Dataset opportunity
Gastonschul — 法规记录数据集机会
Gastonschul 持有的海量法规记录数据集，可用于法规 RAG 和合规助手。
Score
73.9
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
63%
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
全球监管科技市场在 2025 年的估值为 190.6 亿美元，预计到 2034 年将增长到 1052.3 亿美元，复合年增长率为 20.00%（来源：Fortune Business Insights）。[8]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-12
Federal court temporarily upholds Trump’s 10% global tariff
supplychaindive.com ↗ - 📰press2026-06-11
Tariff refunds may soon cover more entries — but not without a fight
supplychaindive.com ↗ - 📰press2026-06-10
Razor reshapes supply chain to weather Trump-era China tariffs
manufacturingdive.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
法规记录数据集
Modality
文本
Sector
出行
Volume
大
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
主要归客户所有 — GDPR 敏感（PII 审查）
Buyer persona
监管科技与合规人工智能供应商
Gastonschul 持有一个监管记录数据集，其文本模态包含详细的报关单、交易数据、事件流和来自其移动和物流运营的地理数据。这种结构化和非结构化信息的丰富组合提供了复杂的国际贸易流动的真实世界证据，使其成为开发和微调监管 RAG 系统以回答细微的合规和海关查询的理想资产。
该数据的商业价值体现在蓬勃发展的RegTech 市场中，该市场在 2025 年的估值为 190.6 亿美元，预计在 2026 年至 2034 年期间的复合年增长率 (CAGR) 为 20.00%。[8] 虽然访问受到严格的海关保密法规的约束并需要数据匿名化，但这种真实世界交易数据的稀有性和深度为旨在构建高价值解决方案的 AI 买家在利润丰厚的贸易合规领域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）：数据受严格的海关保密和财政代表法规约束；主要数据所有权归进出口客户所有；需要对 PII（姓名、地址）和敏感商业价值进行匿名化。· 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 Gastonschul 拥有欧洲海关和监管合规活动的专有运营数据集。数据源自其管理数千份跨境申报的核心业务，包括与碳边境调节机制 (CBAM) 等新兴法规相关的文本。这个高稀有度的数据集是 RegTech 和合规 AI 供应商寻求训练和支持监管 RAG 模型的主要资产，这在全球 RegTech 市场（预计到 2034 年将超过 1000 亿美元）中至关重要。
See dimension details ↓- Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Dataset Specificity100
主导的“监管”，移动行业，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 Volume80
5 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. - Training Value94
适用于监管 RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand82
全球 RegTech 市场预计将从 2026 年到 2033 年以 21.1% 的复合年增长率增长，这得益于对自动化合规流程和人工智能采用日益增长的需求，表明在以下行业对监管数据有非常高的需求：
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/受监管
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
高难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength86
5 种证据类型，5 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License0
所有权=客户拥有，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 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，3 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 Audit67
⚠ 审查 — Gaston Schul 的核心业务是销售海关相关服务和数字解决方案，包括数据交换平台，使其成为情报的销售商，因此不是一个好的目标。问题：该公司的核心业务是提供海关服务和数字解决方案，而不是非数据相关的运营业务。[7, 13]；他们积极销售数字解决方案，包括通过 API/EDI 的“海关数据交换”、一个“出口门户”和一个“控制塔”平台，这些都是销售形式
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
这是来自中央“控制塔”的地理空间物流数据，证明持有者管理和整合了跨多个欧洲国家的全球海关活动。
Event streams
这是来自数字海关平台的实时事件数据，提供了申报流程的时间序列视图，对于对风险和运营效率进行建模很有价值。
Transaction data
这是详细的海关交易数据，包含HS 编码、原产地和估值等基本字段，这些是训练任何贸易合规 AI 的基础。
Regulatory records
这是专有的监管尽职调查文本，直接与新的复杂欧洲法规（如CBAM 和森林砍伐法规）相关，代表了训练下一代合规模型的独特来源。
Data-volume signal
这些证据表明数据量巨大，证实了在包括英国、德国和法国在内的主要欧洲市场处理的数千份申报的生产级规模。
Marketplace
Dataset details
Geographic coverage
Global (primarily Europe for customs declarations)
Time range
Real-time (rolling)
Update frequency
Real-time
Delivery
API / S3 bucket
Formats
Text, Geo-data
License
One-time license for internal use, RAG model training and fine-tuning, and compliance query answering. Restrictions on redistribution and public disclosure apply.
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 dataset's value is driven by its high rarity, proprietary nature, and direct application to the rapidly growing RegTech market, specifically for Regulatory RAG systems. The real-time, large volume of operational customs and transactional data, including emerging regulations like CBAM, makes it a critical asset for compliance and customs intelligence.
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
Gastonschul Regulatory Records — a Large regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global RegTech market was valued at USD 19.06 billion in 2025 and is projected to grow to USD 105.23 billion by 2034, at a CAGR of 20.00% (source: Fortune Business Insights). [8]. Investment score 73.9/100 (confidence 0.63). Recommended action: Data Sharing Agreement.
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