Dataset opportunity
Mt Logistik — Regulatory Records Dataset Opportunity
Moderate regulatory records dataset held by Mt Logistik, usable for Regulatory RAG and Compliance Copilots.
Score
68.6
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
Acquire
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 Big Data in Logistics Market = $4.3B in 2023, CAGR 21.5%.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-19
L’ONG Solidarités International planifie par scénarios avec Anaplan
supplychainmagazine.fr ↗ - 📰press2026-06-19
Blyyd lève 5 M€ pour conquérir l’Europe
supplychainmagazine.fr ↗ - 📰press2026-06-19
La Poste entreprend une plateforme multiflux de 4.900 m² en Moselle
supplychainmagazine.fr ↗ - 📰press2026-06-19
Sophie Pietremont à la tête du marketing de Generix
supplychainmagazine.fr ↗ - 📰press2026-06-19
Citylogin pérennise son emploi du métro pour livrer à Madrid
supplychainmagazine.fr ↗
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
Regulatory Records Dataset
Modality
Text
Sector
mobility
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — licensing rights to clarify · PII/regulated
Buyer persona
RegTech & compliance-AI vendors
Mt Logistik possesses a Regulatory Records Dataset in Text modality, comprising extensive industrial_data, proofs of regulatory compliance, and transaction_data. This collection is exceptionally suited for a Regulatory RAG use case, as it contains the specific, real-world documentation—such as customs filings and shipment manifests—required to train an AI to accurately navigate the complex web of international logistics regulations.
The business value is substantial, situated within the Big Data in Logistics Market, which was valued at $4.3B in 2023 and is projected to grow at a 21.5% CAGR. [11] While access complexities exist—customs data is subject to strict Zollabfertigung oversight, shipment details may require client anonymization, and operational data might be in legacy systems—these challenges underscore the data's rarity and value. For an AI buyer, acquiring this difficult-to-replicate dataset represents a significant competitive moat. ⚠ Diligence (valuable data, access to negotiate): Customs data is subject to strict regulatory oversight (Zollabfertigung).; Shipment-specific data may require anonymization to decouple from specific client identities.; Operational data is likely stored in legacy freight management systems. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Mt Logistik possesses a proprietary dataset detailing over two decades of complex, international customs clearance and logistics operations. This high-rarity text data is a critical asset for RegTech and compliance-AI vendors seeking to train regulatory RAG models on real-world documentation. In a global logistics data market projected to grow at over 21% annually, this dataset offers a unique, operational view of international trade compliance, spanning air, sea, and road transport.
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 Freshness46
periodic
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 extremely high, driven by the need for specialized, industry-specific data to power applications in a market growing at a 21.5% CAGR. [11]
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 License70
ownership=owned, licensing=rights_unclear
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 Orientation56
2 data-appetite signals (2 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 5 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 is a perfect target: a contactable, operational SME in logistics whose core business is moving goods, not selling data, which means its operational data is a dormant, valuable by-product.
- Deep Qualification90
✓ pass — The target is a logistics service provider whose customs clearance services plausibly generate the hypothesized regulatory dataset; however, this data is a byproduct of its core business, not a product, and is subject to significant GDPR and regulatory restrictions, with no recent strategic trigger
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Transaction data
This tabular data documents over two decades of global transport history, providing a rare, long-term view of logistics transactions across all continents for market and trend analysis.
Regulatory records
This core text dataset originates from a specialized customs clearance department, containing proprietary documentation on complex international trade regulations essential for training and validating compliance AI.
Industrial data
These time-series logs from warehouse management detail physical resource allocation and storage, offering a ground-truth layer of operational efficiency data for supply chain optimization models.
Marketplace
Dataset details
Geographic coverage
Global
Time range
Over two decades
Update frequency
Periodic
Delivery
API or CSV export
Formats
Text
License
One-time license for internal use, AI model training, and regulatory compliance applications. Restrictions on redistribution.
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 proprietary dataset of regulatory compliance and transaction records for international logistics is highly valuable for AI training in a rapidly growing market. Its rarity and specific use-case for Regulatory RAG drive significant demand.
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
Mt Logistik Regulatory Records — a Moderate regulatory records dataset (Text modality) in the mobility domain. Primary AI use-case: Regulatory RAG. Market signal: Global Big Data in Logistics Market = $4.3B in 2023, CAGR 21.5% (source: Global Market Insights, Inc.). Investment score 68.6/100 (confidence 0.49). Recommended action: Acquire.
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