Dataset opportunity
Nyobolt — 工业运营数据集商机
Nyobolt 持有的中等规模工业运营数据集，可用于工业监控和预测。
Score
74.3
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
53%
Action
采购
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
全球工业人工智能市场 = 2024 年达到 326 亿美元，复合年增长率 (CAGR) 为 18.3% (2025-2035)
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.
Profile
Dataset profile
Type
工业运营数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 可授权
Buyer persona
工业人工智能集成商
Nyobolt 拥有一个独特的工业运营数据集，主要由其先进电池技术衍生的时间序列和物联网数据组成。这些数据包括电池电压、温度、充放电周期和性能参数等关键指标，非常适合工业监控和预测性维护应用。该数据集提供了对电池健康状况、退化模式和严苛工业环境下的运行效率的精细洞察，从而能够实现先进的电池优化和异常检测。
这个有价值的数据集满足了快速增长的工业人工智能市场的巨大需求，该市场在 2024 年的估值为 326 亿美元，预计到 2035 年将达到 2121 亿美元，复合年增长率 (CAGR) 为 18.3%。该数据的稀缺性源于其来自专有电池技术和客户系统的实际部署数据，这对于训练强大的 AI 模型至关重要。尽管由于敏感数据和客户协议存在固有的访问复杂性，但从这种专业工业数据中获得的洞察对于最大限度地减少停机时间和提高运营效率至关重要，可将生产力提高高达 30%。⚠ 尽职调查（有价值的数据，可协商的访问权限）：专有电池技术和材料数据可能高度敏感；来自已部署客户系统的数据可能受客户协议的约束。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Nyobolt 持有一个专有的工业运营数据集，其中包含来自其先进电池技术的丰富时间序列数据。这些证据具体证明了其在机器人、电动汽车和自主移动机器人中的实际应用，为工业监控和预测性维护提供了关键见解。对于以快速增长的全球工业人工智能市场为目标的人工智能集成商而言，该数据集提供了独特的运营智能，可在高需求工业环境中优化能源系统并提高资产性能。
See dimension details ↓- Dataset Specificity78
主导的“工业数据”，行业为工业，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 Volume64
5 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
适用于工业监控
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
全球工业人工智能市场，高度依赖工业运营数据进行监控，预计将从 2024 年的 436 亿美元增长到 2030 年的 1539 亿美元，复合年增长率 (CAGR) 为 23%。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility62
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 Feasibility4
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 Strength68
3 种证据类型，5 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=已拥有，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 Orientation73
3 个数据需求信号（3 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 Audit75
⚠ 审查 — Nyobolt 是一家开发和销售超快速充电电池技术的独角兽公司，作为副产品产生有价值的运营数据，但其庞大的规模和估值使其不适合面向中小企业的市场。问题：Nyobolt 不是中小企业；它是一家快速增长的规模化公司，估值达 10 亿美元，属于 ICP 的“巨头/不透明集团”排除项；该公司的核心业务是电池技术和集成产品的开发和销售。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
这些时间序列数据展示了 Nyobolt 在高性能电池技术方面的核心专业知识，并通过独立的 OEM 测试验证了其在实际电动汽车原型中卓越的耐用性和快速充电能力。这对于专注于电池生命周期管理和性能优化的人工智能模型至关重要。
Developer portal
多模态证据证实了 Nyobolt 与机器人公司（包括一家领先的人形机器人开发商）的商业合作，以优化电池性能和工作充电比。这些数据对于构建先进机器人和自动化解决方案的人工智能集成商至关重要。
IoT / sensor data
这些时间序列数据详细介绍了关键电池指标（如充电状态、功率状态和健康状态）的精细物联网级监控，从而实现了预测估算和早期故障检测。这对于驱动预防性维护和优化AMR 任务的人工智能解决方案至关重要。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, IoT data
License
One-time license for industrial monitoring, predictive maintenance, and battery optimization use cases.
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 high rarity as proprietary industrial operations data from advanced battery technology, coupled with strong demand from the rapidly growing Industrial AI market, particularly for predictive maintenance and battery optimization.
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
Nyobolt Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the industrial domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Industrial Artificial Intelligence market = US$ 32.6 Billion in 2024, CAGR 18.3% (2025-2035). Investment score 74.3/100 (confidence 0.53). Recommended action: Acquire.
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