Dataset opportunity
Logsytech — 移动遥测数据集商机
Logsytech 持有的大型移动遥测数据集，可用于预测性维护和异常检测。
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
70%
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
全球预测性维护市场 = 2025 年为 USD 14.29 billion，预计到 2033 年将达到 USD 98.16 billion，复合年增长率为 27.9% (2026-2033)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
3 logistics upgrades benefiting Wayfair
supplychaindive.com ↗ - 📰press2026-06-04
Amazon wants sellers to be more precise with handling times
supplychaindive.com ↗ - 📰press2026-06-04
Motul regroupe sa logistique avec FM Logistic à Nangis (77)
supplychainmagazine.fr ↗ - 📰press2026-06-04
Argan a livré 18.000 m² pour Nortene Home Depot à Louailles
supplychainmagazine.fr ↗ - 📰press2026-06-04
Pilgrim’s palettise en froid avec Promalyon à Hénin-Beaumont
supplychainmagazine.fr ↗
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
移动遥测数据集
Modality
时间序列
Sector
移动出行
Volume
大
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — GDPR 敏感（PII 审查）
Buyer persona
工业人工智能与维护优化供应商
Logsytech 拥有丰富的移动遥测数据集，这是一个关键的时间序列集合，涵盖了 API、事件流、地理数据、工业数据、物联网数据和交易数据。这些细粒度数据提供了车辆性能和运营模式的实时洞察，通过预测设备故障和优化运营效率，使其对预测性维护应用具有极高的价值。
此类数据在移动出行领域的商业价值巨大，全球预测性维护市场规模预计在 2025 年达到 142.9 亿美元，并预计到 2033 年达到 981.6 亿美元，2026 年至 2033 年的复合年增长率 (CAGR) 为 27.9%。尽管存在一些复杂性，例如作为 D Groupe 的子公司需要协调数据许可，由于 B2C 物流涉及处理 GDPR 敏感的个人数据，以及潜在的数据所有权可能受客户协议约束，但 AI 买家对此类数据的高需求使其访问具有极高价值并值得谈判。⚠ 尽职调查（有价值的数据，可协商的访问权限）：D Groupe 的子公司，需要与母公司协调数据许可；由于 B2C 物流运营，处理 GDPR 敏感的个人数据；某些数据集的数据所有权可能受特定客户协议约束。· 公司：D Groupe 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Logsytech 拥有高度专有且广泛的移动遥测数据集，这体现在其庞大的工业运营、每年 400 万次的出货量管理以及复杂的物联网基础设施。这种丰富的时间序列数据，涵盖工业资产、物流和地理空间移动，在应对蓬勃发展的预测性维护市场方面具有独特的优势。对于工业 AI 和维护优化供应商而言，该数据集提供了无与伦比的洞察力，可用于开发高级模型，从而提高效率并减少停机时间，预计到 2033 年，该市场将达到近 1000 亿美元。
See dimension details ↓- Dataset Rarity100
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Specificity100
主导的“物联网数据”，移动出行领域，5 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 Volume70
6 项证据命中
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 Value100
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
严重依赖移动遥测数据的 AI 驱动预测性维护市场，预计在 2025 年至 2032 年间将以 39.5% 的复合年增长率 (CAGR) 增长，表明来自 A 的需求非常高且快速增长
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
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 Feasibility0
中等难度，D Groupe 的子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength98
6 种证据类型，6 项命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License62
所有权=自有，许可=GDPR 敏感
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
D Groupe 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 个数据需求信号（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，5 个近期外部信号 — 超出已货币化的专有数据
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 — Logsytech 是一家拥有 160 名员工和 2000 万欧元营业额的物流公司，其供应链活动产生了大量的运营数据，这些数据用于内部和客户服务，但并非作为核心产品出售。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
Logsytech 与工业和电信/物联网领域的合作证实了其物联网数据的收集，这是监控互联设备和实现预测性维护解决方案的关键组成部分。
API access
强大的 API 和连接器能力的存在，展示了 Logsytech 先进的技术基础设施，确保了 AI 应用高效的数据集成和交换。
Transaction data
处理 B2C 和 B2B 业务中每年 400 万次出货量的证据，突显了可用的移动出行交易数据的巨大规模，为物流和资产性能提供了丰富的背景信息。
Industrial data
Logsytech 运营 7 个仓库和专有的 WMS/ERP 系统，证实了其在工业物流领域的深度参与，产生了对运营优化至关重要的有价值的时间序列工业数据。
Geospatial data
与 18 家国内和国际承运商的合作以及拥有车队，表明了广泛的地理空间数据收集，这对于理解移动模式和分布式资产管理至关重要。
Event streams
其呼叫中心处理每天 3,000 次通话，表明了持续的运营事件数据流，为与遥测数据关联和增强预测模型提供了有价值的信号。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API, Event Streams
Formats
API, Event Streams, Time Series
License
One-time license for internal predictive maintenance use, with restrictions on redistribution and resale.
Personal data
No 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 value is driven by its proprietary nature, real-time freshness, and direct application to the rapidly growing predictive maintenance market in mobility. The substantial projected market growth indicates strong demand for such granular operational insights.
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
Logsytech Mobility Telemetry — a Large mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = USD 14.29 billion in 2025, projected to reach USD 98.16 billion by 2033, with a CAGR of 27.9% (2026-2033). Investment score 75.9/100 (confidence 0.7). Recommended action: Data Sharing Agreement.
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