Dataset opportunity
Akajoule — 开放数据资产机会
Akajoule 持有的大型开放数据资产，可用于预训练和基准测试。
Score
79.3
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
71%
Action
许可
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
全球AI训练数据集市场：2025年为42亿美元，预计到2034年将达到227亿美元，复合年增长率（2026-2034）为20.6%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
Protesters target NV Energy at electric utility conference as anger over affordability rises
utilitydive.com ↗ - 📰press2026-06-03
Customer experience, better modeling can boost demand-side portfolio: report
utilitydive.com ↗ - 📰press2026-06-03
L’Occitanie présente ses nouvelles mesures de transition énergétique
greenunivers.com ↗ - 📰press2026-06-03
7 states sue Trump administration over TotalEnergies offshore wind lease buyout
utilitydive.com ↗
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
Datajoule 平台用于能源数据收集和价值化
source ↗
Profile
Dataset profile
Type
开放数据资产
Modality
表格数据
Sector
工业
Volume
大
Freshness
实时
Rarity
中等
Accessibility
开放 / API
Legal
混合所有权 — 易于许可
Buyer persona
基础模型实验室
Akajoule 拥有宝贵的开放数据资产，主要以表格形式存在，涵盖了多种数据类型，例如物联网数据、地理空间数据和事件流，以及一般数据量和开放数据。这一丰富的工业数据集合非常适合预训练高级人工智能模型，为机器学习算法学习复杂模式和关系提供了全面的输入。
此类专业数据的商业价值巨大，全球人工智能训练数据集市场预计到2034年将达到227亿美元，自2026年起复合年增长率（CAGR）为20.6%。尽管由于客户拥有的数据以及与公共部门客户的潜在监管考虑，需要进行仔细的谈判，但人工智能开发对高质量训练数据的高需求使得这项资产具有极高的价值。⚠ 尽职调查（有价值的数据，可协商访问）：Datajoule平台主要管理客户拥有的数据，需要仔细协商才能访问聚合或匿名数据集；与公共部门客户（占其客户群的60%）的合作可能会引入数据共享方面的特定合同或监管考虑。· 公司性质：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Akajoule 明确拥有一系列丰富的工业能源和环境数据，主要以表格和时间序列形式存在，这对于预训练基础模型高度相关。该数据集为人工智能买家，特别是基础模型实验室，提供了一个独特的机会，可以在一个预计到2034年达到227亿美元的市场中获取中等稀有度的领域特定数据。其对能源消耗、生产和地域动态的细致洞察对于开发可持续能源管理和工业优化方面的高级人工智能解决方案至关重要，满足了紧迫的全球需求。
See dimension details ↓- Dataset Specificity90
主导“开放数据”，工业领域，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（开放会降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume100
9个证据命中，明确提及数据量
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
适合预训练
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand88
全球人工智能训练数据集市场（包括用于预训练的数据）预计在2024年至2029年期间将以27.7%的复合年增长率（CAGR）增长，这表明人工智能数据买家的需求非常高且增长迅速。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility78
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 Strength98
5种证据类型，9个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License58
所有权=混合，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 Surplus92
盈余=高，4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 Audit50
⚠ 审查 — Akajoule 是一家独立的咨询和工程公司，通过其 Datajoule 平台专注于能源和环境数据的价值化和分析，这意味着其核心业务涉及销售数据智能服务，使其成为不合适的目标。问题：Akajoule 的核心业务包括“数据与技术”，专注于能源和环境数据的价值化并提供数字解决方案；此项产品构成销售智能。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Open data
此证据证实 Akajoule 拥有公开可用的能源和环境数据，包括动态指标和可视化，为专注于可持续性和能源效率的人工智能模型提供了宝贵的结构化信息来源。
Data-volume signal
这表明 Akajoule 提供各种行政规模（包括市和区域）的聚合能源数据，提供了一个全面的多模态数据集，适用于宏观层面的能源趋势分析和政策建模。
IoT / sensor data
Akajoule 拥有实时能源消耗和生产数据，包括能源使用的监测和分析，以及可再生能源的测量，这对于能源系统中的预测分析和优化是至关重要的时间序列数据。
Event streams
持有者可直接从公用事业运营商获取详细的能源消耗概况和负荷曲线，为智能电网管理和需求预测中的人工智能训练提供必要的时间序列事件数据。
Geospatial data
Akajoule 管理地理空间能源数据，为特定区域带来能源洞察，与地理信息系统（GIS）和开放数据计划整合，为区域能源规划和影响分析提供关键的上下文信息。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Tabular, IoT data, Geospatial data, Event streams
License
One-time license for AI pretraining purposes. Specific usage rights to be negotiated.
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 medium rarity, large volume of industrial IoT, geospatial, and event stream data, and high demand for AI pretraining. The projected growth of the AI training dataset market underscores its significant business potential.
Detailed schema & sample available on access request.
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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
Akajoule Open Data — a Large open data asset (Tabular modality) in the industrial domain. Primary AI use-case: Pretraining. Market signal: Global AI training dataset market = $4.2 billion in 2025, projected to reach $22.7 billion by 2034, with a CAGR of 20.6% (2026-2034).. Investment score 79.3/100 (confidence 0.71). Recommended action: License.
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