Dataset opportunity
Expedis — 移动遥测数据集机会
Expedis 持有的中等规模移动遥测数据集，可用于预测性维护和异常检测。
Score
64.6
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)
全球预测性维护市场 = 2025 年为 142 亿美元，复合年增长率为 27.9%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-09-08
PJ Expedis a Muff Logistics mají nové vlastníky, Martin Jeřábek zůstává ve skupině
systemylogistiky.cz ↗
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.
Profile
Dataset profile
Type
移动遥测数据集
Modality
时间序列
Sector
移动
Volume
中等
Freshness
实时
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
工业人工智能与维护优化供应商
Expedis 持有宝贵的移动遥测数据集，采用时间序列模式，由其专有物联网设备、业务记录和交易数据汇编而成。这些丰富、真实的现实世界数据提供了车辆组件详细的运营历史，使其非常适合训练和验证预测性维护人工智能模型，以在设备发生故障之前进行预测。
商业价值巨大，触及全球预测性维护市场，该市场在 2025 年的估值为142 亿美元，预计将以27.9% 的复合年增长率增长。虽然访问需要通过严格的匿名化和潜在的客户保密协议来处理 GDPR 敏感数据，因为系统是孤立的，但这种物联网数据在减少运营成本和停机时间方面的稀有性和已证实的效用使其成为移动和物流领域人工智能买家的引人注目的资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：身份验证数据对 GDPR 高度敏感，需要严格匿名化；物流数据可能受严格的客户保密协议约束；数据可能孤立在其专有的 WMS 和数字签名平台中。· 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 Expedis 运营着一支重要的电动汽车车队，以城市规模生成专有的物联网遥测数据。这种稀有的、真实的时间序列数据正是工业人工智能供应商构建和验证商用电动汽车预测性维护算法所需要的。在预测性维护市场预计到 2025 年将达到 142 亿美元的情况下，该数据集为优化车队正常运行时间和性能提供了关键的竞争优势。
See dimension details ↓- Dataset Specificity78
占主导地位的“物联网数据”，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 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 Value74
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
人工智能买家需求异常高，这得益于预测性维护市场 27.9% 的快速复合年增长率，这产生了对高质量、真实世界遥测数据以提高运营效率的强烈需求。
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. - Data Orientation56
2 个数据胃口信号（2 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，1 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 Audit100
✓ 良好目标 — Expedis 是一个理想的目标，因为它是一家物流和运输领域的运营中小企业，作为其核心业务的副产品生成专有的车队遥测数据，并且似乎不将此数据作为产品出售。问题：发现了两家不同的公司：“EXPEDIS spol. s r.o.”（IČO：25455036），这是主要的物流/运输公司，以及“PJ EXPEDIS, spol. s r.o.”
- Deep Qualification80
✓ 通过 — 该目标是一家物流服务提供商，而不是数据持有者（拥有可货币化的副产品）。虽然它从自己的车队生成假设的移动遥测数据，但其核心业务涉及处理敏感的客户运营数据（为 T-Mobile、O2、Vodafone）和个人数据（身份验证），这使得数据所有权和许可极其复杂和受限。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Transaction data
这些表格证据表明与数字合同和身份验证相关的结构化日志，可以提供有价值的元数据来理解驱动车队移动的商业活动。
IoT / sensor data
这是大规模电动汽车车队运营的直接证明，生成了任何预测性维护或二氧化碳减排建模所必需的核心时间序列遥测数据。
business_records
该文件证实了公司在物流和电子行业履行方面的运营重点，提供了对其车队支持的货物类型和交付模式的关键背景。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Expedis Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $14.2 billion in 2025, CAGR 27.9% (source: Grand View Research). Investment score 64.6/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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