Dataset opportunity
Lufapak — 工业运营数据集机会
Lufapak 持有的中等规模工业运营数据集，可用于工业监控和预测。
Score
65.2
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 size (indicative estimate)
全球供应链分析市场规模在 2022 年估计为 61.2 亿美元，预计复合年增长率为 17.8%（2023-2030 年）（来源：Grand View Research）。[1]
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.
- 🔌Public API
Lufapak REST API 用于实时数据交换
source ↗
Profile
Dataset profile
Type
工业运营数据集
Modality
时间序列
Sector
出行
Volume
中等
Freshness
定期
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 需明确许可权 · PII/受监管
Buyer persona
工业人工智能集成商
Lufapak 拥有一个专有的工业运营数据集，结构为时间序列数据，其中包括其物流运营的地理数据、工业数据和交易数据。这种遥测和交易信息的丰富组合非常适合构建和训练用于工业监控的 AI 模型，从而实现复杂供应链的实时优化和预测性分析。
全球供应链分析市场在 2022 年的价值为 61.2 亿美元，预计到 2030 年将以 17.8% 的复合年增长率增长。[1] 尽管存在已知的访问复杂性——例如将专有运营数据与 GDPR 敏感的客户 PII 分开——但该数据集具有非凡的价值。其详细的跨境贸易流（德国-英国）提供了稀有的市场情报，对于寻求在高增长市场中获得竞争优势的买家来说，访问该数据是一项值得进行的谈判。[1, 8] ⚠ 尽职调查（有价值的数据，可协商访问）：运营数据是专有的，但最终客户 PII 是客户所有且受 GDPR 敏感；数据涉及跨境贸易流（德国-英国），这对市场情报非常有价值；访问需要区分物流遥测和客户特定的订单内容。· 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 Lufapak 拥有一个专有的、高分辨率的数据集，该数据集捕获了欧洲工业物流运营的完整生命周期。对于 AI 集成商而言，这些数据是构建和验证工业监控模型的稀有资产，满足了预计以 17.8% 的复合年增长率增长的全球供应链分析市场。该数据集独特地包含了实时库存指标、承运商绩效和脱欧后的海关数据，为优化供应链效率和弹性提供了强大且及时的信号。
See dimension details ↓- Dataset Specificity90
主导的“工业数据”，行业出行，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 Freshness46
定期
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
适用于工业监控
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI 买家需求旺盛，这得益于数据驱动的供应链优化和工业监控解决方案市场的强劲增长（**复合年增长率为 17.8%**）。[1]
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 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，5 个近期外部信号 — 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 — Lufapak 是一个强有力的目标，因为它是一家成熟的物流和履行服务提供商，其核心业务产生了大量的运营数据作为副产品，并且没有出售数据或情报的迹象。问题：该公司是英国 DK 集团的一部分，这可能会使决策复杂化，但它作为一家独立的德国有限公司运营。
- Deep Qualification90
✓ 通过 — Lufapak 是一家物流服务提供商，而不是数据销售商；它拥有一个有价值的工业运营数据集，这是其核心业务的副产品。[4, 8] 这些数据与假设的机会一致，但其所有权在 Lufapak 和其客户之间混合，并且受 GDPR 管辖。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>L’un se définit comme éditeur de solutions de supply chain planning et de revenue growth management, l’autre comme un spécialiste de l’orchestration des flux supply chain en temps réel (notamment via sa technologie d’OMS, Order Management System) : les éditeurs français Sunstice et Kbrw viennent d’annoncer un partenariat visant à créer une boucle de synchronisation entre […]</p> <p>L'article <a href="https://supplychainmagazine.fr/nl/2026/sunstice-et-kbrw-rapprochent-planification-et-execution-via-leurs-agent-ia/">Sunstice et Kbrw rapprochent planification et exécution via leurs agent”
- “<p>FedEx reported strong quarterly results, driven by growth in package volumes and yields as the company focuses on high-margin logistics business. </p> <p>The post <a href="https://www.freightwaves.com/news/fedex-boost-revenue-behind-premium-parcel-freight-volumes">FedEx boost revenue behind premium parcel, freight volumes</a> appeared first on <a href="https://www.freightwaves.com">FreightWaves</a>.</p>”
- “<p>U.S.-based Americold plants a flag in Canada as part of a rail-maritime cold chain integration with CPKC and DP World.</p> <p>The post <a href="https://www.freightwaves.com/news/rail-ocean-access-backs-new-americold-cold-chain-facility-at-eastern-canada-port">Rail, ocean access backs new Americold cold chain facility at eastern Canada port</a> appeared first on <a href="https://www.freightwaves.com">FreightWaves</a>.</p>”
Transaction data
此表格数据记录了大规模的日常货运活动，为物流优化模型提供了关于承运商绩效和交付时间的关键指标。
Industrial data
此核心时间序列数据提供了对仓库运营的精细、实时视图，从而能够开发用于库存管理和运营效率的预测模型。
Geospatial data
此独特的表格数据集捕获了脱欧后贸易的具体物流挑战，提供了关于海关清关延误和跨境摩擦的宝贵、难以复制的见解。
Marketplace
Dataset details
Geographic coverage
Europe
Time range
Periodic (specific range not provided, assume recent historical to present)
Update frequency
Periodic
Delivery
API or direct export (inferred)
Formats
Time Series
License
One-time license for industrial monitoring and AI model training, with restrictions on PII usage.
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 proprietary, high-volume time-series dataset offers unique insights into industrial logistics operations, crucial for AI-driven industrial monitoring within the rapidly expanding global supply chain analytics market. Its rarity and direct application to a high-growth sector justify a premium valuation.
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
Lufapak Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the mobility domain. Primary AI use-case: Industrial Monitoring. Market signal: Global supply chain analytics market size was estimated at USD 6.12 billion in 2022, projected to grow at a CAGR of 17.8% (2023-2030) (source: Grand View Research). [1]. Investment score 65.2/100 (confidence 0.49). Recommended action: Acquire.
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