Dataset opportunity
Agilenville — 移动遥测数据集商机
由 Agilenville 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
75.4
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
56%
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
全球车辆预测性维护市场：2024 年为 46.6 亿美元，预计到 2034 年将达到 233.9 亿美元，复合年增长率 17.5%（来源：Global Market Insights Inc.）
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-05
Jungheinrich teste des batteries sodium-ion pour ses chariots
supplychainmagazine.fr ↗ - 📰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 ↗
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
移动出行
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — GDPR敏感（PII审查）
Buyer persona
工业人工智能和维护优化供应商
Agilenville 拥有丰富的移动遥测数据集，采用时间序列模式，包含地理数据、工业数据、物联网数据和交易数据。这份综合数据提供了关于车辆性能、运行状况和配送物流的精细洞察，使其非常适合开发先进的预测性维护AI模型。通过分析这些多样化的数据流，可以预测潜在的设备故障，从而实现主动干预并优化资产寿命。
移动出行领域的预测性维护市场正在经历显著增长，全球车辆预测性维护市场在2024年估值为46.6亿美元，预计到2034年将达到233.9亿美元，显示出17.5%的强劲复合年增长率（CAGR）。尽管由于与配送相关的个人信息以及需要尊重B2B运营中的客户数据权利而存在GDPR合规性的复杂性，该数据集仍然异常有价值且稀有。其详细遥测数据和交易数据的独特组合为寻求提高移动出行领域运营效率和减少停机时间的AI买家提供了竞争优势。⚠ 尽职调查（有价值的数据，可协商访问）：数据包含与配送相关的个人信息（姓名、地址），需要符合GDPR规定；数据来源于B2B客户配送，需要仔细考虑客户数据权利和协议。· 企业：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Agilenville 明确拥有专有的移动遥测数据集，其证据来自其庞大的货运自行车车队所产生的复杂地理定位和物联网传感器数据。这种丰富的时间序列数据，结合运营指标和专业的冷链监控，为车辆性能和资产健康提供了无与伦比的洞察。对于工业AI和维护优化供应商而言，该数据集对于开发先进的预测性维护解决方案至关重要，直接面向一个预计到2034年将达到233.9亿美元的全球市场，并立即提供显著的竞争优势。
See dimension details ↓- Dataset Specificity100
主导的“物联网数据”，移动出行领域，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 Rarity94
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume58
4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 Value94
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 Demand90
全球汽车预测性维护市场广泛利用移动遥测数据进行AI驱动的解决方案，预计从2023年到2032年将以18.6%的复合年增长率增长，到2032年将达到约1000亿美元。
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 Strength74
4种证据类型，4个命中
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 Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation61
3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 — 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 — Agilenville 是一家城市物流中小企业，运营着一支货运自行车和电动汽车车队，每月完成超过18,000次配送，很可能在核心配送服务过程中收集到有价值的移动出行和遥测数据，而这些数据目前尚未出售。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
这份表格数据证实了Agilenville精确地理定位其货运自行车的能力，为物流优化和车队管理解决方案提供了重要的路线和位置智能。
IoT / sensor data
这份数据的时间序列性质证实了Agilenville联网货运自行车的实时遥测数据，为预测性维护和性能分析提供了关键的运营洞察。
Transaction data
这份表格证据详细说明了Agilenville显著的运营规模，包括配送量和行驶里程，这对于将车辆使用情况与维护需求和效率模型相关联至关重要。
Industrial data
这份时间序列数据证实了Agilenville在冷链物流方面的专业知识，表明其收集了对监控专业设备健康至关重要的环境传感器数据，并为温度敏感资产实现了预测性维护。
Marketplace
Dataset details
Geographic coverage
Agilenville
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for internal use in developing predictive maintenance AI models.
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 proprietary, high-rarity mobility telemetry dataset offers granular insights into vehicle performance and logistics, driving significant value for predictive maintenance AI. The rapidly growing global market for predictive maintenance in mobility, projected to exceed $23 billion by 2034, underscores strong demand.
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
Agilenville 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 for Vehicles Market = $4.66 billion in 2024, projected to reach $23.39 billion by 2034, CAGR 17.5% (source: Global Market Insights Inc.). Investment score 75.4/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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