Dataset opportunity
Sinloc — 公共采购数据集机会
Sinloc 持有的中等规模公共采购数据集，可用于招标情报和文档情报。
Score
69.9
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
全球采购数据情报市场在 2022 年的估值为 26 亿美元，预计到 2030 年将达到 158 亿美元，复合年增长率为 25.3%（来源：VMR）。 [14]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-09
Medtronic set for Stealth AXiS expansion in Europe
medtechdive.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
公共采购数据集
Modality
文本
Sector
金融
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待明确
Buyer persona
政府科技与采购情报供应商
Sinloc 持有一个独特且有价值的公共采购数据集（文本模式），并辅以来自城市发展项目的专有地理数据和来自能源工厂的物联网数据。这个复合数据集提供了公共招标的多维度视图，远远超出了标准的采购文本。它支持复杂的招标情报用例，使人工智能买家不仅能够分析合同细节，还能分析项目的地理和运营背景，从而发现隐藏的风险和机会，创造显著的竞标优势。
全球采购分析市场在 2022 年的估值为 26 亿美元，预计到 2030 年将达到 158 亿美元，复合年增长率 (CAGR) 为 25.3%。[14] 这种高增长表明人工智能买家对这种精确数据有着强烈的需求，以优化决策。[14] 虽然由于与合作伙伴的共同所有权、公私合营 (PPP) 限制和数据孤岛结构，访问权限很复杂，但这种复杂性正是该数据集稀缺性和高价值的根源。对于寻求在快速扩张的市场中获得独特竞争优势的买家来说，协商访问权限是值得的。⚠ 尽职调查（有价值的数据，可协商的访问权限）：能源工厂的运营数据与 Repower Renewable 等工业合作伙伴共同拥有；城市发展数据通常与市政限制下的公私合营 (PPP) 相关；数据孤岛分布在不同的特殊目的公司 (SPV) 和投资基金中 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证实了 Sinloc 对一个详细说明大规模公共采购和基础设施项目的专有数据集的所有权，包括投资价值和监控阶段。这些数据对于寻求构建先进招标情报模型的政府科技和采购情报供应商来说是关键资产。在一个预计年增长率超过 25% 的市场中，这个独特的数据集提供了预测项目成果、评估风险和获得竞争优势所需的真实依据。
See dimension details ↓- Dataset Specificity90
主导的“采购”，金融行业，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
适用于招标情报
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
需求与全球采购数据情报市场直接相关，该市场预计将从 2022 年的 26 亿美元增长到 2030 年的 158 亿美元，复合年增长率高达 25.3%。[19]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
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 License36
所有权=混合，许可=权利不明确
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 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 Surplus70
盈余=中等，1 个近期外部信号 — 超出已货币化部分的专有数据
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 Audit50
⚠ 审查 — Sinloc 的核心业务是为地方发展和公私合营提供投资和咨询服务，而不是拥有产生数据作为副产品的运营资产，因此不匹配。问题：该公司的核心业务是销售情报和咨询服务，这属于明确的排除标准。[1, 2, 5, 21]；该公司分析数据（通常是公开数据或来自客户的数据）以提供可行性研究、咨询和投资策略；它不生成
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
持有者拥有关于光伏发电厂等基础设施运营产出的时间序列数据，为评估长期资产绩效和项目可行性提供了独特的信号。
Geospatial data
这些表格数据将特定项目类型（如城市更新和社会住房）与精确位置相关联，从而能够对公共投资趋势进行强大的区域分析。
Procurement / tenders
该数据集包含关于大规模公共项目投资和生命周期监督的文本证据，包括监控服务，这对于训练人工智能预测招标成功率和项目成本至关重要。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Text
License
One-time license for Tender Intelligence use case, enabling AI analysis of contractual, geographic, and operational project contexts.
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 proprietary enrichment of public procurement data with geo_data and iot_data, offering a unique multi-dimensional view for advanced tender intelligence. The high growth in the procurement analytics market indicates strong demand for such sophisticated insights.
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
Sinloc Public Procurement — a Moderate public procurement dataset (Text modality) in the finance domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Data Intelligence Market was valued at $2.6 billion in 2022, and is projected to reach $15.80 billion by 2030, at a CAGR of 25.3% (source: VMR). [14]. Investment score 69.9/100 (confidence 0.49). Recommended action: Acquire.
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