Dataset opportunity
Gatik — 移动遥测数据集机会
Gatik 持有的中等移动遥测数据集，可用于预测性维护和异常检测。
Score
76.9
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
2024年全球汽车车辆预测性维护市场规模为46.6亿美元，复合年增长率为17.5%（2025-2034年）。[8]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-12
Gatik to bring autonomous freight to PepsiCo’s North American supply chain
therobotreport.com ↗ - 📰press2026-06-12
Volvo Autonomous Solutions to remove safety drivers in Q1 2027
freightwaves.com ↗ - 📰press2026-06-11
PepsiCo expanding autonomous truck use in its supply chain
supplychaindive.com ↗ - 📰press2026-06-09
Walmart, Wing add 7 markets in drone delivery expansion
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
移动遥测数据集
Modality
时间序列
Sector
移动出行
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 可授权
Buyer persona
工业人工智能与维护优化供应商
Gatik 提供一个自动驾驶车队运营遥测数据集，该数据集结构化为时间序列，捕获其自动驾驶车队丰富的真实运营数据。该数据集整合了地理数据（GPS、路线）、广泛的图像集（激光雷达、雷达、摄像头）以及精细的物联网数据（车辆诊断、传感器读数），使其非常适合开发先进的预测性维护模型，通过分析遥测和传感器流中的模式来预测组件故障。
全球汽车预测性维护市场在 2024 年的估值为约 46.6 亿美元，预计将以 17.5% 的复合年增长率增长。[8] 尽管存在已知的访问复杂性——例如原始传感器数据的高技术难度、战略知识产权敏感性以及去标识化的需求——但该多模态数据集的稀缺性和深度提供了显著的竞争优势。通过构建专有的 AI 模型来减少停机时间和优化车队维护，这是 AI 买家的一项关键需求领域，因此投资是合理的。[18, 19] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：原始传感器流（激光雷达、雷达、摄像头）的技术复杂性高；关于自动驾驶知识产权的战略敏感性；需要对公共道路使用者进行去标识化（面部、车牌）· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明 Gatik 拥有一个专有的多模态数据集，该数据集由其在实时货运运营中的自动驾驶商用卡车车队生成。传感器、运营和视觉数据的这种独特组合是开发预测性维护解决方案的 AI 供应商的关键资产。在一个预计将超过 46.6 亿美元且年增长率为 17.5% 的市场中，这些真实世界数据使得创建能够预测车辆故障的高度准确的模型成为可能，为任何维护优化平台提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的'物联网数据'，出行行业，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 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 Demand92
全球汽车预测性维护市场，该市场从根本上依赖于出行遥测数据，预计在 2023 年至 2033 年期间将以非常高的 23.9% 的复合年增长率增长，这表明需求非常强劲且增长迅速。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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，4个近期外部信号 — 专有数据超出已货币化部分
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 Audit67
⚠ 审查 — Gatik 的核心业务是销售由 AI 驱动的自动驾驶配送服务，使其成为智能/软件供应商，而不是其他运营的副产品的数据持有者。问题：该公司的核心产品是其'Gatik Driver'AI 和自动驾驶智能，作为服务（ATaaS）出售。[1, 8, 16]；该模型属于'销售智能（AI 软件……作为产品出售）'的排除标准。[1, 8, 16]；该公司已将其智能货币化
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这是来自车辆核心传感器套件的高频时间序列数据，包括激光雷达和雷达，对于训练复杂的预测性维护算法以检测组件级异常至关重要。
Geospatial data
该数据集包括频繁更新的表格日志，详细说明了行程持续时间、停靠点和路线，提供了将车辆磨损与特定商业使用模式相关联所需的运营背景。
Image collection
此图像数据集合捕获了各种天气和交通场景，为预测运行条件对车辆组件影响的模型提供了关键的环境背景。
Marketplace
Dataset details
Geographic coverage
Global (inferred from market read)
Time range
Real-time (inferred from freshness)
Update frequency
Real-time
Delivery
API (inferred from real-time data)
Formats
Time Series, JSON
License
One-time license for predictive maintenance model development and deployment.
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 proprietary, multi-modal telemetry dataset from an autonomous vehicle fleet is highly valuable for predictive maintenance in the rapidly growing automotive sector. Its rarity, real-time freshness, and direct application to a multi-billion dollar market drive its 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
Gatik Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Automotive Predictive Maintenance for Vehicles market = $4.66 billion in 2024, CAGR 17.5% (2025-2034). [8]. Investment score 76.9/100 (confidence 0.49). Recommended action: Acquire.
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