Dataset opportunity
Odwlogistics — 可下载数据资产机会
Odwlogistics 持有的可下载大型数据资产，可用于微调和预训练。
Score
75.9
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
76%
Action
Acquire
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在 2026 年的价值为 189 亿美元，预计到 2036 年将达到 827 亿美元，复合年增长率为 15.9%。
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
可下载数据资产
Modality
表格
Sector
mobility
Volume
Large
Freshness
Real-time
Rarity
高（专有）
Accessibility
Restricted
Legal
混合所有权 — 需明确许可权 · PII/受监管
Buyer persona
Domain LLM builders & vertical AI startups
Odwlogistics 持有一个有价值的表格数据集，非常适合用于高级人工智能模型的微调，其中包含来自其自动化仓库的交易数据、货运地理数据以及专有的物联网数据的丰富组合。这提供了对供应链运营的全面、多方面视图，从仓库楼层遥测到最终交付，为物流优化提供了稀有的知识库。
全球供应链人工智能市场在 2026 年的价值为189 亿美元，预计到 2036 年将以15.9% 的复合年增长率增长，这凸显了该数据的巨大商业价值。虽然访问需要处理客户保密协议和第三方物流服务水平协议，但独特、专有的运营数据使此可下载数据资产成为在快速增长的市场中建立竞争优势的战略资源。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权与零售和制造客户（例如 Walmart、Target）共享。; 专有仓库自动化运营遥测数据可能完全归 ODW 所有。; 访问需要处理第三方物流服务水平协议和客户保密协议。· 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 Odwlogistics 拥有专有的、多模态的数据集，捕获了真实的供应链运营，从仓库机器人和劳动力管理到主要零售商的货运整合。这种高稀有度的数据非常适合微调特定领域的 LLM，为目标是快速增长的供应链人工智能市场的 AI 初创公司提供显著的竞争优势，该市场预计到 2036 年将达到 827 亿美元。该数据集提供了构建模型所需的地面实况，这些模型可以优化装载计划、路由和零售合规性。
See dimension details ↓- Dataset Specificity100
主导的“下载”，行业 mobility，4 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（开放会降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume88
9 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
适用于微调
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，这得益于市场快速增长（15.9% 的复合年增长率），因为公司越来越多地利用物流数据进行预测分析和运营优化。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility22
开放/API 访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility48
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 Strength100
6 种证据类型，9 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 Orientation22
0 个数据胃口信号（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 Audit75
✓ 良好目标 — ODW Logistics 是一家大型私营第三方物流公司，其核心业务是运营物流，使其产生的海量运营数据成为潜在的强大资产。问题：该公司比典型中小企业规模更大，拥有 1,000 多名员工和可观的收入，这可能会影响互动方式。[1, 2, 7]; 他们拥有内部的“数据与分析”部门，并推广其技术平台“ODW INSIGHT”作为关键功能，这表明他们对数据有意识，尽管如此；该公司正在积极投资技术和自动化，这可能意味着他们即将自行产品化其数据。[6, 13]
- Deep Qualification80
✓ 通过 — ODW Logistics 是典型的第三方物流数据持有者，其运营数据是其服务的合理副产品。然而，与第三方物流行业标准一样，代表 Walmart 和 Target 等客户生成的数据很可能归他们所有，这使得数据访问和转售权成为主要挑战。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
该公司提供可下载的表格资产，包括提供关于第三方物流提供商选择和物流原则的结构化、专家级文本的综合指南。
Knowledge base / docs
Odwlogistics 维护着一个专有的知识库，详细介绍了供应链优化策略，为培训提供了丰富的领域特定语言和概念语料库。
IoT / sensor data
该数据集包括从仓库内的自主机器人和数字孪生平台捕获的实时时间序列数据，提供了细致的运营洞察。
Transaction data
该公司作为 Walmart 和 Target 等主要大众零售商的批准货运整合商，产生了交易数据，代表了高价值的商业活动。
Industrial data
该资产包含工业数据流，整合了来自劳动力管理系统、仓库管理系统 (WMS) 和机器人技术的信息，以跟踪运营绩效。
Geospatial data
该数据集包含来自运输管理系统 (TMS) 的地理空间和物流信息，用于优化装载计划、路由和承运商选择。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Odwlogistics Downloadable Data — a Large downloadable data asset (Tabular modality) in the mobility domain. Primary AI use-case: Fine Tuning. Market signal: Global Artificial Intelligence in Supply Chain market is valued at $18.9 billion in 2026, projected to reach $82.7 billion by 2036, at a 15.9% CAGR (source: Fact.MR). Investment score 75.9/100 (confidence 0.76). Recommended action: Acquire.
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