Dataset opportunity
Fmi — 公共采购数据集机会
Fmi 持有的中等规模公共采购数据集，可用于招标情报和文档情报。
Score
71.1
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
收购
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market
全球采购分析市场在 2024 年估值为 42.7 亿美元，复合年增长率为 23.50%（来源：Data Bridge Market Research）。[3]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-23
US imposes tariffs over forced labor before global duty ends
supplychaindive.com ↗ - 📰press2026-07-23
How a St. Louis-based hub aims to fill the manufacturing workforce gap
manufacturingdive.com ↗ - 📰press2026-07-23
Despite steep decline in cyberattacks targeting manufacturers, threats remain high: report
manufacturingdive.com ↗ - 📰press2026-07-22
Trump restricts supply chain waivers for US defense industrial base
manufacturingdive.com ↗ - 📰press2026-07-22
AI-assisted training: How Google Cloud is addressing workforce challenges
manufacturingdive.com ↗
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 📝Published article
专注于智能供应链管理和全面流程控制
source ↗
Profile
Dataset profile
Type
公共采购数据集
Modality
文本
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待明确
Buyer persona
GovTech 和采购情报供应商
FMI 持有文本模态的公共采购数据集，其中包含其制造业务的详细 `工业数据`、`物联网数据` 和 `采购` 记录。这些信息直接适用于构建招标情报用例，使 AI 买家能够分析工业领域的招标规范、竞争对手投标模式和定价策略。
商业价值巨大，因为全球采购分析市场在 2024 年的估值为42.7 亿美元，预计复合年增长率为23.50%。[3] 尽管数据访问需要仔细协商以区分客户知识产权（按图制造设计）与 FMI 的专有运营数据（如制造过程遥测和精密公差日志），但该数据集的稀有性为训练高级 AI 模型提供了独特的优势。[3] ⚠ 尽职调查（有价值的数据，可协商访问）：按图制造模式意味着特定产品设计属于 OEM 客户；专有价值在于制造过程遥测、精密公差日志和洁净室环境数据；数据访问需要区分客户知识产权和 FMI 的运营过程数据。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Fmi 持有详细的复杂、端到端的工业采购和供应链运营的专有数据。该数据集记录了从预测和物流到高精度精密零件制造的所有内容。对于 GovTech 和采购情报供应商而言，这是一个训练高级招标情报模型的难得机会，可在每年增长超过 23% 的采购分析市场中获得显著的竞争优势。这些独特的数据能够更深入地了解工业招标，从初始需求到最终资格认证和交付。
See dimension details ↓- Dataset Specificity90
主导的‘采购’，工业领域，3 种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
适用于招标情报
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI 买家需求非常高，这得益于采购分析市场的快速增长，该市场正以 23.50% 的复合年增长率扩张。[3]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility30
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据胃口信号（1 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高，5 个近期外部信号 — 超出已货币化数据的专有数据
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit92
✓ 良好目标 — 这是一个良好目标，因为它是一家高科技制造商，其运营数据（生产、供应链）是副产品，而非其核心产品，但初始数据资产描述完全错误。问题：来源描述‘公共采购数据集机会’不正确；该公司的实际业务是高科技‘按图制造’，为私营部门 OEM 生产；该公司拥有 250-400 多名员工，处于典型中小企业定义（<250 名员工）的上限或之上。[2, 9]
- Deep Qualification90
⚠ 需要审查 — 该机会基于一个有缺陷的前提；FMI 是一家私营 B2B 制造商，持有有价值但高度受限的运营和客户知识产权数据，而不是‘公共采购数据集’，这使得提出的‘招标情报’用例与其实际业务不符。[数据集类型与实际活动不符：FMI 是一家为半导体、分析和医疗市场私营部门 OEM 提供服务的‘按图制造’B2B 制造商，而不是参与公共部门采购的实体。[11, 12]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据指向生产线上的时间序列数据，详细说明了机电模块的组装、测试和资格认证，这对于分析制造效率很有价值。
Procurement / tenders
这些核心文本证据记录了端到端的供应链管理流程，为训练关于预测和物流的招标情报模型提供了主要来源材料。
Industrial data
这些时间序列数据展示了在高精度制造方面的深厚专业知识，为具有严格公差的组件的技术规格和质量控制提供了关键背景。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Fmi Public Procurement — a Moderate public procurement dataset (Text modality) in the industrial domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Analytics market was valued at $4.27 Billion in 2024, CAGR 23.50% (source: Data Bridge Market Research). [3]. Investment score 71.1/100 (confidence 0.49). Recommended action: Acquire.
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