Dataset opportunity
Pauatech — 移动遥测数据集机会
Pauatech 持有的中等移动遥测数据集，可用于预测性维护和异常检测。
Score
45
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)
全球汽车预测性维护市场 = 2023 年为 220 亿美元，复合年增长率为 18.6%（来源：Market.us）
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.
- 🤝Data partnership
与英国超过 20 个充电网络集成
source ↗
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
聚合/第三方 — 需明确许可权 · PII/受监管
Buyer persona
工业人工智能与维护优化供应商
Pauatech 持有一个宝贵的出行遥测数据集，该数据集结构为时间序列，整合了来自电动汽车充电点的 geo_data、iot_data 和 transaction_data。这些精细的、真实的运营数据特别适合开发和训练预测性维护算法，通过分析使用模式和组件压力，能够预测硬件故障并优化网络正常运行时间。
全球汽车预测性维护市场在 2023 年的价值为220 亿美元，预计将以18.6% 的复合年增长率增长。[1] 尽管存在数据访问复杂性，例如来自多个 CPO 的数据聚合以及与车队客户的共同所有权，但该数据集代表了一个重要的机会。其价值因包含大量未货币化的原始行为数据而得到提升，这是寻求在快速扩张的市场中获得竞争优势的 AI 买家的一项稀有资产。[1] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据来自多个第三方充电点运营商 (CPO)。; 精细的充电遥测数据的所有权可能与车队客户共享。; 主要业务是漫游/支付解决方案，原始行为数据大部分未货币化。 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明了 Pauatech 拥有一个专有数据集，该数据集详细记录了来自超过 43,000 个电动汽车充电连接器的真实运营遥测数据。丰富的时间序列和交易数据是工业 AI 供应商开发预测性维护模型以预测硬件故障和优化正常运行时间的关键资产。在一个迅速转向电气化的市场中，该数据集为创建面向车队运营商和供应商的复杂维护优化解决方案提供了独特的竞争优势。
See dimension details ↓- Dataset Volume52
3 条证据
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
AI 买家需求异常高，这得益于在预测将以强劲的**18.6% 复合年增长率**增长的市场中对训练数据的迫切需求。[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 条证据
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License18
所有权=聚合，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 — 专有数据超出已货币化部分
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. - Dataset Specificity90
占主导地位的 'iot_data'，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. - ICP Audit50
⚠ 审查 — Paua Tech 的核心业务是销售用于电动汽车车队充电管理的软件平台和 API，这是一种销售智能的形式，因此不适合。问题：公司的核心产品是用于管理和支付电动汽车充电的技术平台 (SaaS) 和 API，而不是非数据业务的副产品。[3, 9, 11]; 该公司的业务模式是从第三方充电点运营商那里聚合数据，并为车队经理提供软件/智能。[6, 9, 11]; 他们明确通过 API 出售其数据访问权限，作为集成到车队和金融系统的产品。[3, 17]; 该公司是一家技术/软件供应商，该类别明确排除在 ICP 之外。[14]
- Deep Qualification90
✓ 通过 — 目标客户拥有一个与其核心业务副产品一致且有价值的数据集，但数据所有权混合且许可受 GDPR 限制，对直接货币化构成重大障碍。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该数据集包含精细的时间序列遥测数据，包括能耗、持续时间和连接器级别的事件，这对于训练 AI 模型以预测组件故障和优化充电基础设施至关重要。
Geospatial data
它包含表格地理空间数据，识别高需求充电中心和使用模式，从而能够根据真实车队行为进行战略资源规划和网络优化。
Transaction data
该数据集提供了统一的交易数据，反映了不同车队类型的经济活动，从而能够计算预测性维护干预措施的财务影响和投资回报率。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Pauatech Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global automotive predictive maintenance market = $22 billion in 2023, CAGR 18.6% (source: Market.us). Investment score 45.0/100 (confidence 0.49). Recommended action: Acquire.
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