Dataset opportunity
Epostglobalshipping — 交易数据集机会
Epostglobalshipping 持有的海量交易数据集，可用于推荐模型和欺诈检测。
Score
63.8
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
56%
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)
全球物流和供应链人工智能市场 = 2024 年为 201 亿美元，复合年增长率为 25.9%（来源：Precedence Research）。[1, 7]
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.
- 📣Press / announcement
被 JZ Partners 和 Edgewater Capital 收购以扩展技术驱动的物流
source ↗
Profile
Dataset profile
Type
交易数据集
Modality
表格
Sector
移动
Volume
大
Freshness
定期
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
电子商务与个性化人工智能团队
Epostglobalshipping 持有一个大规模的表格 交易数据数据集，其中包含丰富的地理数据和专有的知识库。这些数据汇集了来自 100 多家第三方承运商的信息，提供了对移动模式的罕见、全面的视图，因此特别适合训练用于物流优化的先进推荐模型。
物流人工智能市场在 2024 年的价值为201 亿美元，预计将以25.9% 的复合年增长率增长，这表明巨大的商业价值和需求。[1, 7] 尽管存在数据访问复杂性，例如数据包含需要匿名化的个人身份信息 (PII)，以及专有的编排层，并且需要获得其私募股权所有者的高级别公司批准，但该汇集数据集的稀有性和规模在快速扩张的市场中提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据包含需要匿名化的 PII（姓名、地址）以用于人工智能用例；专有的编排层汇集了来自 100 多家第三方承运商的数据；由私募股权（JZ Partners/Edgewater）拥有，可能需要高层公司批准。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据表明 Epostglobalshipping 持有一个专有的、高稀有性的数据集，包含在 200 多个国家/地区的2330 万实际国际货运结果。这些细粒度的交易级数据对于希望构建复杂的航运和物流推荐模型的电子商务人工智能团队来说是关键资产。在全球人工智能物流市场预计到 2024 年将达到201 亿美元的情况下，该数据集提供了一个独特的机会，可以大规模地优化承运商绩效、预测交货时间并提升客户体验。
See dimension details ↓- Dataset Specificity78
主导的“交易数据”，行业移动，2 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 Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume74
4 条证据命中，明确提及数据量
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness46
定期
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
适用于推荐模型
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
人工智能买家需求极高，这得益于全球物流人工智能市场的快速扩张，该市场价值 201 亿美元，复合年增长率为 25.9%。[1, 7]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/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
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 Strength74
4 种证据类型，4 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 Orientation39
1 个数据需求信号（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 — 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 — 这是一个好目标；它是一家私营的、运营中的物流/航运公司，作为其核心业务的副产品生成有价值的交易数据，并且似乎不将数据作为产品出售。问题：BBB 和 Reddit 上的一些用户评论表达了对客户服务和包裹跟踪的沮丧，这表明可能存在运营效率低下。 [21, 22]；Scam Detector 给该网站的中等信任评分为 52.8/100，并引用了缺乏元数据和糟糕的设计
- Deep Qualification90
✓ 通过 — ePost Global 是一家物流服务提供商，而非数据销售商。它持有有价值的、汇集而成的交易数据集，作为其核心业务的副产品，但这些数据包含 PII，并且受到复杂的用法权和隐私法规的约束，使得直接访问以进行人工智能培训具有挑战性。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Knowledge base / docs
证据表明存在一个专门的知识库，涵盖国际运输的复杂规则，这是训练模型以自动化海关和关税合规性的宝贵资产。
Transaction data
这是核心表格数据集，捕获了跨承运商和目的地的细粒度货运绩效数据，这对于训练物流推荐模型至关重要。
Data-volume signal
这证实了数据集的显著规模，代表了2330 万次货运的完整结果，提供了训练高性能人工智能模型所需全面、无偏见的真实情况。
Geospatial data
这些表格数据证实了数据集广泛的全球覆盖范围，涵盖了 200 多个国家的专有物流网络，这对于建模和优化国际供应链至关重要。
Marketplace
Dataset details
Geographic coverage
Global (200+ countries)
Time range
Actual international shipment outcomes (specific years not stated, but implied historical)
Update frequency
Periodic
Delivery
API or secure file transfer (inferred due to PII and propr
Formats
Tabular
License
One-time license for use in recommendation models for logistics optimization, subject to PII anonymization and proprietary orchestration.
Personal data
Contains PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's high rarity, large volume of granular international shipment outcomes, and direct applicability to the rapidly growing AI in logistics market drive its significant valuation. Demand is high for training recommendation models in this sector.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Epostglobalshipping Transaction — a Large transaction dataset (Tabular modality) in the mobility domain. Primary AI use-case: Recommendation Models. Market signal: Global AI in logistics and supply chain market = $20.1B in 2024, CAGR 25.9% (source: Precedence Research). [1, 7]. Investment score 63.8/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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