Dataset opportunity
Pure Energie — 可下载数据资产机会
Pure Energie 持有的可下载大型数据资产，可用于微调和预训练。
Score
71.7
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
62%
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)
全球能源领域 AI 市场规模为 37 亿美元（2023 年），年复合增长率为 30.1%。
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.
- 📦Data product
Pure Energie 应用程序，用于实时能源监控和数据可视化
source ↗
Profile
Dataset profile
Type
可下载数据资产
Modality
表格
Sector
其他
Volume
大型
Freshness
实时
Rarity
中等
Accessibility
部分
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
领域 LLM 构建者和垂直 AI 初创公司
Pure Energie 持有宝贵的可下载数据资产，包含表格数据，其中包括其风能和太阳能发电场的精细地理数据、关于能源生产的专有工业数据以及来自智能电表的物联网数据。这种丰富的生产、消费和动态定价信息的结合，为微调复杂的 AI 模型提供了理想的基础，用于能源负荷预测、预测性维护和电网优化等关键任务。
全球能源领域 AI 市场在 2023 年的估值为 37 亿美元，预计将以惊人的年复合增长率 30.1% 增长。[1] 虽然访问数据需要通过匿名化和专有约束来应对 GDPR 的敏感性，但巨大的市场增长和对专业能源数据的需求，使得该资产成为旨在在能源交易和智能电网管理中获得竞争优势的 AI 买家的战略性收购。⚠ 尽职调查（有价值的数据，可协商访问）：客户消费数据对 GDPR 高度敏感，需要匿名化；风能和太阳能发电场的能源生产数据是专有的，但可能涉及电网运营商（TSO/DSO）的报告限制；动态定价数据与市场波动和智能电表集成相关。· 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 Pure Energie 持有宝贵的专有能源数据集合，涵盖了数十年的可再生能源发电运营和精细的客户洞察。该数据集结合了历史时间序列生产数据、高频物联网消费和定价信息，以及来自太阳能装置的结构化地理空间数据。对于领域 LLM 构建者来说，该资产是微调模型以预测能源供应、需求和定价的绝佳候选。在全球能源领域 AI 市场预计每年增长超过 30% 的情况下，这种独特的数据为构建专业、高性能的垂直 AI 解决方案提供了关键优势。
See dimension details ↓- Dataset Specificity74
主导的“下载量”，行业其他，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 Rarity58
专有领域数据（开放降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume76
7 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 Value74
适用于微调
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand95
AI 买家需求异常高，这得益于能源领域 AI 市场的爆炸式增长，该市场正以 30.1% 的年复合增长率扩张，从而产生了对用于训练和微调模型的专业数据的强烈需求。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility48
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 Feasibility66
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 Strength83
4 种证据类型，7 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
所有权=混合，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 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 — 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 — 绝佳目标：Pure Energie 是一家荷兰可再生能源中小企业，自行发电和销售绿色电力，产生了宝贵的、未货币化的专有生产和消费数据。问题：该公司通过与 NET2GRID 的合作，向其能源客户提供数据驱动的洞察应用程序（“Verbruiksmanager”），表明他们了解数据，但；不应与名称相似的外国数据/情报供应商混淆。
- Deep Qualification90
✓ 通过 — 该目标是一家绿色能源生产商和供应商，拥有其自身可再生能源资产的宝贵专有生产数据以及来自其客户的精细消费数据。虽然数据资产与机会高度一致，但其商业化受到 GDPR 和不明确数据所有权权利的限制，因为荷兰的消费者数据被认为归消费者所有。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
该公司提供可下载的报告和基于应用程序的数据，证实了结构化的、可导出的数据的可用性，为 AI 团队提供了干净的表格输入，可立即进行模型训练。
Industrial data
自 1995 年以来产生绿色电力的证据表明，存在来自风能和太阳能资产的长期专有运营数据，这是训练稳健预测模型的关键输入。
IoT / sensor data
提及每小时电价表明存在关于能源消耗和定价的高频智能电表数据，这对于构建复杂的需求响应和电网优化算法至关重要。
Geospatial data
该公司为太阳能装置创建 3D 家庭模型，证明其拥有客户属性的结构化地理空间数据，这是优化分布式能源资源规划模型的宝贵资产。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Pure Energie Downloadable Data — a Large downloadable data asset (Tabular modality) in the other domain. Primary AI use-case: Fine Tuning. Market signal: Global AI in Energy Market size was USD 3.7 Billion in 2023, growing at a CAGR of 30.1% (source: Market.us). Investment score 71.7/100 (confidence 0.62). Recommended action: Data Sharing Agreement.
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