Dataset opportunity
Lastenergy — 维护日志数据集机会
Lastenergy 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
72.3
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 size (indicative estimate)
全球预测性维护市场在 2025 年的价值为 142 亿美元，预计在 2026-2033 年期间的复合年增长率为 27.9%（来源：Grand View Research）。[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.
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 受限
Buyer persona
工业人工智能与维护优化供应商
Lastenergy 持有一个广泛的维护日志数据集，该数据集结构化为来自其工业核电运营的时间序列数据。该数据集以 `iot_data` 和详细的 `maintenance_logs` 为证，提供了设备性能、运行参数和历史故障事件的详细记录，使其非常适合开发和验证高保真预测性维护模型。
该数据在全球预测性维护市场中运行，该市场在 2025 年的价值为142 亿美元，预计将以惊人的27.9% 的复合年增长率增长。[1] 虽然访问受到 NRC 等机构严格的监管审查，并且需要高级安全许可，但运营核数据的固有稀缺性和战略价值为寻求在此高增长市场中获得决定性竞争优势的买家提供了独特而引人注目的机会。⚠ 尽职调查（有价值的数据，可协商的访问权限）：核工业受到严格的国家安全和监管审查（美国 NRC，英国 ONR）。；运营数据可能因安全协议而被列为机密或受限。；数据共享需要高级安全许可并遵守国际核条约。· 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 Lastenergy 拥有并运营自己的下一代微型模块化反应堆，生成持续的专有运营和维护数据流。这个高稀缺性时间序列日志数据集是工业人工智能供应商构建预测性维护模型的关键资产。在一个预计每年增长近 28% 的市场中，来自高风险能源发电环境的独特数据为训练和验证复杂的 AI 解决方案提供了显著的竞争优势。
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 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 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
人工智能买家需求异常高，这得益于在以 27.9% 的复合年增长率扩张的市场中降低运营停机时间的迫切需求。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility36
开放/API 访问
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，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 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License66
所有权=拥有，许可=受限
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 Orientation22
0 个数据胃口信号（0 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 — 专有数据超出已货币化的部分
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. - ICP Audit100
✓ 良好目标 — Last Energy 为工业客户设计、建造、拥有和运营微型核反应堆，使其运营和维护数据成为其核心能源销售业务的有价值的、休眠的副产品。问题：该公司仍处于商业前/早期部署阶段，其首批反应堆预计在 2026 年至 2027 年之间投入运营。[1, 13, 17]；业务模式涉及长期购电协议 (PPA)，这意味着数据是在非常长的生命周期内生成的，而不是来自高容量的短期。
- Deep Qualification50
⚠ 需要审查 — 该假设是合理的，但为时过早；Last Energy 尚未拥有运行中的反应堆，因此不拥有指定的维护数据集，尽管预计一旦其试点项目投入运营（预计 2026 年达到临界状态），它将生成该数据集。[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
- “<figure><div><img src="https://imgproxy.divecdn.com/nSz4DtE-OIJ-Zt4f7t1lVnUY0G0DRNXqBigj-D4Skz0/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9DaG9sbGEtaGVyby5qcGc=.webp" /></div></figure><p>“Given Arizona’s increasing demand for around-the-clock energy and the long timelines for adding new generation, the conversion has proven to be a viable option,” APS said.</p>”
- “<figure><div><img src="https://imgproxy.divecdn.com/bgN5jB-DUP9sh-VT22YrAhSaPiCJewDiZ3MMNGioJL8/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0xNTQ4OTQ0NjYuanBn.webp" /></div></figure><p>Giving Advanced Power Services a waiver from the PJM Interconnection’s rules could harm other project developers, the agency said.</p>”
- “<figure><div><img src="https://imgproxy.divecdn.com/dpiVgKtlIMKJFC4tCdas8ADiOeoCJE5WEtYsN5tMbSw/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0yMjU5Nzg0MzIwLmpwZw==.webp" /></div></figure><p>The companies said the deal marks Walmart’s first nuclear power purchase agreement and is “among the first of its kind between a large retailer and a nuclear energy facility in the United States.”</p>”
Developer portal
面向公众的文档证实了该公司作为先进、下一代核能技术的开发商的身份，确立了其在工业领域的技术信誉。
IoT / sensor data
该公司作为其发电厂所有者和运营商的既定业务模式证实了它直接控制由此产生的运营和传感器数据，这是任何工业 IoT 数据资产的原材料。
Industrial data
工厂生产的模块化方法的证据表明，生成了与工业资产的制造和组装相关的结构化数据，为维护模型提供了有价值的生命周期背景。
Maintenance logs
该公司致力于为客户拥有和运营其发电厂，这是专有维护日志的直接来源，提供了训练高价值预测性维护算法所需的基本地面实况数据。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Lastenergy 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 $14.2 billion in 2025, projected to grow at a CAGR of 27.9% (2026-2033) (source: Grand View Research). [1]. Investment score 72.3/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
From the marketplace
Explore live data opportunities
Ad Cleantech — 维护日志数据集机会
View opportunity →出行Chargeguru — 出行遥测数据集机会
View opportunity →工业Bw Ideol — 维护日志数据集机会
View opportunity →