Dataset opportunity
Axlehire — 移动遥测数据集商机
由 Axlehire 持有的中等规模移动遥测数据集，可用于预测性维护和异常检测。
Score
75.2
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
56%
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
全球车辆预测性维护市场为 2024 年的 $4.66B，CAGR 17.5% (2025-2034)，预计到 2034 年将达到 $23.39B
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-05
CDL fight reignites as DACA recipient petitions FMCSA
freightwaves.com ↗ - 📰press2026-06-05
Up, then down: drop in trucking jobs in May mostly wipes out gain from April
freightwaves.com ↗ - 📰press2026-06-05
Canada Post parcel volumes decline 17.2% in Q1
freightwaves.com ↗ - 📰press2026-06-05
Can AI gains give alternative delivery providers an edge?
supplychaindive.com ↗ - 📰press2026-06-05
EEOC moves to axe EEO-1 reporting
supplychaindive.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.
- 📦Data product
用于实时包裹跟踪和状态更新的客户仪表板
source ↗
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
受限
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
工业AI与维护优化供应商
Jitsu（前身为 AxleHire）拥有丰富的出行遥测数据集（一种时间序列模式），其中包含从其最后一英里交付运营中收集的事件流、地理数据、工业数据和物联网数据。这些详细数据，包括实时跟踪和运营指标，对于预测性维护应用极具价值，能够预测设备故障并优化出行领域的车辆生命周期。
尽管由于公司在 2024 年 4 月的品牌重塑、需要严格遵守 GDPR 的个人身份信息 (PII) 处理以及深度集成到专有技术平台而导致访问复杂性，但该数据为人工智能买家提供了独特的见解。全球预测性维护市场，特别是汽车领域，正经历显著增长，这得益于降低停机时间和运营成本的需求，使得该数据集对于高级分析解决方案而言异常有价值。⚠ 尽职调查（有价值的数据，可协商访问）：公司于 2024 年 4 月从 AxleHire 更名为 Jitsu，需要仔细沟通和品牌一致性；处理与交付和司机相关的个人身份信息 (PII)，需要严格遵守 GDPR 和隐私规定；运营数据已深度集成到其专有技术平台中以进行内部优化，这可能会使直接数据提取复杂化。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Axlehire 的专有技术平台生成了丰富的出行遥测数据集，其先进的实时决策、动态路线规划和物流网络运营优化算法证明了这一点。这种高稀有度的时间序列数据提供了对车辆性能和资产利用率无与伦比的见解，使其对工业人工智能和维护优化供应商极具价值。该数据集满足了关键且快速增长的需求，直接支持预测性维护解决方案，该市场预计将从 2024 年的 46.6 亿美元增长到 2034 年的 233.9 亿美元，使复杂的模型能够预测故障并优化车队寿命。
See dimension details ↓- Dataset Specificity100
占主导地位的“物联网数据”，出行行业，4 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 Rarity94
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume58
4 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 Value94
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
人工智能在出行市场的应用，其中预测性维护是利用遥测数据的关键应用，预计从 2026 年到 2035 年的复合年增长率 (CAGR) 为 44.6%，到 2035 年将达到 5285.8 亿美元。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility20
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 Strength74
4 种证据类型，4 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
所有权=混合，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 个数据需求信号（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，5 个近期外部信号 — 超出已货币化数据的专有数据
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 — Axlehire（已更名为 Jitsu）是一家最后一英里交付公司，作为其核心运营业务的副产品，生成了有价值的出行遥测数据，该公司不销售数据或情报，使其成为数据市场的良好目标。问题：该公司于 2024 年 4 月更名为 Jitsu，在研究时可能会引起一些混淆；不同来源报告的员工人数和融资金额存在细微差异。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
此证据证实了 Axlehire 使用实时算法来优化客户体验和运输时间，表明存在强大的传感器衍生运营数据流，这对于理解车辆行为和影响维护的环境因素至关重要。
Geospatial data
此数据类型代表了 Axlehire 的专有动态路线规划算法的输出，提供了详细的位置和移动模式，这对于分析路线效率、车辆压力以及地理位置对资产磨损的影响至关重要。
Event streams
此类别包括 Axlehire 技术平台生成的运营事件日志，详细说明了物流、路线规划和通信优化，这些对于识别导致效率低下或潜在设备压力的模式至关重要。
Industrial data
这指的是从 Axlehire 平台获得的绩效指标，包括对负载聚合、车辆匹配和交付成功率的见解，这些对于评估车辆利用率、压力水平和预测维护需求至关重要。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time (rolling)
Update frequency
Real-time
Delivery
API
Formats
JSON, Time Series
License
One-time license for predictive maintenance use cases within the mobility sector, subject to GDPR compliance.
Personal data
Contains 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 high-rarity, proprietary mobility telemetry dataset offers granular insights into vehicle performance, crucial for the rapidly growing predictive maintenance market. The real-time nature and moderate volume, combined with significant GDPR compliance requirements, justify a 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
Axlehire Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance for Vehicles Market = $4.66B in 2024, CAGR 17.5% (2025-2034) to reach $23.39B by 2034. Investment score 75.2/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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