Dataset opportunity
Store Dot — 工业运营数据集机会
Store Dot 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
75.8
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
58%
Action
授权
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AI市场**在**2024年达到436亿美元**，预计将以**23%的复合年增长率**增长，到**2030年达到1539亿美元**。作为该数据关键应用之一的**预测性维护市场**，在**2025年估计为142.9亿美元**，预计到**2033年将达到981.6亿美元**，复合年增长率为**27.9%**。更广泛的**工业物联网市场**在**2025年价值5143.9亿美元**，预计到**2035年将达到24302.1亿美元**，复合年增长率为**16.8%**。仅**时间序列分析市场**在**2025年价值48亿美元**，预计到**2034年将达到142亿美元**，复合年增长率为**12.8%**。尽管存在多方战略投资者、SPAC合并流程以及近期财务挑战带来的复杂性，但对**AI训练数据**的**高需求**（该市场在2025年创造了8亿美元收入，预计到2027年将增长到20-30亿美元）以及数据许可中**90-98%的利润率**，都凸显了该数据集的**巨大商业价值**，使得获取谈判变得有意义。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-09
Batteries : Eclipse lève 20 M€ et regarde vers l’Espagne
greenunivers.com ↗ - 📰press2026-06-07
Op-Ed: Sodium-ion batteries are not the end of lithium, but they may be the end of something else
mining.com ↗ - 📰press2026-06-05
Jungheinrich teste des batteries sodium-ion pour ses chariots
supplychainmagazine.fr ↗
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
出行
Volume
中等
Freshness
实时
Rarity
中等
Accessibility
开放/API
Legal
公司所有 — 可授权
Buyer persona
工业AI集成商
Store Dot 拥有丰富的工业运营数据集，具有时间序列模式，包含下载、工业数据、物联网数据和知识库。这些数据对于工业监控应用极具价值，特别是在移动出行领域实现预测性维护、优化运营效率和促进实时决策。通过传感器从工业设备收集的这些数据的粒度和历史深度对于训练先进的 AI 模型以检测异常和预测设备行为至关重要。⚠ 注意事项（有价值的数据，可协商访问）：多个战略投资者可能会使数据许可谈判复杂化；公司正在进行SPAC合并流程，这增加了复杂性；近期的财务挑战和裁员表明存在潜在的不稳定；商业模式是许可技术，而不是直接销售数据。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
StoreDot 拥有丰富、专有的工业运营数据集，主要由时间序列数据组成，源于二十多年的先进电池开发和严格测试。这些独特的数据直接满足了工业 AI 集成商对工业监控和预测性维护解决方案日益增长的需求，该市场预计到 2033 年将达到 981.6 亿美元。通过提供对电池性能、退化和运行状况的洞察，该数据集对于训练优化工业资产的 AI 模型至关重要，从而在快速扩张的工业物联网和工业 AI 领域释放巨大价值。其稀有性和直接适用性使其成为立即评估的引人注目的资产，可利用数据许可中看到的 90-98% 的利润率。
See dimension details ↓- Dataset Specificity78
主导的“工业数据”，移动出行行业，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 Rarity46
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 Volume64
5 个证据点
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
包括预测性维护应用在内的移动出行 AI 市场，预计从 2026 年到 2035 年的复合年增长率 (CAGR) 为 44.6%，这表明对工业运营的需求非常高且正在迅速增长。
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 Feasibility50
难度高，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength77
4 种证据类型，5 个点
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，3 个近期外部信号 — 超出已货币化部分的专有数据
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 — StoreDot 是一家资金雄厚的深度科技公司，致力于开发超快速充电电动汽车电池，产生有价值的研发数据，但其庞大的规模、独角兽估值和战略合作伙伴关系使其不适合作为休眠数据理想的中小企业目标。问题：StoreDot 不是中小企业；它约有 233 名员工，估值为 15 亿美元，是一家大型、成熟的公司；ICP 明确排除了“巨头/不透明集团”，并“理想情况下寻求中小企业”，而 StoreDot 不符合。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
这些证据表明 StoreDot 的面向公众的材料，包括公司概览和对其数据科学方法的见解，反映了二十多年来知识生成的悠久历史，为对数据驱动创新感兴趣的潜在买家提供了关键的背景和验证。
Industrial data
这些证据证实了 StoreDot 在电动汽车电池开发方面的核心专业知识，强调了他们使用AI生成专门的时间序列数据，这对于工业监控和预测性维护应用高度相关。
IoT / sensor data
这些具体证据展示了来自广泛电池组级测试的真实运营数据，包括在极端条件下的性能，所有这些都以时间序列数据形式捕获，对于工业物联网中的预测性维护和资产优化具有宝贵的价值。
Knowledge base / docs
这些证据表明 StoreDot 在加速电池开发方面拥有先进的内部AI、数据科学和机器学习应用，证实了他们能够生成和聚合数百万个数据点以进行高级预测建模，这对于寻求来自AI 原生运营数据的买家具有吸引力。
Marketplace
Dataset details
Geographic coverage
Global
Time range
20+ years
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for industrial monitoring, predictive maintenance, and operational efficiency use cases within the mobility sector. Usage restrictions may apply.
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 offers high value for industrial AI applications, particularly predictive maintenance and operational efficiency in the mobility sector, driven by strong market growth and demand for AI training data. Its moderate rarity and real-time freshness, combined with over two decades of proprietary development, justify a premium valuation.
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
Store Dot Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the mobility domain. Primary AI use-case: Industrial Monitoring. Market signal: The global **Industrial AI market** reached **$43.6 billion in 2024** and is projected to grow at a **CAGR of 23% to $153.9 billion by 2030**. The **predictive maintenance market**, a key application for this data, was estimated at **$14.29 billion in 2025** and is projected to reach **$98.16 billion by 2033**, growing at a **CAGR of 27.9%**. The broader **Industrial IoT market** is valued at **$514.39 billion in 2025** and is anticipated to reach **$2430.21 billion by 2035**, expanding at a **CAGR of 16.8%**. The **time series analytics market** alone is valued at **$4.8 billion in 2025** and is projected to reach **$14.2 billion by 2034** at a **CAGR of 12.8%**. Despite complexities arising from multiple strategic investors, a SPAC merger process, and recent financial challenges, the **high demand** for **AI training data** (which generated $800 million in 2025 and is projected to grow to $2–$3 billion by 2027) and the **90-98% profit margins** in data licensing underscore the **significant business value** of this dataset, making access negotiation worthwhile.. Investment score 75.8/100 (confidence 0.58). Recommended action: License.
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