Dataset opportunity
Precisiongeomatics — Geospatial Dataset Opportunity
Moderate geospatial dataset held by Precisiongeomatics, usable for Geo AI and Routing & Forecasting.
Score
70.3
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
53%
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 = $102.45B in 2025, CAGR 12.90% (2026-2034)
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
Profile
Dataset profile
Type
Geospatial Dataset
Modality
Tabular
Sector
industrial
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
Geospatial-AI & mobility-analytics teams
Precisiongeomatics possesses a rich geospatial dataset in a tabular modality, comprising diverse geo_data, image_collection, and industrial_data. This data is highly valuable for Geo AI applications, enabling advanced spatial analysis, predictive modeling, and real-time insights crucial for decision-making within the industrial sector. It can be leveraged to automate object detection, classify land use, monitor environmental changes, and extract complex patterns from vast datasets.
Despite the need for licensing clarification due to its client-specific and aggregated nature, the strategic importance of such specialized data for buyers in the Geo AI space is significant. The global geospatial analytics market size, a key segment for this data, was valued at USD 102.45 billion in 2025 and is projected to grow with a robust CAGR of 12.90% from 2026 to 2034. ⚠ Diligence (valuable data, access to negotiate): Data is often client-specific and generated as part of a service.; Some data is aggregated from public/third-party sources.; Licensing for re-use of client-generated data would need clarification. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
- Dataset Specificity90
dominant 'geo_data', sector industrial, 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 Demand92
The global Geospatial Analytics Artificial Intelligence Market is forecast to grow from $60.4 billion in 2025 to over $470 billion by 2034, demonstrating an eye-popping 25.7% CAGR, indicating extremely high and rapidly growing buyer demand
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 Feasibility30
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength68
3 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 License36
ownership=mixed, 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 Orientation76
3 data-appetite signals (2 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - ICP Audit100
✓ good target — Precision Geomatics is a highly contactable SME that generates valuable, niche geospatial data as a by-product of its core surveying and mapping services, and does not appear to sell this raw data or derived intelligence as its primary business.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Market read
Precisiongeomatics demonstrably owns a highly proprietary and robust geospatial dataset, primarily in tabular format, meticulously derived from advanced Photogrammetry and LiDAR technologies. This data, encompassing detailed Digital Terrain Models and Digital Surface Models, is exceptionally valuable for Geo AI and mobility-analytics teams seeking precise insights into land features, infrastructure, and industrial operations. Tapping into a Global Geospatial Analytics Market projected to reach $102.45B by 2025, this unique blend of surveying expertise and industrial application offers critical, high-fidelity data for AI-driven decision-making in a rapidly expanding sector.
Geospatial data
Tabular · 3 hitsThis evidence confirms a substantial collection of tabular geospatial data, including Digital Terrain Models (DTMs) and Digital Surface Models (DSMs), generated through sophisticated Photogrammetry and LiDAR; it is crucial for geospatial analytics, urban planning, and pipeline integrity programs, providing foundational data for AI models.
Image collection
Image · 1 hitThis indicates the holder's capability to capture underlying image data via Photogrammetry and LiDAR, which underpins the high fidelity and accuracy of their derived geospatial products, essential for Geo AI applications requiring precise source data.
Industrial data
Time Series · 1 hitThis evidence points to specialized time-series data related to industrial activities, specifically Civil Volumes and Progress Reporting; it offers critical insights for industrial analytics, project management, and predictive maintenance within infrastructure and construction, enabling AI buyers to optimize large-scale operations.
Deal room
Deal Room — Precisiongeomatics — Geospatial Dataset Opportunity
Geospatial Dataset (Tabular, industrial). Best AI use-case: Geo AI. Target buyers: Geospatial-AI & mobility-analytics teams. Market: Global Geospatial Analytics Market = $102.45B in 2025, CAGR 12.90% (2026-2034). Rarity: High (proprietary); accessibility: Restricted. Key risk: Mixed ownership — licensing rights to clarify. Recommended deal structure: Acquire. Investment score 70.3/100.
Buyer persona
Geospatial-AI & mobility-analytics teams
Market
Global Geospatial Analytics Market = $102.45B in 2025, CAGR 12.90% (2026-2034)
Risk
Mixed ownership — licensing rights to clarify
Action
Acquire
Coverage
Scanned sources
Deliverable
Premium dataset report
Precisiongeomatics Geospatial — a Moderate geospatial dataset (Tabular modality) in the industrial domain. Primary AI use-case: Geo AI. Market signal: Global Geospatial Analytics Market = $102.45B in 2025, CAGR 12.90% (2026-2034). Investment score 70.3/100 (confidence 0.53). Recommended action: Acquire.