Dataset opportunity
Makotsl — 交易数据集机会
Makotsl 持有的中等交易数据集，可用于推荐模型和欺诈检测。
Score
61.4
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)
全球交通运输分析市场 = 2024 年为 126 亿美元，复合年增长率为 23.8%。
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.
- ✨Signal
报告 2025 年已执行的运输关系 195,803 次
source ↗
Profile
Dataset profile
Type
交易数据集
Modality
表格
Sector
出行
Volume
中等
Freshness
定期
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
电子商务和个性化 AI 团队
Makotsl 提供源自其出行运营的表格 交易数据集，整合了来自 1,000 多辆签约承运商车辆的业务记录、地理数据和交易信息。这种丰富的真实运营数据组合旨在构建和训练高级推荐模型，从而优化客户-承运商匹配、动态定价和路线效率。
该数据的商业价值体现在交通运输分析市场，该市场在 2024 年的估值为126 亿美元，预计将以 23.8% 的复合年增长率增长。[1] 尽管存在数据所有权共享和需要匿名化电子合同文件中的个人身份信息等访问复杂性，但该数据集的稀有性和高商业敏感性使其成为寻求在物流领域获得显著竞争优势的 AI 买家的宝贵资产。⚠ 尽职调查（有价值的数据，可协商访问）：数据所有权与签约承运商共享（1000 多辆车不完全拥有）；电子合同文件包含个人身份信息（姓名、签名、地址），需要匿名化；关于路线定价和客户-承运商匹配的商业敏感性高 · 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 Makotsl 拥有一个大规模的专有交易数据集，详细记录了横跨西欧的 195,000 多条物流路线。对于电子商务和个性化 AI 团队而言，这些数据是训练高级推荐模型和优化复杂供应链的稀有资产。在交通运输分析市场预计每年增长近 24% 的情况下，这些真实的出行模式的详细记录为理解和预测物流需求提供了独特的竞争优势。
See dimension details ↓- Data Orientation39
1 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…). - Dataset Specificity78
主导的“交易数据”，行业出行，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 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 Freshness46
定期
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
适合推荐模型
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI 买家需求异常高，这得益于交通运输分析市场的快速增长，该市场正以 23.8% 的复合年增长率扩张。[1]
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
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 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. - 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 Audit100
✓ 良好目标 — Makotsl 是一家波兰的物流和货运代理中小型企业，作为其核心业务的副产品，它产生了大量的专有运营数据（路线、车辆远程信息处理、交易详情），使其成为一个尚未在外部货币化此数据的完美目标。[1, 2, 9]
- Deep Qualification90
✓ 通过 — Makotsl 是一家货运代理公司，其管理 1,000 多辆签约车辆的运营活动产生了一个有价值的交易和遥测数据集。然而，数据所有权与承运商共享，并且数据包含来自电子合同文件的敏感个人身份信息，在使用前需要仔细匿名化。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
business_records
这些证据表明该公司在欧洲各地为每个订单生成大量物流文件，这些文件正在进行数字化和自动化。
Transaction data
这些表格数据量化了公司的运营规模，详细记录了集中在德国和西欧的 195,000 多条已完成路线，为预测建模提供了丰富的来源。
Geospatial data
这些数据具体说明了车队的构成，包括超过 1,000 辆签约车辆以及波兰最大的货车车队，为供应链分析增加了关键的资产级别详细信息。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Makotsl Transaction — a Moderate transaction dataset (Tabular modality) in the mobility domain. Primary AI use-case: Recommendation Models. Market signal: Global Transportation Analytics Market = $12.6 billion in 2024, CAGR 23.8% (source: Grand View Research). [1]. Investment score 61.4/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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