Dataset opportunity
Horizonfastfreight — Mobility & Geospatial Dataset Opportunity
Moderate mobility & geospatial dataset held by Horizonfastfreight, usable for Geo AI and Routing & Forecasting.
Score
68.4
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
58%
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
Global Geospatial Analytics market = $117.30 billion in 2026, CAGR 12.90% (source: Fortune Business Insights)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-14
BulkLoads expands ag freight footprint with Livestock Network acquisition
freightwaves.com ↗ - 📰press2026-07-14
NEW: Trade turbulence turns to record volume for top U.S. port
freightwaves.com ↗ - 📰press2026-07-14
Fuel surcharges push parcel shipping rates near record high
freightwaves.com ↗ - 📰press2026-07-14
Should the Postal Service reassess its UPS air contract?
supplychaindive.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 & Geospatial Dataset
Modality
Tabular
Sector
mobility
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — clean to license · PII/regulated
Buyer persona
Geospatial-AI & mobility-analytics teams
Horizonfastfreight holds a valuable Mobility & Geospatial Dataset in Tabular format, containing granular geo_data, transaction_data, and industrial client information. This rich combination of operational evidence provides the raw material for sophisticated Geo AI applications, such as logistics optimization, supply chain analysis, and predictive demand modeling within specific territories and industries.
The global Geospatial Analytics market is estimated at $117.30 billion in 2026, with a projected 12.90% CAGR, underscoring the high value of this data class. While the data requires technical extraction from third-party dispatching software and includes information from carrier partners, its rarity and the direct access to the company's President for negotiation make it a compelling asset for AI buyers seeking a unique competitive advantage. ⚠ Diligence (valuable data, access to negotiate): Data is likely managed via third-party dispatching software, requiring technical extraction.; As a broker, some shipment data involves third-party carrier partners.; Direct access to decision-makers (President) is feasible for a family-owned SME. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
The evidence confirms Horizon Fast Freight owns a proprietary dataset detailing cross-border freight logistics, specifically focused on the Canada-USA trade corridor. This tabular data captures shipment routes, carrier performance, and delivery outcomes across various shipping modalities. For Geospatial-AI and mobility-analytics teams, this is a rare opportunity to train predictive models for supply chain optimization and route planning. In a Geospatial Analytics market projected to exceed $117 billion by 2026, this dataset provides a distinct advantage for modeling North American trade flows.
See dimension details ↓- Dataset Specificity90
dominant 'geo_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 Volume64
5 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 Geo AI
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI buyer demand is driven by the rapid growth of the Geospatial Analytics market, which is expanding at a 12.90% CAGR as companies increasingly use this data for a competitive edge.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility16
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 Strength77
4 evidence types, 5 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
ownership=owned, licensing=clean
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, 4 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 — The company is an active, family-owned Canadian freight brokerage SME that generates valuable logistics data (routes, pricing, shipments) as a by-product of its core business and shows no signs of selling this data as a product. [1, 3, 6, 8] Issues: An online forum post from 2021 suggests the registered address is a residence, indicating the company may be very small or fully remote. [4]
- Deep Qualification70
✓ pass — Horizon Fast Freight is a freight broker whose business model plausibly generates a valuable Mobility & Geospatial dataset; however, data ownership is complex and licensing rights are unclear due to its role as an intermediary using third-party carriers and the absence of a specific operational data policy.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
This evidence points to tabular geospatial data detailing actual freight routes and delivery points within the high-value Canada-USA trade corridor, essential for logistics optimization models.
Knowledge base / docs
This text-based evidence describes the company's core logistics processes, providing the business logic and context needed to interpret and structure the raw operational data.
Transaction data
This evidence indicates the existence of data on a partner network, which can be used to model commercial relationships and supply chain dependencies across North America.
Industrial data
This time-series evidence shows the dataset tracks diverse shipping modalities and specialized load types, enabling granular analysis of industrial transport trends over time.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Horizonfastfreight Mobility & Geospatial — a Moderate mobility & geospatial dataset (Tabular modality) in the mobility domain. Primary AI use-case: Geo AI. Market signal: Global Geospatial Analytics market = $117.30 billion in 2026, CAGR 12.90% (source: Fortune Business Insights). Investment score 68.4/100 (confidence 0.58). Recommended action: Acquire.
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Learn before you deal
- Is Your Data Worth Money?3 min read
- What is a Dataset Worth?3 min read
- How a Data Transaction Works3 min read