Dataset opportunity
Quicargo — 移动和地理空间数据集商机
Quicargo 持有的大型移动和地理空间数据集，可用于地理人工智能以及路线规划和预测。
Score
75.4
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
79%
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 size (indicative estimate)
全球地理空间分析人工智能市场 = 2024 年达到 477.6 亿美元，复合年增长率 25.71% (2025-2035)
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
移动和地理空间数据集
Modality
表格型
Sector
移动出行
Volume
大
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
聚合/第三方 — GDPR敏感（PII审查）
Buyer persona
地理空间人工智能和移动分析团队
Quicargo 拥有一个移动与地理空间数据集，以表格形式呈现，通过API访问、显著的数据量、地理数据、工业数据、物联网数据、知识库和交易数据得到证实。这种丰富的组合提供了对现实世界移动模式和物流运营的精细洞察，使其对于需要精确基于位置的智能进行分析、预测和优化的地理AI应用极具价值。
此类数据市场正在迅速扩张，仅地理空间分析人工智能市场在2024年的估值就达到477.6亿美元，预计从2025年到2035年将以25.71%的复合年增长率增长。这种高速增长得益于交通和物流等行业对实时位置智能和预测分析日益增长的需求，以优化运营并增强决策。尽管存在GVT子公司、数据部分来源于第三方承运商以及存在GDPR敏感数据等复杂性，但该稀有且全面的数据集为地理AI用例（尤其是在路线优化和需求预测方面）提供了有价值的洞察，这证明了获取访问权限的谈判是合理的。⚠ 尽职调查（有价值的数据，可协商访问）：GVT子公司；数据部分来源于第三方承运商；包含用户/员工的GDPR敏感数据 · 公司：被GVT收购。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Quicargo 拥有高度专有且广泛的移动和地理空间数据集，为欧洲公路货运物流提供了无与伦比的洞察。这一丰富的实时跟踪和历史交易数据集合，来源于6,000多辆卡车和270家承运商，直接满足了地理空间AI和移动分析团队的关键需求。随着全球地理空间分析AI市场预计将大幅增长，该数据集为开发物流优化、预测路线规划和可持续供应链管理方面的先进解决方案提供了独特的基础。
See dimension details ↓- Dataset Specificity100
主要为“地理数据”，行业为移动出行，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 Volume98
8个证据命中，明确提及数据量
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value94
适用于地理AI
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand95
全球移动出行领域的人工智能（AI）市场，利用地理空间数据集进行地理AI，预计从2026年到2035年将以44.6%的复合年增长率（CAGR）增长，表明买家需求极高。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
开放/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 Feasibility0
中等难度，被GVT收购
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
7种证据类型，8次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License10
所有权=聚合，许可=GDPR敏感
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence45
被GVT收购
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2个数据需求信号（2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 Audit100
✓ 良好目标 — Quicargo 是一个良好目标，因为它是一家可联系的中小型企业，经营数字货运代理业务，产生有价值的物流数据作为副产品，并明确表示不将其作为核心产品出售。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>Cargo theft has advanced from smash-and-grab crimes into sophisticated identity-based fraud schemes, experts say</p> <p>The post <a href="https://www.freightwaves.com/news/criminals-target-freight-with-fake-ids-spoofed-emails-and-stolen-identities">Criminals target freight with fake IDs, spoofed emails and stolen identities</a> appeared first on <a href="https://www.freightwaves.com">FreightWaves</a>.</p>”
- “<figure><div><img src="https://imgproxy.divecdn.com/-lI3LJwJEMI3XZjd_Bf7lTs3RTbSgquf5Xp2UiR5-P0/g:nowe:0:0/c:3747:2117/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0xMzk5NDc2OTU1LmpwZw==.webp" /></div></figure><p>Maintaining on-time delivery promises will keep shoppers coming back, but fast shipping still has a role to play, retail leaders said at Home Delivery World 2026.</p>”
- “<p>Spend a day on any interstate in this country and you will lose count. Trucks rolling down the highway with the company name scrawled on the door in black marker. USDOT numbers handwritten so small you would have to be parked next to the truck to read them. Letters smeared, crooked, half peeled off, applied […]</p> <p>The post <a href="https://www.freightwaves.com/news/black-marker-magnetic-signs-and-peeling-decals-here-is-what-49-cfr-390-21-actually-requires">Black Marker, Magnetic Signs, and Peeling Decals: Here Is What 49 CFR 390.21 Actually Requires.</a> appeared first on <a href=”
Geospatial data
这表明 Quicargo 在欧洲国家拥有广泛的运营足迹，为底层移动数据提供了广阔的地理范围，对于地理空间AI和区域物流分析至关重要。
API access
此证据证实了 Quicargo 强大的API集成能力，表明其为自动化货运管理提供了结构化且易于访问的数据环境，对于需要程序化数据访问的AI系统极具价值。
Knowledge base / docs
这指的是 Quicargo 的文本知识库，提供有关物流运营、术语和支持的上下文信息，可以丰富理解或训练NLP模型以获取领域特定洞察。
IoT / sensor data
这强调了通过 Quicargo 的跟踪与追溯系统收集的关于货物位置、状况和预计到达时间的实时跟踪数据，为预测分析和动态物流优化提供了关键的时间序列数据。
Transaction data
这证实了历史运输订单数据的可用性，包括调度、运输和交付详情，对于绩效分析、路线优化和识别长期运营模式至关重要。
Industrial data
这概述了 Quicargo 通过填充空载卡车来优化公路运输的核心使命，这意味着其拥有关于运营效率和资源利用的数据，对于专注于可持续性和运力管理的AI模型具有价值。
Data-volume signal
这量化了 Quicargo 显著的运营规模，连接了3,000多家企业与来自270家承运商的6,000多辆卡车，强调了专有数据集在大型AI应用中的广度和深度。
Marketplace
Dataset details
Geographic coverage
Europe
Time range
Real-time and historical
Update frequency
Real-time
Delivery
API
Formats
Tabular
License
One-time license for Geo AI and mobility analytics use cases.
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, real-time mobility and geospatial dataset offers granular insights into European road freight, driven by high volume from 6,000+ trucks and 270 carriers. Its value is amplified by the rapidly growing Geo AI market, demanding precise location-based intelligence for logistics optimization.
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
Quicargo Mobility & Geospatial — a Large mobility & geospatial dataset (Tabular modality) in the mobility domain. Primary AI use-case: Geo AI. Market signal: Global Geospatial Analytics Artificial Intelligence market = USD 47.76 billion in 2024, CAGR 25.71% (2025-2035). Investment score 75.4/100 (confidence 0.79). Recommended action: Data Sharing Agreement.
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