Dataset opportunity
Radiantnuclear — 监管记录数据集机会
Radiantnuclear 持有的中等监管记录数据集，可用于监管 RAG 和合规助手。
Score
76.2
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 size (indicative estimate)
全球监管事务人工智能市场 = 2024 年为 13.1 亿美元，年复合增长率为 18.60%（来源：Grand View 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.
- 📣Press / announcement
筹集了 4000 万美元 B 轮融资，以加速 Kaleidos 微型反应堆的开发和测试
source ↗
Profile
Dataset profile
Type
监管记录数据集
Modality
文本
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 受限
Buyer persona
监管科技与合规人工智能供应商
Radiantnuclear 拥有一个专门的文本模态数据集，由监管记录、事件流和工业物联网数据组成。这个证据集合经过独特构建，可支持监管 RAG 用例，从而实现对复杂核合规信息和运营遥测数据的先进 AI 驱动分析。
商业价值巨大，触及全球监管事务中的人工智能市场，该市场在2024 年的估值为13.1 亿美元，预计将以 18.60% 的复合年增长率增长。尽管存在NRC 监管和ITAR/EAR 控制等访问复杂性，但该数据的稀有性和深度，特别是专有的TRISO 燃料性能指标，为在严格的核监管环境中导航的 AI 买家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）：核监管机构（NRC）的监管可能限制数据共享；国家安全和出口管制（ITAR/EAR）对反应堆遥测的影响；数据目前处于开发/测试阶段（燃料测试计划于 2026 年进行）；专有的 TRISO 燃料性能指标高度敏感 · 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 Radiantnuclear 拥有详细说明创新核反应堆设计如何获得监管批准的专有文件。这个基于文本的数据集是 RegTech 和合规 AI 供应商构建监管 RAG 系统以驾驭复杂工业领域的宝贵资产。在全球监管事务中的人工智能市场预计到 2024 年将达到 13.1 亿美元，并且年增长率超过 18%，这个专有数据集为训练专业AI 模型提供了独特的竞争优势。
See dimension details ↓- Dataset Specificity100
主导的“监管”，工业领域，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
适用于监管 RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
买家需求旺盛，这得益于监管事务中的人工智能市场快速增长的 18.60% 的复合年增长率，这产生了对专业、高价值数据以训练和支持先进合规模型的强烈需求。
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 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 License66
所有权=拥有，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 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 — 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 Audit92
✓ 好目标 — 优秀目标：Radiant Nuclear 是一家制造便携式微型反应堆的硬件公司，它产生的海量运营、测试和监管数据是其核心业务的副产品，而不是其主要产品。问题：该公司资金充足且增长迅速，可能很快会超出中小企业类别；初始提示提到了“监管记录数据集”，这似乎是误解；该公司在过程中生成监管文件
- Deep Qualification90
⚠ 需要审查 — Radiant 是一家开发便携式微型反应堆的硬件公司，而不是数据销售商。它作为副产品生成运营和监管数据，这对于“监管 RAG”来说是合理的，但受到 NRC 和 ITAR/EAR 控制的高度限制，使得商业化复杂化。[许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<figure><div><img src="https://imgproxy.divecdn.com/dpiVgKtlIMKJFC4tCdas8ADiOeoCJE5WEtYsN5tMbSw/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9HZXR0eUltYWdlcy0yMjU5Nzg0MzIwLmpwZw==.webp" /></div></figure><p>The companies said the deal marks Walmart’s first nuclear power purchase agreement and is “among the first of its kind between a large retailer and a nuclear energy facility in the United States.”</p>”
- “<p>Proxima Fusion, a Munich, Germany-based group that is considered among the leading European companies working on fusion energy, said it completed a €411 million ($468 million) funding round. Proxima on July 7 said investors included technology giant Google along with global energy company RWE.</p> <p>The post <a href="https://www.powermag.com/google-invests-in-468-million-funding-round-for-german-fusion-group/">Google Invests in $468-Million Funding Round for German Fusion Group</a> appeared first on <a href="https://www.powermag.com">POWER Magazine</a>.</p> <p><img alt="Proxmia Fusion" cla”
- “<p>Aalo Atomics’ Aalo-X Critical Test Reactor (CTR)—dubbed “Project First Light”—has reached criticality at Idaho National Laboratory (INL), marking the fourth Department of Energy (DOE)–authorized advanced reactor startup under the federal push to accelerate reactor testing and demonstration. The U.S. Department of Energy (DOE) said July 6 that Aalo’s test reactor, which DOE referred to as […]</p> <p>The post <a href="https://www.powermag.com/aalo-atomics-test-reactor-reaches-criticality-at-inl-fourth-doe-authorized-advanced-reactor-by-july-4/">Aalo Atomics’ Test Reactor Reaches Critica”
Event streams
这些证据指向来自集中监控系统的时间序列数据，对于开发工业车队预测性维护或运营效率模型的 AI 供应商来说很有价值。
IoT / sensor data
持有者从涡轮机械等核心反应堆组件生成时间序列物联网数据，这对于训练优化性能和确保设备健康的 AI 模型至关重要。
Industrial data
这表明存在与TRISO 燃料等先进材料的制造和工厂测试相关的工业数据，这是供应链和质量控制 AI 应用的关键输入。
Regulatory records
这些基于文本的证据直接将特定工程设计（如被动冷却）与简化监管批准的过程联系起来，使其成为训练监管 RAG 系统的主要来源。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Radiantnuclear Regulatory Records — a Moderate regulatory records dataset (Text modality) in the industrial domain. Primary AI use-case: Regulatory RAG. Market signal: Global AI in Regulatory Affairs market = $1.31B in 2024, CAGR 18.60% (source: Grand View Research). Investment score 76.2/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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