},"提示词管理","Prompt governance",{"zh":206,"en":207},"集中版本化,改动可追溯","versioned and traceable",{"icon":55,"title":209,"description":212},{"zh":210,"en":211},"用量计量","Usage metering",{"zh":213,"en":214},"调用次数与令牌统一统计","calls and tokens in one place",{"icon":55,"title":216,"description":219},{"zh":217,"en":218},"场景即用","Ready scenarios",{"zh":220,"en":221},"分析\u002F甄别\u002F报告生成内置场景","analysis,screening,report generation",{"icon":55,"title":223,"description":226},{"zh":224,"en":225},"私有化部署","Private deployment",{"zh":227,"en":228},"支持内网离线环境","runs fully offline in intranets","i-carbon-machine-learning-model","#7C3AED",3,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":103,"en":104},{"id":236,"slug":237,"name":238,"tagline":241,"description":244,"image_url":247,"pairs_with":248,"features":251,"icon":294,"color":295,"sort_order":296,"cross_border":297,"price":298,"badge":299},"8","loom",{"zh":239,"en":240},"Loom 场景编排","Loom Orchestration",{"zh":242,"en":243},"复杂工作流写成配置，不写代码","Write workflows as config, not code",{"zh":245,"en":246},"复杂业务流程不用写代码：数据抽取、清洗、模型跑批、报告生成、通知分发，像搭积木一样组合。跑批失败自动从断点接着跑，每步结果可对账。跑批调度、参数推演、AI 辅助甄别这类重活都是它干的。要改流程？改个配置就行，不用等程序员排期。","Complex business workflows without writing code: extraction, cleansing, model batch runs, reports, notifications—composed like building blocks. Failed batches resume from checkpoints; every step reconciles. Heavy lifting like scheduling, parameter simulation, and AI-assisted review runs on it. Change a flow by editing config, never waiting on developers.","\u002Fgenerated\u002Fsite-1-product-8-1790131153430.webp",{"zh":249,"en":250},"数据建好后定时跑批自动出报表,结论自动送达该收的人","Once your data is modeled,scheduled batches produce reports and conclusions reach the right people automatically",[252,259,266,273,280,287],{"icon":55,"title":253,"description":256},{"zh":254,"en":255},"零代码编排","Zero-code flows",{"zh":257,"en":258},"业务流程像搭积木,改流程不用等程序员","compose steps like blocks,no developers needed to change flows",{"icon":55,"title":260,"description":263},{"zh":261,"en":262},"断点续跑","Resumable",{"zh":264,"en":265},"跑批失败从断点恢复,不重头再来","failed batches continue from checkpoints",{"icon":55,"title":267,"description":270},{"zh":268,"en":269},"多引擎步骤","Multi-engine steps",{"zh":271,"en":272},"SQL\u002F模型\u002F脚本\u002F通知一类一步","SQL,models,scripts,notifications",{"icon":55,"title":274,"description":277},{"zh":275,"en":276},"结果可对账","Reconcilable",{"zh":278,"en":279},"每步产出落库,行数对得上","every step lands in DB,count by count",{"icon":55,"title":281,"description":284},{"zh":282,"en":283},"调度托管","Managed scheduling",{"zh":285,"en":286},"定时与依赖触发开箱即用","cron and dependency triggers built in",{"icon":55,"title":288,"description":291},{"zh":289,"en":290},"沙盘推演","What-if sandbox",{"zh":292,"en":293},"调参前先推演影响,数据说话","simulate before you commit parameters","i-carbon-flow-stream","#B45309",4,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":103,"en":104},{"id":301,"slug":302,"name":303,"tagline":306,"description":309,"image_url":312,"pairs_with":313,"features":316,"icon":352,"color":353,"sort_order":354,"cross_border":355,"price":356,"badge":357},"373237013597388868","agent-factory",{"zh":304,"en":305},"智能体工厂","Agent Factory",{"zh":307,"en":308},"一句话，造出你的业务智能体","Create your business agent with one sentence",{"zh":310,"en":311},"用一句普通话描述业务任务——「分析账户交易，识别可疑资金链路」或「审本批病历内涵质量，逐条规则对照检核」——AI 几秒内提案领域、场景与数据表，你确认拍板后一键生成智能体，并在真实数据上双跑验证、结论一致才放行。AI 只提案、决策权在人，思考链与查询全程透明。两大形态（数据分析型+文档审查型）覆盖政企校医四条主战线，内置 42 个实战智能体开箱即用——换客户只换规则包，不动代码。","Describe your business task in one sentence—\"analyze transactions for suspicious fund flows\" or \"QC this batch of medical records against every rule\"—and AI proposes the domain, scenario, and tables within seconds. You confirm, the agent is generated, then verified by dual runs on real data with consistent conclusions before release. AI proposes; humans decide. Two agent archetypes (data-analysis and document-review) cover government, enterprise, education, and healthcare. 42 battle-tested agents out of the box; new customers swap rule packs, not code.","\u002Fgenerated\u002Fsite-1-product-373237013597388868-1790232012373.webp",{"zh":314,"en":315},"产出的智能体跑在 Loom 场景上，模型调度走 Cortex，与智能体平台的运行管控互补","Generated agents run on Loom scenarios with Cortex models, complementing Agent Platform governance",[317,324,331,338,345],{"icon":55,"title":318,"description":321},{"zh":319,"en":320},"一句话起步","One-sentence start",{"zh":322,"en":323},"说一句业务任务，AI 提案领域、场景与数据表，每表带行数与样例预览","State the task; AI proposes domain, scenario, and tables with row counts and previews",{"icon":55,"title":325,"description":328},{"zh":326,"en":327},"AI 只提案，人拍板","AI proposes, you decide",{"zh":329,"en":330},"换表、改名、换领域全部可改可拒，确认后才生成","Change tables, names, or domain—nothing is generated until you confirm",{"icon":55,"title":332,"description":335},{"zh":333,"en":334},"双跑验证门禁","Dual-run verification",{"zh":336,"en":337},"真实数据完整跑两遍、结论一致才放行，结果可复现才叫可信","Runs twice on real data; only consistent conclusions pass the gate",{"icon":55,"title":339,"description":342},{"zh":340,"en":341},"全程透明","Full transparency",{"zh":343,"en":344},"每步思考、每次查询、每条结论可展开查看，审计留痕","Every step, query, and conclusion inspectable with audit trail",{"icon":55,"title":346,"description":349},{"zh":347,"en":348},"42 个实战智能体","42 battle-tested agents",{"zh":350,"en":351},"政企校医等七大领域，数据分析型+文档审查型两大形态，拿来即用","Government, enterprise, education, healthcare and more; two archetypes, ready to use","i-carbon-bot","#4DA6FF",6,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":358,"en":359},"拳头产品","Flagship",{"id":361,"slug":362,"name":363,"tagline":366,"description":369,"image_url":372,"pairs_with":373,"features":376,"icon":412,"color":413,"sort_order":414,"cross_border":415,"price":416,"badge":417},"373237013597388869","agent-platform",{"zh":364,"en":365},"智能体平台","Agent Platform",{"zh":367,"en":368},"会记忆、可评测、受管控的企业级智能体","Enterprise agents that remember, benchmark, and stay governed",{"zh":370,"en":371},"智能体不是聊天玩具，是能扛生产任务的数字员工。跨会话记忆让智能体记住历史调查结论，不重复提问；任务评测基准让成功率可度量、可对赌；工具调用按角色管控，越权操作直接拒绝并留痕；执行沙箱限制资源消耗，失控渲染不拖垮宿主；每个智能体的调用与用量独立记账，成本一目了然。全部能力私有化部署，数据不出域。","Agents as production digital workers, not chat toys. Cross-session memory remembers past investigation conclusions; a benchmark suite makes success rates measurable; tool calls are gated by role with full audit trail; a sandbox caps resource usage; every agent's calls and token usage are metered separately. Fully private deployment.","\u002Fgenerated\u002Fsite-1-product-373237013597388869-1790232037045.webp",{"zh":374,"en":375},"工厂负责「造智能体」，平台负责「运行管控」——记忆\u002F评测\u002F权限\u002F沙箱","The factory builds agents; the platform governs them—memory, benchmarks, ACL, sandbox",[377,384,391,398,405],{"icon":55,"title":378,"description":381},{"zh":379,"en":380},"跨会话记忆","Cross-session memory",{"zh":382,"en":383},"记住历史结论与关键事实，跨任务复用","Recall past conclusions and facts across sessions",{"icon":55,"title":385,"description":388},{"zh":386,"en":387},"任务评测基准","Task benchmark",{"zh":389,"en":390},"30 项任务断言式判分，成功率可度量","30 tasks with assertion-based scoring",{"icon":55,"title":392,"description":395},{"zh":393,"en":394},"工具权限管控","Tool ACL",{"zh":396,"en":397},"按角色封禁工具调用，拒绝留痕可审计","Role-based tool gating with audit trail",{"icon":55,"title":399,"description":402},{"zh":400,"en":401},"执行沙箱","Sandbox",{"zh":403,"en":404},"限制 CPU\u002F内存\u002F超时，失控不扩散","CPU\u002Fmemory\u002Ftime caps contain runaway tasks",{"icon":55,"title":406,"description":409},{"zh":407,"en":408},"独立计量","Per-agent metering",{"zh":410,"en":411},"每个智能体调用与 token 独立记账","Calls and tokens metered separately","carbon:bot","#8B5CF6",7,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":19,"en":19},{"id":419,"slug":420,"name":421,"tagline":424,"description":427,"image_url":19,"pairs_with":430,"features":431,"icon":474,"color":475,"sort_order":414,"cross_border":476,"price":477,"badge":480},"910000001","aml-agents",{"zh":422,"en":423},"反洗钱智能体军团","AML Agent Legion",{"zh":425,"en":426},"14 个智能体覆盖反洗钱全链，连真库自主查证","14 agents across the full AML chain, querying live databases autonomously",{"zh":428,"en":429},"一句话派活，智能体自己查：预警甄别、名单核查、受益人穿透、资金网络图、报送对账、评级迁移……14 个反洗钱智能体覆盖监测-甄别-报送-审查全链路。每个智能体自主调用工具查真实数据库（4600 万交易 \u002F 78 万预警 \u002F 286 万评级轨迹量级），结论带真实数字、结构化落库、全程留痕可审计——不是演示数据，是银行真实量级的作战能力。","Say it once, the agent investigates: alert triage, sanctions screening, UBO tracing, fund-network graphs, report reconciliation, rating migration — 14 AML agents covering monitor-triage-report-review. Each agent queries live databases (46M transactions \u002F 780K alerts \u002F 2.86M rating tracks at bank scale) and files structured, auditable conclusions with real numbers.",{"zh":19,"en":19},[432,439,446,453,460,467],{"icon":55,"title":433,"description":436},{"zh":434,"en":435},"甄别效率诊断","Triage diagnostics",{"zh":437,"en":438},"78 万预警积压 51% 这类真数字一跑即出","real backlog numbers in one run",{"icon":55,"title":440,"description":443},{"zh":441,"en":442},"受益人穿透","UBO tracing",{"zh":444,"en":445},"3.2 万尽调任务与央行报备缺口自动盘点","32K due-diligence tasks auto-inventoried",{"icon":55,"title":447,"description":450},{"zh":448,"en":449},"资金网络图","Fund network",{"zh":451,"en":452},"57 万边交易图谱定位钱庄枢纽","570K-edge graph pinpoints hub accounts",{"icon":55,"title":454,"description":457},{"zh":455,"en":456},"报送对账","Report reconciliation",{"zh":458,"en":459},"4 万报文与回执断链全量核对","40K filings vs receipts fully checked",{"icon":55,"title":461,"description":464},{"zh":462,"en":463},"名单回溯","List retro-screening",{"zh":465,"en":466},"1.2 万命中记录多维甄别误报","12K hits multi-dimension triaged",{"icon":55,"title":468,"description":471},{"zh":469,"en":470},"AI 留痕审计","AI trace audit",{"zh":472,"en":473},"1.5 万推理会话可解释性治理","15K reasoning sessions governed","i-carbon-security","#DC2626",{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":478,"en":479},"咨询诊断 3-5 万起","From ¥30K consulting",{"zh":481,"en":482},"NEW · 62 场景全绿","NEW · 62 verified scenarios",{"id":484,"slug":485,"name":486,"tagline":489,"description":492,"image_url":19,"pairs_with":495,"features":496,"icon":539,"color":540,"sort_order":541,"cross_border":542,"price":543,"badge":544},"373237013597388870","aml-ng",{"zh":487,"en":488},"智能反洗钱平台","Next-Gen AML Platform",{"zh":490,"en":491},"甄别工作台 × 智能体军团 × 合规闭环，一套系统重定义反洗钱作业","Triage workbench, agent legion, and compliance loop—one system redefines AML operations",{"zh":493,"en":494},"以 AI 辅助甄别 · 人工审核签报为核心的新一代反洗钱作业平台。五大岗位工作台（甄别、复核、尽调、报送、合规）覆盖预警处置全链路，14 个 AML 智能体像员工一样分工协作、可考核；甄别回放让每一步 AI 推理可复核，覆盖矩阵与法规台账让合规检查从「迎检突击」变成「日常在线」。跑在真实银行级数据规模上：4600 万交易、78 万预警、286 万评级轨迹。","A next-generation AML operations platform built around AI-assisted triage with human sign-off. Five role workbenches cover the full alert lifecycle; 14 AML agents collaborate like staff. Triage replay makes every AI reasoning step reviewable; coverage matrix and regulation ledger turn compliance into daily routine. Proven on bank-scale data: 46M transactions, 780K alerts.",{"zh":19,"en":19},[497,504,511,518,525,532],{"icon":55,"title":498,"description":501},{"zh":499,"en":500},"五大岗位工作台","Five role workbenches",{"zh":502,"en":503},"甄别\u002F复核\u002F尽调\u002F报送\u002F合规按角色分流作业","Triage, review, CDD, reporting, compliance",{"icon":55,"title":505,"description":508},{"zh":506,"en":507},"14 个 AML 智能体","14 AML agents",{"zh":509,"en":510},"像员工一样分工协作产出可考核","Agents collaborate like staff, measurable",{"icon":55,"title":512,"description":515},{"zh":513,"en":514},"甄别回放","Triage replay",{"zh":516,"en":517},"AI 推理链逐步回放每步结论可复核","Replay AI reasoning chains step by step",{"icon":55,"title":519,"description":522},{"zh":520,"en":521},"覆盖矩阵","Coverage matrix",{"zh":523,"en":524},"类型学×指标覆盖度一屏可视盲区无处藏","Typology×indicator coverage visible",{"icon":55,"title":526,"description":529},{"zh":527,"en":528},"法规台账","Regulation ledger",{"zh":530,"en":531},"新规条款×平台落点逐条对齐落地有账","Regulation clauses mapped to controls",{"icon":55,"title":533,"description":536},{"zh":534,"en":535},"真库验证","Proven on real data",{"zh":537,"en":538},"16 万预警云端真库实时查询演示","160K alerts live on cloud demo","carbon:workspace","#2563eb",11,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":19,"en":19},{"id":546,"slug":547,"name":548,"tagline":551,"description":554,"image_url":557,"pairs_with":558,"features":561,"icon":604,"color":605,"sort_order":606,"cross_border":607,"price":608,"badge":609},"9","data-migration",{"zh":549,"en":550},"数据迁移","Data Migration",{"zh":552,"en":553},"整库搬迁不停业务，搬完即用","Full-database relocation without downtime",{"zh":555,"en":556},"异构数据库搬迁工具：Oracle、MySQL、PostgreSQL 之间整库迁移，表结构自动翻译、数据分批搬运、存量与增量衔接。字段类型方言差异自动适配，迁移前后行数与内容对账，搬完即用。老系统换新平台时，历史数据一次性带过去，不停业务。","Heterogeneous database relocation: full-database migration across Oracle, MySQL, and PostgreSQL with automatic schema translation, batched data movement, and initial-plus-incremental continuity. Dialect type differences are adapted automatically; row counts and content reconcile before and after. When replacing a legacy system, historical data moves over in one pass—without stopping the business.","\u002Fgenerated\u002Fsite-1-product-9-1790131179914.webp",{"zh":559,"en":560},"搬完的库当天可用 DBChat 问数、Loom 跑批","Migrated DB is queryable by DBChat and runnable by Loom the same day",[562,569,576,583,590,597],{"icon":55,"title":563,"description":566},{"zh":564,"en":565},"整库迁移","Full database",{"zh":567,"en":568},"表结构+数据+字典一次搬迁","schema+data+dictionaries in one pass",{"icon":55,"title":570,"description":573},{"zh":571,"en":572},"方言适配","Dialect adaptation",{"zh":574,"en":575},"Oracle\u002FMySQL\u002FPG 类型自动翻译","types translated across engines",{"icon":55,"title":577,"description":580},{"zh":578,"en":579},"批量高效","Parallel batches",{"zh":581,"en":582},"分片并行搬运,千万级小时级","tens of millions of rows in hours",{"icon":55,"title":584,"description":587},{"zh":585,"en":586},"增量衔接","Incremental handoff",{"zh":588,"en":589},"存量搬完接增量,不停业务","cutover without downtime",{"icon":55,"title":591,"description":594},{"zh":592,"en":593},"迁移对账","Reconciliation",{"zh":595,"en":596},"前后行数与内容核对恒等","row counts and content verified equal",{"icon":55,"title":598,"description":601},{"zh":599,"en":600},"回滚预案","Reversible",{"zh":602,"en":603},"切换前可演练可回退","rehearse and roll back before cutover","i-carbon-data-share","#0369A1",90,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":610,"en":611},"扩展应用","Extension",{"id":613,"slug":614,"name":615,"tagline":618,"description":621,"image_url":624,"pairs_with":625,"features":628,"icon":671,"color":672,"sort_order":673,"cross_border":674,"price":675,"badge":676},"10","atomatch",{"zh":616,"en":617},"名单匹配","AtoMatch",{"zh":619,"en":620},"制裁名单筛查，先保不漏报再降误报","Sanctions screening: recall first, fewer false positives",{"zh":622,"en":623},"多算法实体名单匹配引擎，为制裁名单筛查、客户尽调、风险名单监控而生。精确、拼音、模糊多路召回互补，先保不漏报，再降误报。亿级名单万级吞吐实测验证，匹配结果带证据可解释，满足监管对筛查留痕的要求。","A multi-algorithm entity matching engine built for sanctions screening, KYC, and watchlist monitoring. Exact, transliteration, and fuzzy recall run in parallel and complement each other—maximize recall first, then reduce false positives. Validated at 100M-scale lists with 10K-scale throughput; every match carries explainable evidence for regulatory audit trails.","\u002Fgenerated\u002Fsite-1-product-10-1790131206285.webp",{"zh":626,"en":627},"命中的名单自动生成 OMS 工单，走 Loom 流程分发处置","Hits become OMS tickets automatically, dispatched through Loom flows",[629,636,643,650,657,664],{"icon":55,"title":630,"description":633},{"zh":631,"en":632},"多路召回","Multi-path recall",{"zh":634,"en":635},"精确\u002F拼音\u002F模糊互补,先保不漏报","exact\u002Fpinyin\u002Ffuzzy complement,no miss first",{"icon":55,"title":637,"description":640},{"zh":638,"en":639},"亿级名单","100M-scale",{"zh":641,"en":642},"实测亿级数据万级吞吐","validated throughput on huge lists",{"icon":55,"title":644,"description":647},{"zh":645,"en":646},"证据可解释","Explainable",{"zh":648,"en":649},"每个命中给出匹配依据","every hit shows why it matched",{"icon":55,"title":651,"description":654},{"zh":652,"en":653},"监管留痕","Audit-ready",{"zh":655,"en":656},"筛查过程与结果全程可审计","screening fully traceable for regulators",{"icon":55,"title":658,"description":661},{"zh":659,"en":660},"多源名单","Unified lists",{"zh":662,"en":663},"制裁\u002F监管\u002F自建名单统一管理","sanctions\u002Fregulatory\u002Fprivate together",{"icon":55,"title":665,"description":668},{"zh":666,"en":667},"低误报","Fewer false positives",{"zh":669,"en":670},"多算法排序把人工复核量降下来","ranking cuts manual review load","i-carbon-rule-draft","#BE123C",91,{"sku":19,"hs_code":19,"moq":19,"lead_time":19,"production_capacity":19,"product_category":19,"target_markets":19},{"zh":19,"en":19},{"zh":610,"en":611},[678,719,760,801,848],{"id":106,"slug":106,"industry":679,"title":682,"description":685,"image_url":688,"pain_points":689,"highlights":699,"product_ids":709,"sort_order":99,"company":19,"challenge":710,"solution":713,"result":716},{"zh":680,"en":681},"反洗钱","AML",{"zh":683,"en":684},"AML 反洗钱全链路","AML End-to-End Compliance",{"zh":686,"en":687},"预警分诊、SAR 智能起草、名单筛查、大额报告、监管报文六维度校验——AI 员工顶上合规部三个岗位。","Alert triage, AI SAR drafting, sanctions screening, large-value reports and regulatory message validation.","\u002Fgenerated\u002Fsite-1-solution-6-1788599247212.webp",[690,693,696],{"zh":691,"en":692},"人工分诊慢且标准不一","Slow manual triage with inconsistent standards",{"zh":694,"en":695},"SAR 报告撰写耗时长","Time-consuming SAR report drafting",{"zh":697,"en":698},"名单筛查漏报风险","Sanctions screening miss risk",[700,703,706],{"zh":701,"en":702},"35 页前端真机走查全通过","35 pages of real-device frontend walkthrough all passed",{"zh":704,"en":705},"2000 万客户 \u002F 4610 万交易量级基准","20M customers \u002F 46.1M transactions benchmark",{"zh":707,"en":708},"名单筛查命中 89,016 条实测","89,016 sanctions screening hits in production tests",[],{"zh":711,"en":712},"监管要求逐年收紧，预警量却以每年 30% 以上的速度增长；人工分诊一条预警平均要 15 分钟，标准还因人而异；可疑交易报告从取证到成文人均 2 小时起步；名单筛查最怕漏报——漏一个制裁主体就是合规事故。团队全年疲于奔命，精力被低价值的初筛占满，真正的可疑集团案件反而没有时间深挖。","Alert volumes grow 30%+ yearly under tightening regulation; manual triage averages 15 minutes per alert with inconsistent standards; SAR drafting takes 2 hours per report; the deadliest risk is a missed sanctioned party.",{"zh":714,"en":715},"按\"接入—监测—处置\"整链重建：数据接入环节自动对账补数，指标引擎逐日跑批产出预警；AI 分诊给每条预警标注风险等级与证据摘要，高分自动进人工队列；SAR 报告由 AI 起草、人复核；名单筛查走多路召回加人工确认。全链路每个环节的规则、阈值、调度都可以在运行中调整，不用停机改代码。","Rebuild the full chain: automated data reconciliation, daily indicator runs, AI triage scoring every alert with evidence summaries, AI-drafted SARs with human review, multi-path watchlist recall. Every rule, threshold and schedule is adjustable at runtime.",{"zh":717,"en":718},"预警初筛工作量下降约 70%，分诊标准全行统一；SAR 成文时间从 2 小时压缩到 30 分钟以内；筛查召回经实战回溯验证无漏报。团队把精力转向集团案件深挖与模型调优。","~70% less manual triage, unified triage standards, SAR drafting down from 2h to 30min, zero missed sanctions in backtesting.",{"id":171,"slug":171,"industry":720,"title":723,"description":726,"image_url":729,"pain_points":730,"highlights":740,"product_ids":750,"sort_order":166,"company":19,"challenge":751,"solution":754,"result":757},{"zh":721,"en":722},"数据治理","Data Governance",{"zh":724,"en":725},"数据质量与血缘治理","Data Quality & Lineage",{"zh":727,"en":728},"元数据探查、质量规则七类校验、血缘追溯、指标对账——让企业数据可信可用可追溯。","Metadata discovery, 7-type quality checks, lineage tracing and metric reconciliation.","\u002Fgenerated\u002Fsite-1-solution-7-1788599255408.webp",[731,734,737],{"zh":732,"en":733},"多源数据口径不一","Inconsistent metrics across sources",{"zh":735,"en":736},"质量规则散落无沉淀","Quality rules scattered with no reuse",{"zh":738,"en":739},"出数对不上没人管","Nobody owns mismatched numbers",[741,744,747],{"zh":742,"en":743},"知识自动探查入库","Auto knowledge discovery into the glossary",{"zh":745,"en":746},"DQ 规则引擎+执行报告","DQ rule engine + execution reports",{"zh":748,"en":749},"跨库血缘图谱","Cross-database lineage graph",[],{"zh":752,"en":753},"数据散落在十几个系统里，同一个客户在 CRM、订单、风控三处的名字、证件号、手机号各不相同；报表口径对不上，每次开会先花半小时争论数字谁对；想查一个指标从哪张表算出来的，没有人说得清；出了数据事故，追责查不到链路。","The same customer looks different across CRM, orders and risk systems; reports never reconcile; nobody can trace where a metric comes from; incidents cannot be attributed.",{"zh":755,"en":756},"先用血缘治理把全库表与字段的来龙去脉登记成图：哪个指标、经过哪些加工、源自哪些表，一图可查；再上数据质量规则引擎，空值率、格式错误、跨表不一致逐日扫描，问题当天发现当天定位到责任人；所有修复走工单闭环，禁直改生产。","Lineage graph covering every table and field, a quality rule engine scanning daily for nulls, format errors and cross-system inconsistency, and a ticket-based remediation loop with no direct production edits.",{"zh":758,"en":759},"指标口径统一后报表争议消失；数据问题平均发现时间从\"下次开会\"缩短到当天；血缘图让新人一周即可接手老系统；全年数据事故归零。","Report disputes gone, issue detection from \"next meeting\" to same-day, onboarding cut to one week, zero data incidents for the year.",{"id":236,"slug":236,"industry":761,"title":764,"description":767,"image_url":770,"pain_points":771,"highlights":781,"product_ids":791,"sort_order":231,"company":19,"challenge":792,"solution":795,"result":798},{"zh":762,"en":763},"流程编排","Workflow Orchestration",{"zh":765,"en":766},"跨系统流程编排引擎","Cross-System Workflow Orchestration Engine",{"zh":768,"en":769},"声明式编排跨系统业务流程：数据接入、AI 处理、结果落库、通知触达，断点续跑零代码交付。","Declaratively orchestrate cross-system flows: data ingestion, AI processing, result persistence, notifications — zero-code with resume-from-checkpoint.","\u002Fgenerated\u002Fsite-1-solution-8-1788599263797.webp",[772,775,778],{"zh":773,"en":774},"业务流程靠手写代码串联","Flows glued together by hand-written code",{"zh":776,"en":777},"跨系统衔接靠人肉协调","Cross-system handoffs rely on human coordination",{"zh":779,"en":780},"故障排查从零重跑","Failures restart from scratch",[782,785,788],{"zh":783,"en":784},"跨系统流程统一编排","Unified cross-system orchestration",{"zh":786,"en":787},"流程零代码改配置","Zero-code flows, config-driven",{"zh":789,"en":790},"断点续跑质量门控","Resume-from-checkpoint with quality gates",[],{"zh":793,"en":794},"一个业务流程横跨四个系统：审批在 OA、数据在业务库、文档靠邮件、通知靠人盯。系统之间不连通，全靠人当\"胶水\"——复制粘贴、催办、对账。换一个人接手就断一次；流程改一个环节要约三个部门开两周会。","One process spans four systems glued together by people copying, pasting and chasing; handover breaks it; every change needs two weeks of cross-team meetings.",{"zh":796,"en":797},"用流程编排把四个系统串成一条自动化链路：定时器触发、条件分支路由、跨系统取数、AI 生成文档、异常自动告警重试。每个步骤的参数可配置可审计，流程版本可回滚；改流程不再改代码，配置生效即可重跑。","An orchestration chain across systems: schedulers, conditional routing, cross-system data fetch, AI document generation, automatic retries and alerts. Steps are configurable, auditable and rollbackable without code changes.",{"zh":799,"en":800},"端到端流程从人工三天缩短到自动 40 分钟；环节异常当小时告警，不再积压到月底对账才发现；流程变更上线周期从两周降到当天。","End-to-end time from 3 manual days to 40 automated minutes; exceptions alerted within the hour; change lead time from two weeks to same day.",{"id":802,"slug":802,"industry":803,"title":806,"description":809,"image_url":812,"pain_points":813,"highlights":824,"product_ids":837,"sort_order":838,"company":19,"challenge":839,"solution":842,"result":845},"11",{"zh":804,"en":805},"电子商务","E-commerce",{"zh":807,"en":808},"电商经营全链路","E-commerce Full Chain",{"zh":810,"en":811},"商品建档、内容出片、独立站上架、咨询应答、支付对账、随口问数、复购营销——七个环节一条链，聊着改。","From product modeling to remarketing: seven links in one chain, editable by chat.","\u002Fgenerated\u002Fsite-1-solution-11-1788963680333.webp",[814,816,818,820,822],{"zh":815,"en":815},"商品信息散在表格里",{"zh":817,"en":817},"商品图视频外包贵且慢",{"zh":819,"en":819},"咨询靠人盯",{"zh":821,"en":821},"经营数据要等开发取数",{"zh":823,"en":823},"复购营销没工具",[825,827,829,831,833,835],{"zh":826,"en":826},"一句话建商品进销存系统",{"zh":828,"en":828},"一张商品图自动出营销视频",{"zh":830,"en":830},"独立站自动上架",{"zh":832,"en":832},"AI 咨询应答转工单",{"zh":834,"en":834},"微信支付宝收款对账",{"zh":836,"en":836},"老板随口问数",[],60,{"zh":840,"en":841},"电商业务一环扣一环：商品资料要人肉整理上架、详情页设计排版耗时、客服咨询半夜也要回、账要等月底才能算清、卖得好的商品不知道为什么好。每个环节单点都有工具，但工具之间不连通，数据要人工搬运，团队忙于琐碎、没时间做经营决策。","Every ecommerce task is a siloed tool with humans moving data between them: listing, design, night-shift support, month-end books — no time left for actual decisions.",{"zh":843,"en":844},"一条链路串起经营全流程：商品建档自动生成带页面和权限的管理系统；AI 按商品资料批量产出图文详情与营销素材；独立站建站上架；客服由 AI 应答，复杂问题转人工；订单与回款自动归集；每天的经营数据自动汇成早报，波动超过阈值才提醒。想改哪个环节，说一句话就能调。","One chain runs the whole business: auto-generated product admin, AI-produced content and store pages, AI support with human escalation, automated order reconciliation, and a daily morning report that only alerts on anomalies. Every step adjustable by conversation.",{"zh":846,"en":847},"商品上架周期从三天缩到半天；客服响应全天候，人力聚焦复杂咨询；经营数据当天可见，补货和投放决策不再拍脑袋；全链路改动说一句就生效，不用找开发排期。","Listing time from 3 days to half a day, 24\u002F7 support coverage, same-day business visibility, changes shipped by sentence instead of dev sprints.",{"id":849,"slug":849,"industry":850,"title":853,"description":856,"image_url":859,"pain_points":860,"highlights":869,"product_ids":880,"sort_order":881,"company":19,"challenge":882,"solution":885,"result":888},"12",{"zh":851,"en":852},"内容媒体","Content & Media",{"zh":854,"en":855},"内容媒体矩阵运营","Content Media Matrix",{"zh":857,"en":858},"选题库、批量出片、多平台定时发布、数据回流、AI 找爆款规律——内容生产流水线，聊着改节奏。","Topic bank, batch production, scheduled multi-platform publishing, data feedback, AI pattern-finding.","\u002Fgenerated\u002Fsite-1-solution-12-1788963689441.webp",[861,863,865,867],{"zh":862,"en":862},"选题靠灵感没有沉淀",{"zh":864,"en":864},"产能上不去",{"zh":866,"en":866},"多平台手动发布",{"zh":868,"en":868},"哪条爆了说不清",[870,872,874,876,878],{"zh":871,"en":871},"选题库对象化管理",{"zh":873,"en":873},"AIGC 批量出片",{"zh":875,"en":875},"多平台定时自动发布",{"zh":877,"en":877},"表现数据自动回流",{"zh":879,"en":879},"AI 对比找爆款规律反哺选题",[],61,{"zh":883,"en":884},"内容团队同时运营五六个平台：选题靠感觉、素材生产排期乱、发布要逐个平台手动传、数据回流水慢半拍、什么内容火全凭印象。团队产能被重复劳动吃掉，爆款经验沉淀不下来。","Running 5-6 platforms with gut-feel topics, manual publishing, slow data loops and no institutionalized hit-making.",{"zh":886,"en":887},"矩阵运营一条链：选题库统一管理，AI 按选题批量生产图文与短视频脚本；多平台定时自动发布；发布后表现数据自动回流；AI 分析哪类选题在哪个平台跑得好，反哺选题库。每个平台的发布时间、内容配比、审核要求独立配置，改配置聊一句就行。","A matrix pipeline: unified topic library, AI batch content production, scheduled multi-platform publishing, automated performance datafeedback, and AI analysis of what works where — feeding back into the library. 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