Dataset opportunity
Supplychainsolution — 监管记录数据集机会
由 Supplychainsolution 持有的中等规模监管记录数据集，可用于监管 RAG 和合规 Copilots。
Score
64.4
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
数据共享协议
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 size (indicative estimate)
全球供应链人工智能市场 = 2023 年为 51 亿美元，复合年增长率为 38.9%。[1, 5]。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-31
Comércio acelera em junho com retalho a crescer 3%
distribuicaohoje.com ↗ - 📰press2026-07-24
Produção nacional representa mais de 60% da oferta de frescos do Intermarché
logisticamoderna.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.
Profile
Dataset profile
Type
监管记录数据集
Modality
文本
Sector
移动
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — GDPR 敏感（个人身份信息审查）
Buyer persona
RegTech 和合规 AI 供应商
Supplychainsolution 持有一个监管记录数据集，其模态为文本，该数据集独特地结合了监管备案、物联网数据及其移动运营的交易记录。这个丰富、多源的数据集专门为监管 RAG 用例构建，使 AI 能够通过基于经过验证的运营和法律文件来回答复杂的合规和物流查询。
商业价值巨大，目标是全球供应链中的人工智能市场，该市场在 2023 年的估值为51 亿美元，并预计到 2030 年将以惊人的38.9% 的复合年增长率增长。[1, 5] 虽然由于客户出货详情、GDPR 下的个人身份信息以及海关数据限制，访问需要谨慎处理，但该数据集的稀有性和全面性在快速采用人工智能以提高效率和透明度的市场中提供了显著的竞争优势。[1] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据包括需要匿名化的客户出货详情；电子商务履行数据包含受 GDPR 管辖的个人身份信息（姓名/地址）；海关数据可能存在监管共享限制 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明 Supplychainsolution 在从电子商务订单到最终清关的整个物流生命周期中生成专有数据轨迹。由此产生的监管记录数据集，通过真实的交易和物联网数据独特地进行情境化，具有极高的价值。对于 RegTech 供应商来说，这是一个难得的机会，可以获取构建强大的监管 RAG 系统所需的地面真相数据，并抓住蓬勃发展的供应链人工智能市场的一部分，该市场预计每年增长近 40%。
See dimension details ↓- Dataset Specificity90
主导的“监管”，移动行业，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
适用于监管 RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
人工智能买家需求异常高，这得益于市场的爆炸式增长，预计将以 38.9% 的复合年增长率扩张，因为公司竞相部署人工智能以优化供应链。[1, 5]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
个人身份信息/受监管
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
低难度，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 License28
所有权=混合，许可=GDPR 敏感
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 Orientation22
0 数据胃口信号（0 类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
盈余=中等，2 个近期外部信号 — 超出已货币化范围的专有数据
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 Audit100
✓ 良好目标 — 这家总部位于英国的货运代理和物流公司成立于 2007 年，似乎是理想的目标，因为其核心业务是运营物流，这会产生有价值的副产品数据，而且没有任何迹象表明他们目前正在出售这些数据。
- Deep Qualification80
⚠ 需要审查 — 目标是物流服务提供商，而不是数据销售商。“监管记录数据集”是其全球食品/饮料物流核心业务的合理副产品，涉及广泛的合规和海关文件。然而，这些数据归其客户所有，并受 GDPR 和其他限制的约束，没有发现数据策略发生变化的具体触发因素。[数据归公司客户所有]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该公司从海运、空运和陆运货物的实时跟踪中生成时间序列数据，为物流和保险平台提供有价值的物理地面真相。
Transaction data
这些证据表明持有者处理高频电子商务交易，创建了有价值的关于订单履行和交付模式的表格数据，用于需求预测。
Regulatory records
持有者拥有一个专有的、结构化的文本数据集，该数据集源自其清关服务，包含诸如商品代码和税收估值等关键字段，这些字段对于训练合规人工智能至关重要。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Supplychainsolution Regulatory Records — a Moderate regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global Artificial Intelligence in Supply Chain market = $5.1B in 2023, CAGR 38.9% (source: Grand View Research). [1, 5]. Investment score 64.4/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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