Dataset opportunity
Foodcareplus — 法规记录数据集机会
由 Foodcareplus 持有的中等规模法规记录数据集，可用于法规 RAG 和合规 Copilots。
Score
67.4
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
合作（集团层面）
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
全球食品物流市场规模在 2024 年的估值为 1389.3 亿美元，预计从 2025 年到 2032 年的复合年增长率为 8.3%（来源：Maximize Market Research）。[5]
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
法规记录数据集
Modality
文本
Sector
mobility
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待澄清
Buyer persona
RegTech 和合规 AI 供应商
Foodcareplus 持有一个文本模态的法规记录数据集，以 `event_streams`、`iot_data` 和 `regulatory` 文件为证。这些数据提供了食品货物运输、条件和合规性检查的详细、可审计的记录，使其非常适合法规 RAG 用例，允许人工智能直接从源文档中检索复杂合规性和后勤查询的精确、上下文感知答案。
全球食品物流市场的价值凸显了这一点，该市场在2024 年的估值为 1389.3 亿美元，预计将以8.3% 的复合年增长率增长。[5] 尽管这个有价值的数据集包含敏感的商业信息，并且访问需要处理共享数据所有权和 Remant Group 的治理，但其稀有性和直接适用于高风险法规自动化使其对成熟的 AI 买家来说，谈判是值得的。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权在货主、承运商和 Foodcareplus 之间共享；Remant Group 的子公司，可能需要集团层面的数据治理批准；包含有关食品供应链定价和路线的敏感商业信息 · 公司：Remant Group 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Foodcareplus 持有国际食品法规、兽医证书和海关清关模式的专有数据集。对于寻求构建复杂的法规 RAG 系统的 RegTech 和合规 AI 供应商来说，这是一个高价值资产。在全球食品物流市场预计以 8.3% 的复合年增长率增长的情况下，该数据集提供了自动化合规和应对日益复杂的国际贸易环境所需的基本、高稀有度知识库。
See dimension details ↓- Dataset Specificity90
主导的“法规”，行业 mobility，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
适用于法规 RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI 买家对专业物流数据需求旺盛，这得益于在价值 1389.3 亿美元的食品物流市场（复合年增长率 8.3%）中对效率和合规性的需求。（[5]）
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 Feasibility15
中等难度，Remant Group 的子公司
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 Independence50
Remant Group 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 个数据需求信号（0 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 — 专有数据超出已货币化的部分
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 — Foodcareplus 是一个良好的目标，因为它是一家面向食品行业的中小型物流服务提供商，其核心业务是实体货运代理，而不是销售数据，从而产生了有价值的法规、海关和冷链数据副产品。问题：该公司提到使用“最先进的动态仪表板”以及利用“我们捕获的大量数据和指标来设计最高性能的供应链。
- Deep Qualification80
✓ 通过 — Foodcareplus 是一家物流服务提供商，而不是数据销售商，其管理受管制食品运输的业务使得“法规记录数据集”的存在是合理的。然而，数据与客户和合作伙伴的数据混合在一起，带来了重大的所有权和许可复杂性。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该公司为其易腐品的温控物流生成连续的时间序列传感器数据，为食品安全和质量保证提供了关键记录。
Event streams
该数据集包含实时和历史事件流，详细说明了全球食品运输路线和港口拥堵，为供应链优化和风险管理提供了关键情报。
Regulatory records
持有者拥有大量的基于文本的国际食品法规、兽医证书和海关文件集合，构成了自动化复杂合规任务的专有知识库。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Foodcareplus Regulatory Records — a Moderate regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global Food Logistics Market size was valued at USD 138.93 Billion in 2024 and is expected to grow at a CAGR of 8.3% from 2025 to 2032 (source: Maximize Market Research). [5]. Investment score 67.4/100 (confidence 0.49). Recommended action: Partnership (group-level).
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