Dataset opportunity
Nesslog — 监管记录数据集机会
Nesslog 持有的中等监管记录数据集，可用于监管 RAG 和合规助手。
Score
63.3
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
42%
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
全球监管科技中的人工智能市场到 2035 年将达到 1442.6 亿美元，复合年增长率为 22.80%（2026-2035）（来源：Precedence Research）
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
监管记录数据集
Modality
文本
Sector
mobility
Volume
中等
Freshness
定期
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 受限
Buyer persona
RegTech 和合规 AI 供应商
Nesslog 持有一个由文本格式的海关和物流文件组成的监管记录数据集。这些数据以 `industrial_data` 和 `regulatory` 证明为依据，为训练和运行监管 RAG 系统提供了丰富的基础。它包含海关申报、合规备案和运输法规的真实案例，对于准确的 AI 驱动的查询响应至关重要。
全球监管科技中的人工智能市场预计到2035 年将达到 1442.6 亿美元，复合年增长率为 22.80%。[9] 这表明对能够为合规性人工智能提供支持的数据有着巨大的需求。尽管存在税务保密和共享所有权等访问复杂性，但这种匿名海关数据的稀缺性和高价值使其成为寻求在自动化监管导航中获得竞争优势的买家的战略资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：海关数据受严格的财政和法律保密（税务保密）约束；数据所有权可能与进出口客户共享；需要高级匿名化以删除商业秘密和个人身份信息。· 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 Nesslog 持有一个国际海关记录的专有数据集，该数据集直接源自其核心物流业务。这些数据包含HS 编码和原产地/目的地信息等详细信息，非常适合构建高级监管 RAG 系统的 RegTech 供应商。在预计将达到 1442.6 亿美元的人工智能合规市场中，该数据集提供了一个独特的地面实况数据来源，为自动化跨境贸易和物流的下一代工具提供支持。
See dimension details ↓- Training Value74
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. - Dataset Specificity78
主导的“监管”，行业 mobility，2 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 Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume46
2 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness46
定期
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Buyer Demand92
人工智能买家需求极高，这得益于人工智能监管科技市场的快速增长（复合年增长率 22.80%）以及对专业数据以支持自动化合规解决方案的需求。[9]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility24
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 Strength50
2 种证据类型，2 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License32
所有权=混合，许可=受限
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 Orientation50
2 个数据胃口信号（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 — 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 Audit67
✓ 良好目标 — Nesslog 是一家德国物流和海关咨询公司，不拥有实体资产，但为客户管理物流，这可能（尽管不明确）产生有价值的监管和运营数据副产品。问题：公司的核心业务是提供服务（咨询、报关、服务提供商管理），而不是实体运营业务，该业务产生；通过其管理和咨询活动生成的数据（例如，流程描述、服务水平协议、海关申报）是否不清楚；公司明确表示没有自己的车队或仓库，而是为客户采购这些服务。[3, 4, 8]
- Deep Qualification90
⚠ 需要审查 — Nesslog 是一家海关和物流服务提供商，而非数据经纪人。它作为其核心业务的副产品，拥有一个看似合理的“监管记录数据集”，但这些数据归其客户所有，并受到严格的保密和数据保护法规的约束，这对其商业化构成了重大障碍。[数据归公司客户所有；许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Regulatory records
这些证据证实持有者拥有国际海关申报的文本记录，包括用于商品分类的HS 编码等具体细节——这是训练人工智能模型理解跨境贸易合规细微之处的非常有价值的资产。
Industrial data
这些证据指向关于货物跟踪和承运商绩效的运营时间序列数据，这些数据是生成主要监管记录的真实物流活动的底层证明，验证了其真实性和来源。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Nesslog Regulatory Records — a Moderate regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global AI in Regulatory Technology market to reach $144.26 billion by 2035, CAGR 22.80% (2026-2035) (source: Precedence Research). Investment score 63.3/100 (confidence 0.42). Recommended action: Data Sharing Agreement.
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