Dataset opportunity
Aquablu — 事件流数据集机会
Aquablu 持有的海量事件流数据集，可用于预测和异常检测。
Score
48
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
60%
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)
全球智能水管理市场 = 2025 年为 175.3 亿美元，复合年增长率为 11.70%。
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.
- ✨Signal
专有的“智能净化”技术，具有实时监控功能
source ↗
Profile
Dataset profile
Type
事件流数据集
Modality
时间序列
Sector
其他
Volume
大型
Freshness
实时
Rarity
中等
Accessibility
部分
Legal
公司所有 — GDPR 敏感（需进行个人身份信息审查）
Buyer persona
量化基金和需求预测人工智能团队
Aquablu 持有一个专有的事件流数据集，该数据集由其智能饮水机物联网传感器网络生成。此时间序列数据捕获详细的事件流，包括用户下载和来自 iot_data 源的特定消耗模式，使其非常适合旨在预测用水量和饮水机维护需求的预测模型。[8]
此类数据的价值体现在全球智能水管理市场，预计到 2025 年将达到175.3 亿美元，复合年增长率为 11.70%。[5] 尽管存在访问复杂性，例如消耗数据与个人用户资料相关联以及本地化的水质指标，但此工业数据的稀有性和粒度为开发精确、数据驱动的人工智能应用提供了独特的竞争优势。[1, 5] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通过物理饮水机中的专有物联网传感器生成；消耗数据可能通过用户的应用程序/界面与个人用户资料相关联；水质数据仅限于特定建筑管道和区域电网 · 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 Aquablu 拥有一系列来自其智能饮水机网络的专有实时消耗数据。该物联网数据集拥有超过 200,000 名员工的已确认用户群，可提供对饮料偏好（从苏打水到功能性饮料）的细粒度视图。此类信号深受量化基金和人工智能团队的青睐，用于需求预测，并且鉴于 175.3 亿美元的智能水管理市场快速增长，目前尤其有价值。
See dimension details ↓- Dataset Specificity74
主导的“事件流”，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（公开会降低稀有度）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume70
6 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
适合预测
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - ICP Audit83
⚠ 审查 — 该公司的核心业务是销售智能饮水机，并捆绑提供提供分析的智能平台 (AURA)，使其成为智能产品的销售商，因此不适合。问题：公司核心产品是硬件系统，与名为 AURA 的专有智能/分析平台紧密集成。[11, 15, 16]；AURA 被宣传为提供“数据驱动的洞察”、“设备状态、性能和消耗模式的实时洞察”，甚至是个性化补水；此分析/商业智能平台作为产品关键部分的产品意味着他们已经从事销售智能的业务，这是明确的排除项；该公司不仅仅销售硬件；它销售的是“互联水合解决方案”，其中数据和洞察是价值主张的核心部分
- Deep Qualification90
✓ 通过 — Aquablu 是数据持有者，销售智能饮水机并生成消耗事件的副产品时间序列数据集。但是，数据所有权与客户混合，转售的许可权不明确且受 GDPR 限制。
- Buyer Demand88
人工智能买家需求很高，这得益于智能水管理市场的显著增长，该市场正以 11.70% 的复合年增长率扩张，公用事业和行业正在投资数字化解决方案。[5]
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 Feasibility80
低难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength80
4 种证据类型，6 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License62
所有权=公司所有，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.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
这指向核心时间序列数据，捕获实时饮料使用量和环境影响指标，为消耗预测模型提供直接、高价值的输入。
Downloads / exports
该公司通过报价请求和手册下载捕获 B2B 销售意向数据，提供客户元数据来源，可以丰富主要数据集。
IoT / sensor data
证据证实数据来自大规模的物联网支持的智能饮水机网络，验证了事件流的来源和显著规模。
Industrial data
这表明收集了与过滤和净化相关的机器级时间序列数据，这对于构建预测性维护算法很有价值。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Aquablu Event Stream — a Large event stream dataset (Time Series modality) in the other domain. Primary AI use-case: Forecasting. Market signal: Global Smart Water Management market = $17.53B in 2025, CAGR 11.70% (source: Fortune Business Insights). Investment score 48.0/100 (confidence 0.6). Recommended action: Data Sharing Agreement.
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