Dataset opportunity
Agilityrobotics — 工业传感器数据集机会
Agilityrobotics 持有的中等工业传感器数据集，可用于预测性维护和异常检测。
Score
47.5
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
49%
Action
收购
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 size (indicative estimate)
全球预测性维护市场在 2025 年的估值为 142 亿美元，预计将以 27.9% 的复合年增长率增长（2026-2033 年）。
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.
- 🧑💻Hiring a data role
招聘人工智能/机器学习和机器人软件工程师
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Profile
Dataset profile
Type
工业传感器数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 许可权待明确
Buyer persona
工业人工智能与维护优化供应商
Agility Robotics 持有一个独特的工业传感器数据集，由其双足机器人在第三方物流设施中生成。数据包括丰富的时间序列模态，对预测性维护至关重要，例如来自高保真 IMU 和关节扭矩传感器的 `iot_data`、来自 LiDAR 的 `image_collection` 数据以及操作 `event_streams`。这种复杂的遥测技术为训练 AI 模型以在硬件故障导致运营停机之前进行预测和诊断提供了全面的基础。
此数据集价值非凡，因为它服务于全球预测性维护市场，该市场在 2025 年的估值为 142 亿美元，预计将以 27.9% 的复合年增长率增长。虽然访问涉及处理共同所有权限制以及数据对 Agility 自身“Physical AI”堆栈的极高战略价值，但其稀有性及其对数十亿美元市场的直接适用性使其成为任何专注于工业自动化和资产管理的 AI 买家的引人注目的资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据在第三方物流设施（例如 Amazon、GXO）中生成，可能存在共同所有权或隐私限制；原始机器人遥测（LiDAR、IMU、关节扭矩）的高技术复杂性需要专门的解码；数据对其自身“Physical AI”堆栈的战略价值可能使其不愿授权给竞争对手。· 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 Agility Robotics 拥有大量专有的时间序列传感器数据，这些数据来自超过 65,000 小时的真实工业机器人运行。这些独特的数据对于开发预测性维护解决方案的 AI 供应商至关重要，使他们能够训练能够预测复杂机器人系统故障的模型。在一个预计复合年增长率为 27.9% 的市场中，该数据集提供了一个难得的机会，可以在工业自动化和维护优化领域获得竞争优势。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'，行业工业，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 Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 条证据命中
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
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
买家需求极高，这得益于预测性维护市场的快速增长，预计该市场将以 27.9% 的复合年增长率扩张，因为各行业大力投资人工智能以减少设备停机时间。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility14
高难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 条命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
所有权=公司所有，许可=权利不明确
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 Audit58
⚠ 审查 — Agility Robotics 的契合度很差，因为其核心业务模式包括机器人即服务 (RaaS) 和用于车队管理的云软件平台 (Agility Arc)，这构成了销售智能和数据驱动服务。问题：公司核心业务是销售支持人工智能的机器人和软件平台，这是一种销售智能的形式，因此不符合 ICP；业务模式明确为机器人即服务 (RaaS) 和直接销售，两者都包括软件、维护和云平台 (Agility Arc)；该公司不是中小企业；它拥有 410 至 500 名员工，估值超过 17.5 亿美元。[1, 2, 4]；机器人生成的数据不是“休眠”的；它被积极用于改进“Physical AI”模型，并且是其核心价值主张的一部分。
- Deep Qualification90
✓ 通过 — Agility Robotics 是一个强大的数据持有者候选者。它以服务形式销售人形机器人自动化，作为副产品生成大量独特的工业传感器数据集。虽然数据在客户站点（Amazon、GXO）生成，形成了混合所有权模式，但 Agility 明确保留使用聚合和匿名化数据来改进其核心 AI 平台的权利。即将进行的 SPAC 主导的公开募股为谈判创造了一个引人注目的触发点。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这代表了海量的时间序列传感器数据，记录了超过 65,000 小时的连续工业运行，这对于训练强大的预测性维护算法至关重要。
Event streams
该数据集包括事件流，记录了超过 100,000 个离散任务，使 AI 模型能够将特定的操作动作与传感器级别的性能和潜在的退化相关联。
Image collection
这指向了用于训练机器人AI 堆栈的相应图像集合，为环境条件和物理状态提供了关键的视觉上下文，可以增强时间序列维护模型。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Agilityrobotics Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at $14.2 billion in 2025, projected to grow at a CAGR of 27.9% (2026-2033) (source: Grand View Research).. Investment score 47.5/100 (confidence 0.49). Recommended action: Acquire.
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