Dataset opportunity
Path Robotics — 图像数据集机会
Path Robotics 持有的海量图像数据集，可用于计算机视觉和多模态预训练。
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
60%
Action
标注计划
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)
全球工业视觉市场 = 2024 年为 100 亿美元，复合年增长率为 7.4%（2025-2035 年）。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-06
HII signs up to $900M agreement with Path Robotics, GrayMatter Robotics
therobotreport.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.
Profile
Dataset profile
Type
图像数据集
Modality
图像
Sector
工业
Volume
大型
Freshness
实时
Rarity
中等
Accessibility
部分
Legal
公司所有 — 许可权待明确
Buyer persona
计算机视觉实验室和基础模型团队
Path Robotics 持有一个宝贵的图像数据集，其中包含其工业机器人焊接操作的原始物理传感器和视觉日志。这些工业数据提供了对制造过程的罕见、真实世界的视图，包括来自国防和造船等行业的潜在敏感零件几何形状，使其成为训练先进计算机视觉模型的理想选择。
全球工业视觉市场在2024 年的估值为 100 亿美元，预计到 2035 年的复合年增长率为 7.4%。[8] 尽管由于其深度集成到专有的“Obsidian”模型和客户保密性而存在访问复杂性，但这些原始传感器数据的稀有性和高保真度为开发下一代工业人工智能提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据深度集成到其专有的“Obsidian”人工智能模型中；可能与客户零件几何形状（例如，国防/造船）存在共同所有权或保密问题；主要价值在于原始物理传感器/视觉日志，目前仅用于内部模型训练 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
证据强烈表明 Path Robotics 拥有海量专有数据集，量化为数千万英寸的焊接数据，用于训练其基础焊接人工智能。该集合是其计算机视觉系统的核心，使机器人能够在复杂的工业环境中“看到”并适应。对于基础模型团队而言，这代表了一个难得的机会，可以获取工业级训练数据，以在快速增长的 100 亿美元工业视觉市场中竞争。该数据独特地专注于焊接和实际应用，使其成为开发专业、高性能机器人模型的宝贵资产。
See dimension details ↓- Dataset Specificity90
主导的“图像集合”，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（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
适用于计算机视觉
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
买家需求非常高，这得益于 100 亿美元工业视觉市场 7.4% 的强劲复合年增长率，该市场依赖独特的真实世界数据进行人工智能模型开发。[8]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility56
公开/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
高难度，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 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 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
过剩=高，1 个近期外部信号 — 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 — Path Robotics 的核心业务是销售人工智能驱动的机器人焊接系统以及相关的软件/人工智能模型，使其成为已服务于市场的技术供应商，而不是休眠数据的持有者。问题：该公司的整个商业模式建立在销售智能（人工智能软件、机器学习模型）作为产品之上。[10, 13, 17]；他们的产品是“智能焊接单元”和“Obsidian”人工智能模型，该模型基于数据训练但作为一种能力出售，而不是数据本身。[10, 14, 15；它们被明确描述为人工智能、机器学习和计算机视觉系统的开发商。[7]；公司首席收入官证实，他们的业务是构建和销售“制造业的物理人工智能”。[19]
- Deep Qualification60
✓ 通过 — 目标是拥有连贯数据集的数据持有者，但数据所有权和许可权未知，并且可能由于国防和造船等敏感客户应用而受到限制。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
该公司收集潜在客户下载案例研究的潜在客户开发数据，直接了解客户意图和市场需求。
Image collection
持有者明确表示其技术建立在计算机视觉之上，证明了用于训练其工业机器人系统的核心图像数据集的存在。
Industrial data
该公司证实其人工智能是在数千万英寸的焊接数据上训练的，这是一个独特且庞大的特定数据集，非常适合构建下一代工业应用的基础模型。
IoT / sensor data
部署系统中的连续数据反馈循环确保数据集不断用真实世界的运营数据进行丰富，从而提高其在稳健模型训练中的价值。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Path Robotics Image — a Large image dataset (Image modality) in the industrial domain. Primary AI use-case: Computer Vision. Market signal: Global Industrial Vision market = $10.0B in 2024, CAGR 7.4% (2025-2035) (source: Market Research Future). Investment score 47.5/100 (confidence 0.6). Recommended action: Annotation Program.
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