Dataset opportunity
Endurance Logistique — Industrial Operations Dataset Opportunity
Moderate industrial operations dataset held by Endurance Logistique, usable for Industrial Monitoring and Forecasting.
Score
66.1
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 Supply Chain Analytics market = $11.0 Billion in 2025, CAGR 15.85%.
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
Industrial Operations Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
Industrial AI integrators
Endurance Logistique holds a high-value Time Series dataset derived from its core industrial operations, encompassing granular `event_streams`, `industrial_data`, and `transaction_data`. This data provides a detailed, real-time chronicle of warehouse management (WMS) and transport management (TMS) activities, making it exceptionally well-suited for training and validating AI models for the Industrial Monitoring use case by offering a direct view into operational efficiency and asset performance.
This data is a strategic asset in the global Supply Chain Analytics market, which was valued at $11.0 Billion in 2025 and is projected to grow at a 15.85% CAGR. Despite access complexities—such as the need for heavy anonymization of end-customer PII, navigation of third-party carrier terms, and the fact that the data is originally siloed in WMS/TMS tools—its rarity and operational depth make it a premium resource for AI buyers seeking to develop advanced monitoring and optimization solutions. ⚠ Diligence (valuable data, access to negotiate): Data contains end-customer PII (names, addresses) requiring heavy anonymization; Shipping and carrier performance data may involve third-party carrier terms; Operational data is siloed within their WMS/TMS tools · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Evidence confirms Endurance Logistique possesses proprietary time-series data streams detailing its end-to-end industrial logistics operations, from warehouse management to final shipment. This dataset is a prime asset for Industrial AI integrators seeking to build and validate industrial monitoring and predictive optimization models. In a rapidly growing supply chain analytics market (forecasted at $11.0B by 2025), this high-rarity data provides a direct, real-world feed for training AI that can optimize inventory, predict shipment events, and improve overall operational resilience.
See dimension details ↓- Dataset Specificity90
dominant 'industrial_data', 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 Industrial Monitoring
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 very high, driven by the rapid growth of the Supply Chain Analytics market, which is expanding at a 15.85% CAGR.
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 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 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 Surplus70
surplus=medium — 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 French SME in e-commerce logistics is a good target as it generates significant operational data as a by-product of its core business and does not appear to be selling it as a product. Issues: The company has an integrated web agency, 'Endurance Développement', which creates e-commerce sites for clients. This service is complementary to their logistic; The company mentions using its own IT tools (EDI and WMS) and data synchronization modules, but this seems to be for internal efficiency and client integration,
- Deep Qualification80
⚠ needs review — Endurance Logistique is a 3PL service provider, making the data a byproduct of operations on behalf of its clients, who likely own the data, complicating any data monetization effort. [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.
Transaction data
This tabular data details e-commerce order fulfillment, capturing order preparation and multi-carrier shipping events valuable for analyzing fulfillment efficiency and carrier performance.
Event streams
This is a time-series feed of real-time shipment tracking data, including interfaces with core WMS/TMS systems, essential for building predictive models for delivery times and logistics monitoring.
Industrial data
This time-series data provides a granular view of internal warehouse operations, including inventory management, goods reception, and storage optimization, enabling AI applications that improve asset utilization and stock flow.
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
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Deliverable
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Endurance Logistique Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the mobility domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Supply Chain Analytics market = $11.0 Billion in 2025, CAGR 15.85% (source: IMARC Group). Investment score 66.1/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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