Dataset opportunity
Supplychainsolution — Regulatory Records Dataset Opportunity
Moderate regulatory records dataset held by Supplychainsolution, usable for Regulatory RAG and Compliance Copilots.
Score
64.4
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
49%
Action
Data Sharing Agreement
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)
Global Artificial Intelligence in Supply Chain market = $5.1B in 2023, CAGR 38.9%. [1, 5].
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-31
Comércio acelera em junho com retalho a crescer 3%
distribuicaohoje.com ↗ - 📰press2026-07-24
Produção nacional representa mais de 60% da oferta de frescos do Intermarché
logisticamoderna.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.
Profile
Dataset profile
Type
Regulatory Records Dataset
Modality
Text
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
RegTech & compliance-AI vendors
Supplychainsolution holds a Regulatory Records Dataset in Text modality, which uniquely combines regulatory filings with IoT data and transactional records from its mobility operations. This rich, multi-source dataset is specifically structured for a Regulatory RAG use case, enabling an AI to answer complex compliance and logistics queries by grounding responses in verified operational and legal documents.
The business value is substantial, targeting the global AI in Supply Chain market, which was valued at USD 5.1 billion in 2023 and is projected to grow at a remarkable 38.9% CAGR through 2030. [1, 5] While access requires careful handling due to client shipment details, PII under GDPR, and customs data restrictions, the rarity and comprehensiveness of this dataset offer a significant competitive advantage in a market rapidly adopting AI for efficiency and transparency. [1] ⚠ Diligence (valuable data, access to negotiate): Data includes client shipment details requiring anonymization; E-commerce fulfillment data contains PII (names/addresses) subject to GDPR; Customs data may have regulatory sharing restrictions · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Supplychainsolution generates a proprietary data trail across the full logistics lifecycle, from e-commerce orders to final customs clearance. The resulting dataset of regulatory records, uniquely contextualized by real-world transactional and IoT data, is of exceptionally high value. For RegTech vendors, this is a rare opportunity to acquire the ground-truth data needed to build powerful Regulatory RAG systems and capture a share of the booming AI in Supply Chain market, which is projected to grow at nearly 40% annually.
See dimension details ↓- Dataset Specificity90
dominant 'regulatory', sector mobility, 3 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Regulatory RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI buyer demand is exceptionally high, driven by the market's explosive growth, which is projected to expand at a 38.9% CAGR as companies race to deploy AI for supply chain optimization. [1, 5]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
low difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
ownership=mixed, licensing=gdpr_sensitive
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 data-appetite signals (0 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
surplus=medium, 2 recent external signals — proprietary data beyond what's already monetised
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
✓ good target — This UK-based freight forwarder and logistics company, established in 2007, appears to be an ideal target, as its core business is operational logistics, which generates valuable data as a by-product without any indication that they are currently selling this data.
- Deep Qualification80
⚠ needs review — The target is a logistics services provider, not a data seller. The 'Regulatory Records Dataset' is a plausible byproduct of its core business in global food/drink logistics, which involves extensive compliance and customs documentation. However, this data is owned by its clients and is subject to GDPR and other restrictions, with no specific trigger identified for a change in data strategy. [data is owned by the company's customers]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
The company generates time-series data from the real-time tracking of goods across sea, air, and road, providing physical ground-truth valuable to logistics and insurance platforms.
Transaction data
This evidence indicates the holder processes high-frequency e-commerce transactions, creating valuable tabular data on order fulfillment and delivery patterns for demand forecasting.
Regulatory records
The holder possesses a proprietary, structured text dataset derived from its customs clearance services, containing critical fields like commodity codes and tax valuations essential for training compliance AI.
Marketplace
Dataset details
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
Supplychainsolution Regulatory Records — a Moderate regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global Artificial Intelligence in Supply Chain market = $5.1B in 2023, CAGR 38.9% (source: Grand View Research). [1, 5]. Investment score 64.4/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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