产业数据 · 企业洞察 · 决策依据Industrial Data · Enterprise Insight · Decision Support

从一条产业链,
到一家企业,再到一次决策From an industrial chain,
to a single enterprise,
to a decision

知源科技以五链合一的数据底座,把区域产业、集群分布与企业实况组织成同一条依据链, 为银行、金融机构、投资机构、交易平台、政府园区与国央企提供产业洞察、企业研判与风险监测能力。OriSyn Technology builds on its integrated five-chain data architecture to weave regional industries, cluster distributions, and enterprise realities into a single chain of evidence—empowering banks, financial institutions, investors, trading platforms, government zones, and state-owned enterprises with industrial intelligence, corporate assessment, and risk monitoring capabilities.

165条产业链目录Industrial Chains
6,000 万+商事主体覆盖Business Entities Covered
10 亿条企业关系穿透Corporate Relationships Mapped
7 万+个产业园区Industrial Parks

数据有源,产业合力Grounded in Data, Strengthened by Industry

每一组数据背后,都有一条看不见的来路。Behind every dataset lies an unseen origin.

在供应链日益复杂、产业边界不断消融的今天,企业面临的不再是单一环节的问题, 而是一张由数据、资源、信任交织而成的网。信息可以传递,但真相需要追溯; 节点可以连接,但价值需要共振。As supply chains grow more complex and industry boundaries dissolve, enterprises no longer face isolated problems but a web woven from data, resources, and trust. Information can be transmitted — but truth must be traced. Nodes can be connected — but value must resonate.

这正是知源科技 OriSyn 存在的理由。This is precisely why OriSyn Tech exists.

数据有源Grounded in Data

我们坚信,可信的决策始于可信的数据。从原材料的第一公里到交付的最后一环, 我们帮助企业穿透信息迷雾,回到数据的起点,验证每一份主张,厘清每一个关联。 溯源不是目的,让真相成为共识才是。We believe credible decisions begin with credible data. From the first mile of raw materials to the final link of delivery, we help enterprises cut through the fog of information, return to the origin of the data, verify every claim, and clarify every connection. Traceability is not the goal — making truth the shared consensus is.

产业合力Strengthened by Industry

我们同样坚信,没有一家企业能独自完成产业链的升级。供应商、制造商、品牌方、 金融机构、监管机构……每一方都握有拼图的一块。OriSyn 所做的,是在这些碎片之间 建立语言、标准和信任机制,让分散的力量找到共同的节奏,让个体的优势汇成系统的动能。We believe equally that no single enterprise can upgrade an industrial chain alone. Suppliers, manufacturers, brands, financial institutions, regulators — each holds one piece of the puzzle. What OriSyn does is establish a shared language, standards, and trust mechanisms among these fragments, so that dispersed forces find a common rhythm and individual strengths converge into systemic momentum.

从供应链溯源到数据智能,从产业集群诊断到国际对话平台,我们以技术为底座, 以方法论为纽带,陪伴企业走过「看清自己」到「连接世界」的每一步。From supply chain traceability to data intelligence, from industrial cluster diagnosis to international dialogue platforms, we use technology as the foundation and methodology as the connective tissue — accompanying enterprises through every step from seeing themselves clearly to connecting with the world.

OriSyn 不提供标准答案。我们提供回到源头的能力,和走向共生的路径。OriSyn does not offer standard answers. We offer the ability to return to the source, and a path toward symbiosis.

数据有源,所以决策有据;
产业合力,所以未来可期。Grounded in data, decisions stand on evidence.
Strengthened by industry, the future holds promise.

三层结构,逐级下钻,最终落到单个企业Three-tier structure, drill-down at each level, ultimately landing at the individual enterprise.

产业层看区域有哪些产业,集群层看产业里有哪些集群,企业层看集群里有哪些企业。 三层不是三张表,而是同一套数据的三种看法——因此三个问题指向同一份依据。The industry layer shows which industries exist in a region; the cluster layer shows which clusters exist within an industry; the enterprise layer shows which enterprises make up a cluster. These three layers are not three separate tables, but three views of the same dataset—so all three questions point to one shared chain of evidence.

01 / 产业层01 / Industry Layer

区域有哪些产业Which industries exist in the region

产业链拆解至环节,标出本地已有与缺失。可用的是「电池壳体」「热管理管路」这样的环节粒度,而非「新能源汽车」这样的笼统标签。The industrial chain is decomposed down to the component level, marking what exists locally and what is missing. The granularity is at the level of specific links—such as "battery enclosure" or "thermal management piping"—rather than broad labels like "new energy vehicles."

回答:做哪条链Answers: Which chain to pursue

02 / 集群层02 / Cluster Layer

产业里有哪些集群Which clusters exist within an industry?

集群标签、园区归属与集聚程度逐层呈现,支持以区域为起点筛选,也支持以链主为锚沿真实交易关系穿透。Cluster tags, park affiliations, and agglomeration levels are presented layer by layer—supporting filtering that starts from a region, or tracing along real transaction relationships anchored to a lead firm.

回答:找哪些企业Answers: Which enterprises to target

03 / 企业层03 / Enterprise Layer

集群里有哪些企业Which enterprises are in a cluster?

落到单个企业的主体、股权、产业链位置、经营体征与风险信号。每家企业均可回溯至链上环节、集群位次、园区归属、集团关系与供应链关系。Drill down to the individual enterprise—its legal identity, equity structure, position in the industrial chain, operating indicators, and risk signals. Every company can be traced back to its chain segment, cluster ranking, park affiliation, group relationships, and supply chain linkages.

回答:这家企业能否合作Answers: Whether this enterprise is viable to partner with

五条链,五个视角,同一批企业Five chains, five perspectives, one shared set of enterprises

五链不是五张表,而是一张可落到企业的实体网络。同一家企业,在五条链上各有坐标,合起来才构成完整画像。The five chains are not five separate tables, but one entity network that maps down to the enterprise level. A single company holds distinct coordinates across all five chains—and only together do they form a complete profile.

覆盖规模统计截至 2026 年 10 月Coverage metrics as of October 2026
链Chain看什么What it reveals规模Scale
产业链Industrial Chain 处于哪条链、哪个环节;上下游价值传导与环节空位Which chain and segment; upstream-downstream value transmission and segment gaps 165 条目录,三级节点165 industrial chains, three-level nodes
产业集群Industrial Cluster 区域有哪些集群、集群内有哪些企业、集聚与联动风险Which clusters exist in the region, which enterprises belong to each cluster, and the risks of agglomeration and cross-cluster linkage 1,429 个标签,364 万企业归属1,429 tags, 3.64M enterprise affiliations
产业园区Industrial Park 承载于哪个园区、园区企业结构、管委会批量入口Which park it belongs to, the enterprise composition of that park, and the bulk-entry channel for the park management committee 7 万+ 个园区,含主导产业70,000+ parks, with leading industries
产业集团Industrial Group 归属哪个集团、关联关系、并表与额度集中风险Which group it belongs to, its related-party relationships, and the risks of consolidated reporting and exposure concentration 370 万条成员关系,股权穿透3.7M membership relationships, equity look-through
供应链Supply Chain 与谁交易、规模多大;链主上下游真实交易关系Who it trades with and at what scale; the lead firm's real upstream and downstream transaction relationships 26.4 万条链上关系264K on-chain relationships

四层体系,支撑从数据到判断的完整链路A four-layer architecture powering the complete pipeline from data to judgment

底层是数据,中间是知识与模型,上层是面向具体问题的智能体。四层共用同一套企业主数据与指标口径。The foundation is data, the middle comprises knowledge and models, and the top layer consists of purpose-built agents for specific problems. All four layers share a unified set of enterprise master data and metric standards.

LAYER 01

数据层Data Layer

  • 工商、资质、知识产权、招投标、参保Business registration, licenses, intellectual property, tendering, social insurance enrollment
  • 中标、扩产、融资、招聘、政策公示Contract awards, capacity expansion, financing, hiring, policy announcements
  • 股权、集团、担保、投资、供应链关系Equity, group, guarantee, investment, and supply chain relationships
9 大类 73 张数据表9 categories, 73 data tables
LAYER 02

知识层Knowledge Layer

  • 产业链、集群、园区、集团、供应链Industrial chain, cluster, park, group, supply chain
  • 14 类关系定义与 45 项知识资产14 relationship definitions and 45 knowledge assets
  • 五链合一的统一实体网络A unified entity network integrating the five chains
14 类关系 · 45 项知识资产14 relationship types · 45 knowledge assets
LAYER 03

模型层Model Layer

  • 主体风险、事件预警、隐含违约率Entity risk, event alerts, implied default rate
  • 交易真实性、名单分层、位次测算Transaction authenticity, list stratification, ranking estimation
  • 规则、图谱、模型、大模型四引擎Four engines: rules, graphs, models, and large language models
6 大模型族 · 25 个模型6 model families · 25 models
LAYER 04

智能体层Agent Layer

  • 场景 Agent、专业 Skill、数据 MCPScenario agents, professional skills, data MCP
  • 报告生成、名单筛选、风险监测Report generation, list screening, risk monitoring
  • 数十个智能体对应不同业务场景Dozens of agents mapped to different business scenarios
数十个智能体协同交付Dozens of agents delivering in coordination

六类客户,六个切入点,同一套数据底座Six client types, six entry points, one data foundation

不同机构的问题不同,但答案都指向同一件事——企业在产业里的位置。位置清楚了,名单才有依据,预警才有指向。Different institutions face different questions, but the answers all point to the same thing—where an enterprise sits within its industry. Once that position is clear, prospect lists gain a basis, and early warnings gain direction.

A

银行Banks

对公业务的两件事:找对客户、看住客户。从产业链圈定名单,从经营体征识别风险,营销与风控共用同一套数据。Two priorities in corporate banking: identify the right clients, and monitor them effectively. Define prospect lists through the industrial chain, and detect risks through operating indicators—marketing and risk control powered by the same dataset.

B

金融机构Financial Institutions

担保、租赁、保理、小贷与保险,覆盖准入、承做、存续三段,按机构类型切换交付物与阈值。Guarantee, leasing, factoring, micro-lending, and insurance—covering three phases: onboarding, underwriting, and portfolio monitoring, with deliverables and thresholds tailored by institution type.

C

投资机构Investment Institutions

二级市场从过载信息中筛出真信号,一级市场从空白信息中拼出全貌,投前尽调与投后监测一体贯通。The secondary market filters true signals from information overload; the primary market pieces together a full picture from information gaps. Pre-investment due diligence and post-investment monitoring are integrated into one continuous workflow.

D

交易平台Trading Platforms

交易的风险不在对方是否具备资金实力,而在交易是否真实。主体、关系、交易、履约四道检验,每条结论附证据链。The risk in a transaction lies not in whether the counterparty has the financial capacity, but in whether the transaction is real. Four lines of verification—entity, relationship, transaction, and performance—with an evidence chain attached to every conclusion.

E

政府与园区Government and Parks

招得来、看得住、补得准。从产业链缺口识别到目标企业筛选,再到落地企业承诺兑现监测,形成闭环。Attract the right ones, monitor them effectively, and fill gaps with precision. From identifying industrial chain gaps to screening target enterprises, and on to monitoring the fulfillment of commitments by settled enterprises—forming a closed loop.

F

国央企State-Owned Enterprises

穿透式监管不是增加报表,而是把监管要求转化为可执行的数据规则。支持本地化部署,内外两张网在同一套模型下计算。Penetrative supervision is not about adding more reports—it is about translating regulatory requirements into executable data rules. Supports on-premise deployment, with internal and external networks computed under the same model.

四条基线,决定输出能否被直接使用Four baselines that determine whether our output can be used directly

数据产品最大的风险不是覆盖不够,而是以估算填充空缺、以结论替代依据。以下四条在所有交付物中一致执行。The greatest risk in a data product is not insufficient coverage, but filling gaps with estimates and substituting conclusions for evidence. The following four principles are consistently enforced across all deliverables.

01

真源不造数No Fabrication Data

只取数据源原始值,查不到写「—」,不补 0、不估算填充。空位据实标注,反而构成判断依据。We take only raw values from source systems. Where data is unavailable, we mark it with "—"—never filling with zeros or estimates. Leaving gaps visible, in fact, becomes part of the basis for judgment.

02

公开与授权分版Separate Editions for Public and Authorized Data

财税、流水、征信须经授权,未授权章节显示「—」。同一份报告,授权范围不同,呈现内容不同。Tax, transaction, and credit data require authorization; unauthorized sections display "—". The same report renders different content depending on the scope of authorization granted.

03

可装配、可追溯Configurable and Traceable

规则来源、字段出处、报告版本与操作记录全留痕。任何一条结论都能回溯至具体数据与具体条款。Full traceability of rule sources, field origins, report versions, and operation logs. Every conclusion can be traced back to specific data and specific clauses.

04

不替代决策No Decision Substitution

系统给出事实依据、风险提示与测算区间;授信、准入、投资等决策由使用方作出,边界清晰。The system provides factual evidence, risk alerts, and estimation ranges; decisions on credit, onboarding, investment, and the like are made by the user—with clear boundaries.

已在多类机构落地,覆盖营销、风控、监管三类场景Live deployments across multiple institutions, spanning marketing, risk control, and regulatory scenarios.

以下为脱敏表述,仅说明业务形态与交付方式,不涉及具体机构名称与内部数据。The following is a desensitized description, outlining business models and delivery methods only, without involving specific institution names or internal data.

国有大型商业银行Large State-Owned Commercial Bank

产业集群白名单与批量获客Industrial Cluster Whitelists and Batch Client Acquisition

覆盖 100 余个重点产业集群,白名单批复规模 90 亿元以上,获贷率与审批效率同步提升。Covering 100+ key industrial clusters, with whitelist approvals exceeding RMB 9 billion, and simultaneous improvements in loan uptake rate and approval efficiency.

国有大型商业银行省级分行Provincial Branch of a Large State-Owned Commercial Bank

省域集群全覆盖Provincial Cluster Full Coverage

国家级、省级与地方集群分层建库,覆盖企业 2.3 万户以上,投放规模 130 亿元以上。National, provincial, and local clusters are stratified into a tiered database, covering over 23,000 enterprises, with a deployment scale exceeding RMB 13 billion.

城市商业银行City Commercial Bank

连续建设七年Seven Years of Continuous Development

覆盖 11 个部门,迭代至 6.0 版本,系统活跃度居全行前三,营销与风控共用一套底座。Covering 11 departments and iterated to version 6.0, with system activity ranking among the top three bank-wide; marketing and risk control share one foundation.

金融租赁公司Financial Leasing Company

租赁行业首个「租赁大脑」The first-ever “Leasing Brain” platform in the leasing industry

业态 × 产业风险矩阵、租金承受力测算与租后三级监测,支持不同业态下的差异化风险权重。Business-type × industry risk matrix, rental affordability calculation, and three-tier post-lease monitoring—supporting differentiated risk weights across business types.

交易集团Trading Group

12 类业态的对手方核查Counterparty Verification Across 12 Business Formats

以「业态定场景、产业定特征、数据定精度」构建动态权重模型,配套一票否决项与三级监测频率。A dynamic weighting model built on "business type defines the scenario, industry defines the characteristics, data defines the precision," complemented by veto items and a three-tier monitoring frequency.

中央企业Central State-Owned Enterprise

虚假贸易识别知识库Trade Fraud Detection Knowledge Base

覆盖 10 亿条企业经济关系,按贸易管理要求形成事前防范、事中管控、事后审查的闭环。Covering 1 billion corporate economic relationships, forming a closed-loop of pre-transaction prevention, transaction monitoring, and post-transaction review aligned with trade compliance requirements.

上述项目由知源科技及其关联技术团队交付。团队自 2006 年起承担银行业监管客户风险预警系统建设, 相关模型能力持续演进至今。The projects above were delivered by OriSyn Tech and its affiliated technical team. Since 2006, the team has built client risk early-warning systems for banking regulators, and the underlying modeling capabilities have continued to evolve.

一家专注产业数据价值化的技术公司A technology company focused on realizing the value of industrial data

北京合韵知源科技有限公司(品牌名「知源科技」)专注产业数据的组织与价值化。 我们的判断是:产业数据的价值不在于覆盖多少家企业,而在于能否支撑一次具体的判断—— 做哪条链、找哪些企业、这家企业能否合作。 OriSyn Technology (Beijing) Co., Ltd. (brand: OriSyn Tech) specializes in the organization and value realization of industrial data. Our conviction is this: the value of industrial data is not in how many enterprises it covers, but in whether it can support one concrete judgment—which chain to pursue, which enterprises to target, and whether a given enterprise is viable to partner with.

围绕这一判断,我们把分散的工商、司法、经营、关系与产业数据,组织成五链合一的实体网络, 再以模型与智能体把它转化为可交付的报告、名单与预警。 我们的服务支持 SaaS、本地部署与定制三种形态。Building on this conviction, we organize fragmented administrative, legal, operational, relational, and industrial data into an integrated five-chain entity network—then transform it through models and agents into deliverable reports, lists, and alerts. Our services support three deployment models: SaaS, on-premise, and custom.

公司全称Legal Name
北京合韵知源科技有限公司OriSyn Technology (Beijing) Co., Ltd.
英文名称English Name
OriSyn Technology (Beijing) Co., Ltd.
品牌名称Brand Name
知源科技OriSyn Tech

从一个具体的产业问题开始Start with a Specific Industrial Question

如果你正在判断一条产业链的机会、一批企业的准入,或一套监测体系的落地方式, 欢迎与我们联系。我们会先理解问题,再讨论方案。If you are evaluating an industrial chain opportunity, screening a batch of enterprises for onboarding, or determining how to implement a monitoring system, we invite you to get in touch. We start by understanding the problem, then discuss the solution.

商务邮箱Business Email
contact@heyunzhiyuan.cn
公司全称Legal Name
北京合韵知源科技有限公司OriSyn Technology (Beijing) Co., Ltd.
企业微信WeCom
企业微信客服二维码 / WeCom customer service QR code 微信扫码,直接发起对话Scan with WeChat to start a chat