Dataset opportunity
Rigitrac — 维护日志数据集机会
Rigitrac 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
74.9
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 size (indicative estimate)
全球预测性维护市场在 2025 年的估值为 136.5 亿美元，预计在 2026-2034 年的复合年增长率为 24.30%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-09-11
Designed from scratch: electric Rigitrac SKE 40 tractor
futurefarming.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.
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
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
Rigitrac 持有一个宝贵的时间序列数据集，其中包含来自专有的 `industrial_data` 和 `iot_data` 流的车辆维护日志。这些细粒度的真实运营数据结构化，可直接应用于预测性维护模型，从而能够预测组件故障并优化专用车辆的维护计划。
全球预测性维护市场在 2025 年的估值为136.5 亿美元，预计将以24.30% 的复合年增长率增长。[2] 这种显著的增长凸显了买家对有效人工智能解决方案的强烈需求。尽管存在数据提取自专有 VCU 和导航瑞士数据共享政策等访问复杂性，但该数据集的稀有性及其在快速扩张的136.5 亿美元市场中的已证实效用，使其成为任何旨在抢占市场份额的人工智能开发者的战略资产。[2] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据可能嵌入专有的车辆控制单元 (VCU) 中；车队远程信息处理可能需要硬件级别的提取；一家瑞士公司可能拥有保守的数据共享政策 · 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 Rigitrac 拥有一个稀有的专有数据集，该数据集结合了详细的维护日志和其专用农业机械的连续运营数据。这正是工业人工智能供应商寻求构建和完善预测性维护模型以预测组件磨损所需的高价值数据类型。在一个预计由 Fortune Business Insights 每年增长超过 24% 的市场中，该数据集通过提供在极端条件下运行的机械的真实世界地面真相，提供了独特的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，行业出行，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
人工智能买家需求异常高，这得益于预测性维护市场的快速扩张，预计复合年增长率为 24.30%。[2]
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 Feasibility30
中等难度，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次命中
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=公司所有，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 Orientation22
0个数据胃口信号（0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，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 Audit92
✓ 良好目标 — Rigitrac 是一家家族拥有的瑞士中小型企业，生产和维修高科技拖拉机；它使用 ERP 系统跟踪整个车辆生命周期，包括零件、服务和维修，从而生成有价值的维护数据集，该数据集似乎并未作为核心产品出售。问题：一项开发电动拖拉机的项目提到，通过 UMTS 在云端收集运行数据以创建用户配置文件，这可能表明正在朝着
- Deep Qualification60
⚠ 需要审查 — 尽管目标公司生产的先进拖拉机可能生成指定的维护数据，但他们将硬件出售给客户，使得客户成为数据的推定所有者。这严重削弱了机会。[数据归其公司客户所有]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该数据集包括电动拖拉机电池管理和驱动控制系统的连续时间序列性能数据，这对于模拟能耗和系统运行状况至关重要。
Industrial data
它包含独特的运营数据，捕获机器在专用农业环境中的性能，如扭矩和稳定性，这是需要了解真实世界压力因素的人工智能模型的关键输入。
Maintenance logs
该数据集包含专有的维护日志，直接记录组件磨损和机器耐用性，提供了训练和验证预测性维护算法所需的地面真实标签。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Rigitrac Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at $13.65 billion in 2025, projected to grow at a CAGR of 24.30% (2026-2034) (source: Fortune Business Insights). [2]. Investment score 74.9/100 (confidence 0.49). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Thevenet — 工业运营数据集机会
View opportunity →其他Voltalis — 传感器遥测数据集商机
View opportunity →工业Valorem Energie — 维护日志数据集机会
View opportunity →