Dataset opportunity
Imperativelogistics — Mobility Event Dataset Opportunity
Moderate mobility event dataset held by Imperativelogistics, usable for Forecasting and Anomaly Detection.
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
Partnership (group-level)
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 was valued at $10.02 billion in 2025, with a projected CAGR of 15.8% (2026-2035).
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-09-06
Borderlands Mexico: Trucker protest raises stakes in Mexico-US B-1 visa dispute
freightwaves.com ↗ - 📰press2026-09-04
Logistics provider accuses Alabama carrier of raiding its workforce, stealing trade secrets
freightwaves.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
Mobility Event Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — licensing rights to clarify
Buyer persona
Quant funds & demand-forecasting AI teams
Imperativelogistics holds a proprietary Mobility Event Dataset structured as a Time Series. This dataset is compiled from internal business_records, real-time event_streams, and geo_data, offering detailed insights into aggregated lane performance. Its modality is ideal for training AI models for Forecasting applications, such as predicting transit times, identifying potential delays, and optimizing routes.
The value of such data is reflected in the global supply chain analytics market, which was valued at $10.02 billion in 2025 and is projected to grow with a CAGR of 15.8%. [1] While access requires navigating a corporate structure resulting from a private equity acquisition and data fragmentation across brands like DLS Worldwide, the proprietary nature of the aggregated performance data makes it a valuable asset for buyers seeking a competitive edge in logistics optimization. ⚠ Diligence (valuable data, access to negotiate): Data is likely fragmented across multiple brands including DLS Worldwide and Imperative Expedited.; Ownership of specific cargo details may be restricted by shipper contracts, but aggregated lane and performance data is proprietary.; Acquired by private equity (LaSalle Capital) and merged with other entities, making corporate navigation necessary. · corporate: subsidiary of Imperative Logistics Group.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Imperativelogistics possesses a proprietary, high-rarity dataset detailing multi-modal logistics events, including granular transit durations and cross-border performance. This type of time-series data is sought after by quant funds and AI teams to power sophisticated forecasting models that predict supply chain disruptions and efficiencies. In a global supply chain analytics market projected to grow at over 15% annually, this dataset offers a distinct competitive edge for modeling demand and carrier performance.
See dimension details ↓- Dataset Specificity78
dominant 'event_streams', 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 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 Value74
fit for Forecasting
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 high, driven by the significant growth in the supply chain analytics market (CAGR 15.8%) where **Forecasting** is a critical capability for optimization and efficiency. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
restricted/unknown
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility15
medium difficulty, subsidiary of Imperative Logistics Group
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=company_owned, licensing=rights_unclear
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
subsidiary of Imperative Logistics Group
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 Surplus92
surplus=high, 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 — Imperative Logistics is a private, medium-sized operational logistics company whose core business is freight forwarding, generating a significant volume of proprietary shipping and tracking data as a byproduct, making it an ideal target. Issues: A single third-party profile on Preqin vaguely describes them as a 'technology solutions provider' with a subscription model, which conflicts with all other evi; The 'Mobility Event Dataset' mentioned in the prompt is not publicly listed, suggesting it is a dormant data asset.
- Deep Qualification80
⚠ needs review — The target is a logistics service provider whose business model generates the specified dataset, but its privacy policy explicitly prohibits selling personal information, posing a significant restriction on data licensing. [licensing restricted]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
business_records
These business records contain structured details on time-sensitive shipments, providing ground-truth data on transit durations and delay factors crucial for training risk-assessment models.
Geospatial data
This tabular data provides proprietary intelligence on US-Mexico-Canada shipping lanes, offering a unique view into customs clearance times and carrier efficiency for optimizing North American trade routes.
Event streams
These event streams contain the core time-series data, capturing both historical and real-time status updates across global transport modes to directly feed predictive forecasting models.
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
Imperativelogistics Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global supply chain analytics market was valued at $10.02 billion in 2025, with a projected CAGR of 15.8% (2026-2035) (source: Market Research Future). [1]. Investment score 66.1/100 (confidence 0.49). Recommended action: Partnership (group-level).
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