Dataset opportunity
Epostglobalshipping — Transaction Dataset Opportunity
Large transaction dataset held by Epostglobalshipping, usable for Recommendation Models and Fraud Detection.
Score
63.8
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
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 AI in logistics and supply chain market = $20.1B in 2024, CAGR 25.9%. [1, 7].
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
Acquisition by JZ Partners and Edgewater Capital to scale tech-enabled logistics
source ↗
Profile
Dataset profile
Type
Transaction Dataset
Modality
Tabular
Sector
mobility
Volume
Large
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
E-commerce & personalization AI teams
Epostglobalshipping holds a large-scale Tabular transaction_data dataset, which includes rich geo_data and a proprietary knowledge_base. This data is aggregated from over 100 third-party carriers, providing a rare, comprehensive view of mobility patterns, making it exceptionally well-suited for training advanced Recommendation Models for logistics optimization.
The AI in logistics market is valued at $20.1 billion in 2024 and is projected to grow at a CAGR of 25.9%, indicating massive business value and demand. [1, 7] Despite access complexities, such as the data containing PII that requires anonymization, a proprietary orchestration layer, and the need for high-level corporate approval from its private equity owners, the rarity and scale of this aggregated dataset offer a significant competitive advantage in a rapidly expanding market. ⚠ Diligence (valuable data, access to negotiate): Data contains PII (names, addresses) requiring anonymization for AI use cases.; Proprietary orchestration layer aggregates data from 100+ third-party carriers.; Owned by private equity (JZ Partners/Edgewater), might require high-level corporate approval. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Epostglobalshipping owns a proprietary, high-rarity dataset of 23.3 million actual international shipment outcomes across more than 200 countries. This granular, transaction-level data is a critical asset for e-commerce AI teams looking to build sophisticated recommendation models for shipping and logistics. In a global AI logistics market projected to reach $20.1 billion in 2024, this dataset offers a unique opportunity to optimize carrier performance, predict delivery times, and enhance the customer experience at scale.
See dimension details ↓- Dataset Specificity78
dominant 'transaction_data', sector mobility, 2 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume74
4 evidence hits, explicit data-volume mention
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 Value74
fit for Recommendation Models
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 global AI in logistics market's rapid expansion, which is valued at $20.1B and growing at a 25.9% CAGR. [1, 7]
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
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 evidence types, 4 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 Orientation39
1 data-appetite signals (1 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high — 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 Audit92
✓ good target — This is a good target; it's a privately held, operational logistics/shipping company that generates valuable transactional data as a by-product of its core business and does not appear to sell data as a product. Issues: Some user reviews on BBB and Reddit express frustration with customer service and package tracking, suggesting potential operational inefficiencies. [21, 22]; Scam Detector gives the website a medium trust score of 52.8/100, citing a lack of metadata and poor desi
- Deep Qualification90
✓ pass — ePost Global is a logistics services provider, not a data seller. It holds a valuable, aggregated transaction dataset as a byproduct of its core operations, but this data contains PII and is subject to complex usage rights and privacy regulations, making direct access for AI training challenging.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Knowledge base / docs
The evidence points to a specialized knowledge base covering the complex rules of international shipping, a valuable asset for training models to automate customs and duties compliance.
Transaction data
This is the core tabular dataset, capturing granular shipment-level performance data across carriers and destinations, which is essential for training logistics recommendation models.
Data-volume signal
This confirms the dataset's significant scale, representing the complete outcomes of 23.3 million shipments, which provides the comprehensive, unbiased ground truth needed to train high-performing AI models.
Geospatial data
This tabular data confirms the dataset's extensive global footprint, covering a proprietary logistics network of over 200 countries, which is critical for modeling and optimizing the international supply chain.
Marketplace
Dataset details
Geographic coverage
Global (200+ countries)
Time range
Actual international shipment outcomes (specific years not stated, but implied historical)
Update frequency
Periodic
Delivery
API or secure file transfer (inferred due to PII and propr
Formats
Tabular
License
One-time license for use in recommendation models for logistics optimization, subject to PII anonymization and proprietary orchestration.
Personal data
Contains 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 high rarity, large volume of granular international shipment outcomes, and direct applicability to the rapidly growing AI in logistics market drive its significant valuation. Demand is high for training recommendation models in this sector.
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
Epostglobalshipping Transaction — a Large transaction dataset (Tabular modality) in the mobility domain. Primary AI use-case: Recommendation Models. Market signal: Global AI in logistics and supply chain market = $20.1B in 2024, CAGR 25.9% (source: Precedence Research). [1, 7]. Investment score 63.8/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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