Dataset opportunity
Ilos — 维护日志数据集机会
Ilos 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
72.7
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
Partnership (group-level)
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 134 亿美元，预计将以 23.2% 的复合年增长率增长（来源：Market.us）。[1]
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
向拥有内部资产管理的完全集成式 IPP 平台转型
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Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
industrial
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 可授权许可
Buyer persona
Industrial AI & maintenance-optimization vendors
Ilos 持有一个全面的维护日志数据集，结构为时间序列数据，源自其泛欧能源业务。该数据集整合了运营资产的精细iot_data和industrial_data，使其非常适合开发和验证高保真Predictive Maintenance模型。
预测性维护的全球市场规模巨大，2025 年价值为134 亿美元，预计将以惊人的23.2% 的复合年增长率增长。[1] 这个高增长市场凸显了 Ilos 独特数据的巨大价值。虽然访问需要进行谈判，因为它与关键能源基础设施和 AXA IM Alts 的多数股权相关，但该数据集的稀有性和直接适用于数十亿美元的用例，提供了一个引人注目的投资机会。⚠ 尽职调查（有价值的数据，可协商访问）：截至 2025 年，由 AXA IM Alts 多数拥有（60%）；数据涉及关键能源基础设施和电网遥测；横跨 7 个国家的泛欧业务可能涉及本地化数据孤岛 · corporate：AXA IM Alts 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
公开证据证实 Ilos 拥有并运营自己的太阳能农场，生成专有的纵向维护数据集。这些数据结合了来自太阳能、电池存储和氢能源资产的实时 IoT 传感器读数和工业系统性能。对于工业人工智能供应商来说，这是一个难得的机会，可以获取高质量的培训数据，以构建和验证快速增长的可再生能源领域的预测性维护模型，该市场的年增长率预计将超过 23%。这种独特的数据流直接满足了对地面真实运营情报的核心需求，以提高资产正常运行时间和效率。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业部门，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 Demand90
人工智能买家需求极高，这得益于预测性维护市场的快速扩张，该市场正以 23.2% 的复合年增长率增长。[1]
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 Feasibility0
高难度，AXA IM Alts 的子公司
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=拥有，许可=干净
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
AXA IM Alts 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据胃口信号（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 Audit83
✓ 良好目标 — Ilos Energy 是一个良好目标，因为它是一家独立电力生产商，开发、建设和运营自己的太阳能农场，这应该会作为其销售电力的核心业务的副产品产生有价值的维护和运营数据。问题：该公司由大型资产管理公司（AXA IM Alts，前身为 BNP Paribas Asset Management Alts）多数拥有，这可能使其行为不像一个；虽然肯定会产生运营数据，但其网站上并未明确提及它是一个“数据集”，因此其结构和可访问性未知。
- Deep Qualification90
⚠ 需要审查 — Ilos 是一家太阳能发电公司，开发、建设和运营自己的资产，这使得“维护日志数据集”作为其核心业务的副产品极有可能存在。然而，这些运营数据与项目开发和融资的指定细分市场不符。[许可受限；实体不持有细分市场的特征数据：已识别的数据集（维护日志）与运营资产管理相关，而细分市场由项目开发、融资和市场价格数据定义。]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>Lincoln Electric System is energizing a 3-MW/12-MWh zinc-based battery to support the Nebraska state Capitol complex and other critical infrastructure.</p>”
- “<figure><div><img src="https://imgproxy.divecdn.com/R9VpWXCI-N45Br9Sxcuid13dNR4kDAaWssKLIGBBmTE/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0xMjA2NTM2NzAzLmpwZw==.webp" /></div></figure><p>Regulatory complexities are thwarting innovation and keeping electricity bills for the majority of Californians far too high, writes Ardi Arian, CEO of Renewable America.</p>”
- “<p>Ce serait une quasi-première en France, mise à part une petite expérience au Triscastin (Drôme). EDF, par l’intermédiaire de sa filiale Dalkia, étudie la récupération de la chaleur produite par sa centrale nucléaire de Cattenom en Moselle, de manière à alimenter un réseau de chauffage urbain, indique La Tribune. Ces calories décarbonées perdues seraient  </p> <p>L’article <a href="https://www.greenunivers.com/2026/07/a-cattenom-edf-etudie-la-recuperation-de-la-chaleur-nucleaire-perdue-430853/">A Cattenom, EDF étudie la récupération de la chaleur nucléaire perdue</a> est apparu en premi”
IoT / sensor data
该公司从其太阳能资产生成实时 IoT 数据，包括面板温度和设备状态的传感器读数，这对于在故障前检测异常的模型训练至关重要。
Industrial data
Ilos 捕获了跨太阳能、氢能和电池存储（BESS）系统的集成工业性能数据，提供了优化复杂能源电网所需的独特的多资产视图。
Maintenance logs
通过保留对其太阳能农场的完全所有权和运营控制权，Ilos 创建了专有的资产管理和干预日志历史记录，提供了验证预测性维护算法所需的地面真实数据。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Ilos 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 13.4 billion in 2025 and is projected to grow at a CAGR of 23.2% (source: Market.us). [1]. Investment score 72.7/100 (confidence 0.49). Recommended action: Partnership (group-level).
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