Dataset opportunity
A2Dm — 维护日志数据集机会
A2Dm 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
68.2
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)
全球预测性维护市场在 2025 年的估值为 136.5 亿美元，预计复合年增长率为 24.30%。
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.
- ✨Signal
专注于工业自动化和工程办公室 (Bureau d'Études)
source ↗
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
定期
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 许可干净
Buyer persona
工业人工智能与维护优化供应商
A2Dm 持有一个广泛的维护日志数据集，结构为时间序列，详细记录了其工业运营中的历史设备干预和性能。这些细粒度数据，包括业务记录和工业数据点，特别适合开发和训练高精度预测性维护模型，以在设备发生故障前进行预测。
预测性维护的全球市场正在迅速扩张，2025 年市场价值为136.5 亿美元，预计将以24.30% 的复合年增长率增长。[4] 虽然访问需要应对复杂性，例如非结构化的 PDF/纸质日志和专有的项目特定 CAD 设计的可能性，但该工业数据固有的稀缺性和直接适用性使其成为人工智能买家瞄准这一利润丰厚、高增长领域的高价值资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：维护日志可能采用非结构化的 PDF 或纸质格式；技术设计（CAD）是专有的但项目特定的 · 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 A2Dm 从真实的工业维护干预中生成专有的时间序列数据。这些日志详细记录了复杂设备上的预防性和纠正性措施，是工业人工智能供应商构建和验证预测性维护模型所需的地面实况。在一个预计每年增长超过 24% 的市场中，这个稀有的数据集为优化设备正常运行时间和性能提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity78
主导的“维护日志”，工业领域，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 Freshness46
定期
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 Demand90
人工智能买家需求异常高，这得益于在复合年增长率为 24.30% 的预测性维护市场中降低运营停机时间和成本的迫切需求。[4]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 Feasibility44
低难度，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 License92
所有权=公司所有，许可=干净
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 Surplus70
盈余=中等 — 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 Audit75
✓ 良好目标 — 确定的公司 A2DM 是一家金属门制造商，而不是数据公司，这符合目标模型，但提供的 URL 已失效，并且最初的“维护日志”前提不正确。问题：提供的 URL https://www.a2dm.fr 无效；该公司的实际业务是“金属门窗制造”（NAF 代码 25.12Z），这与“维护日志数据集”机会不符；“A2DM”名称被多个不相关的实体使用，包括一家可持续发展咨询公司和一个非政府组织，造成了重大的来源混淆。[3,
- Deep Qualification90
⚠ 需要审查 — 该机会无效；目标公司是金属门窗制造商，而不是工业维护提供商，这使得假设的维护数据集不切实际。[实体不具备该细分市场的特征数据：该公司制造商品；其主要数据将与生产和销售相关，而不是定义该细分市场的广泛工业资产和维护日志；数据集类型与实际活动不符：目标公司的注册活动是制造金属门窗，而不是工业维护服务，这使得存在广泛的、面向客户的维护日志数据集极不可能。[2, 5, 7]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Maintenance logs
这证实了持有者生成了关于工业设备的预防性和纠正性维护干预记录，为训练预测性维护算法提供了必要的地面实况数据。
Industrial data
这证明了持有者拥有深入的技术文档，包括电气原理图和自动化程序，这些文档可以丰富主要日志，用于构建更复杂的诊断模型。
business_records
这证实了持有者在整个生产线方面的经验，表明该数据集可能涵盖复杂的、系统级的事件，这些事件对于优化大规模工业运营非常有价值。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
A2Dm Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at USD 13.65 billion in 2025, with a projected CAGR of 24.30% (source: Fortune Business Insights). [4]. Investment score 68.2/100 (confidence 0.49). Recommended action: Acquire.
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