Dataset opportunity
Weeve — 维护日志数据集机会
Weeve 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
73.5
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)
全球汽车预测性维护市场 = 2023 年为 13 亿美元，复合年增长率为 23.9%（来源：IMR）
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
维护日志数据集
Modality
时间序列
Sector
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
工业人工智能与维护优化供应商
Weeve 持有一个结构为时间序列的维护日志数据集，其中整合了详细的地理数据、物联网数据和明确的维护日志。这种远程信息处理和维修记录的多模态组合提供了训练强大的预测性维护模型所需的特征，从而能够准确预测车辆组件在发生故障前的失效情况。
全球汽车预测性维护市场在 2023 年的估值为13 亿美元，预计将以惊人的 23.9% 的复合年增长率增长。[5] 这一显著的市场增长凸显了像 Weeve 这样全面数据集的高价值和稀缺性。虽然由于远程信息处理数据中包含敏感的个人身份信息 (PII) 以及可能与 Uber 的合作协议，访问权限需经协商，但该数据集的丰富性为旨在引领这一快速扩张的 AI 应用领域的买家提供了独特的优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：远程信息处理数据包含敏感的驾驶员位置和行为 PII；数据访问可能受 Uber 合作协议的约束；特定行程数据的归属可能与驾驶员或 Uber 共享 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明 Weeve 持有一个专有的维护日志和高里程商用电动汽车车队的运营数据。这种独特的时间序列数据非常适合训练预测性维护算法，这是 AI 供应商针对汽车行业的关键应用。在一个预计年增长率超过 23% 的市场中，该数据集为开发和验证优化车队正常运行时间并降低特斯拉车辆在真实专业驾驶条件下的运营成本的模型提供了难得的机会。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，出行行业，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. - 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 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 Demand95
AI 买家需求极高，这得益于汽车预测性维护市场的爆炸式增长，该市场正以 23.9% 的复合年增长率扩张。[5]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility20
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility30
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 License62
所有权=已拥有，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 Orientation56
2 个数据需求信号（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，5 个近期外部信号 — 超出已货币化数据的专有数据
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 — 该公司的核心业务是将其自有电动汽车车队出租给专业驾驶员，这产生了专有的维护和遥测数据，作为目前未出售的有价值的副产品。问题：公司名称“Weeve”与其他不相关的科技公司（例如 Weave、WeeveAI）相似，需要仔细验证域名（weeve.ca）。；该公司最近推出了名为“Avigo”的汽车共享子公司，但核心业务仍然是车队租赁。[1
- Deep Qualification90
⚠ 需要审查 — Weeve 是数据持有者，而非销售商。其将电动汽车出租给网约车驾驶员并提供全包维护服务的业务，使得存在有价值的“维护日志数据集”的可能性极高。然而，由于敏感的驾驶员 PII 和集成，数据访问复杂且受限 [许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>A claim is circulating that stops you mid-scroll: a California small fleet can now buy a Tesla Semi for as little as $50,000. The Tesla Semi carries a $290,000 sticker. The post lays out how two California incentive programs stack to knock $240,000 off that price, leaving a net cost of roughly $50,000, which it […]</p> <p>The post <a href="https://www.freightwaves.com/news/a-290000-tesla-semi-for-50000-californias-incentive-stack-is-real-but-the-number-hides-as-much-as-it-reveals">A $290,000 Tesla Semi for $50,000?? California’s Incentive Stack Is Real, but the Number Hides as M”
- “Avec une politique de prix plus offensive, le retour du leasing social et une future Corsa électrique annoncée autour de 25 000 euros, Opel veut redevenir la marque de référence des généralistes accessibles. Une stratégie qui doit permettre au constructeur allemand de reprendre des parts de marché en France.”
- “Comptant parmi les leaders de la recharge ultrarapide en France, Electra détaille ses performances 2025 et ses ambitions européennes. L’opérateur mise sur une application unifiée, une tarification plus lisible et une forte expansion de son réseau pour s’imposer comme une plateforme incontournable de la mobilité électrique.”
IoT / sensor data
这些证据表明存在持续的远程信息处理数据流，包括来自商用特斯拉车队的电池和性能指标，这对于构建将实际使用与组件健康状况联系起来的模型至关重要。
Geospatial data
这表明存在表格形式的位置数据，详细说明了高密度城市驾驶周期，使 AI 模型能够将地理和交通模式与车辆磨损相关联。
Maintenance logs
这证实了核心资产的存在：时间序列维护日志，记录了组件的磨损，提供了训练和验证高利用率电动汽车预测性故障算法所需的关键真实数据。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for predictive maintenance model training and deployment within the automotive sector. Usage subject to negotiation.
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 value is driven by its high rarity as proprietary, multi-modal time-series data from a commercial EV fleet, crucial for predictive maintenance. The strong market demand, evidenced by the $1.3B global automotive predictive maintenance market with a 23.9% CAGR, supports a premium valuation.
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Weeve Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Automotive Predictive Maintenance Market = $1.3 Billion in 2023, CAGR 23.9% (source: IMR). Investment score 73.5/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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