Dataset opportunity
Farmdroid — Geospatial Dataset Opportunity
Large geospatial dataset held by Farmdroid, usable for Geo AI and Routing & Forecasting.
Score
75.3
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
62%
Action
License
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 Geo-Spatial Agriculture Analytics market to reach $6.56 billion by 2034, CAGR 13.0% (2026-2034).
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.
- 🧑💻Hiring a data role
Historical hiring for Software and Robotics Engineers focused on GPS and data precision
source ↗
Profile
Dataset profile
Type
Geospatial Dataset
Modality
Tabular
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Partial
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
Geospatial-AI & mobility-analytics teams
Farmdroid possesses a unique Geospatial Dataset generated by its autonomous farming robots. This high-fidelity data, presented in a Tabular modality, includes proprietary, high-precision RTK GPS coordinates, along with extensive iot_data and industrial_data from on-farm operations. This rich combination of sensor and location information provides a powerful foundation for Geo AI models aimed at optimizing agronomic processes, from seeding to harvesting, with unparalleled accuracy.
The global Geo-Spatial Agriculture Analytics market is a significant and rapidly expanding sector, projected to reach $6.56 billion by 2034 with a strong 13.0% CAGR. [2] While access to this data requires navigating EULAs due to its origin on customer farms, its rarity and the fact that the underlying agronomic 'big data' is largely unmonetized represent a substantial opportunity. For an AI buyer, negotiating access means acquiring a distinct competitive advantage in a high-growth market. ⚠ Diligence (valuable data, access to negotiate): Data is generated on customer farms, requiring clear data sharing agreements in EULAs.; High-precision RTK GPS data is proprietary to the FarmDroid platform but relates to third-party land.; The company sells the robot and a platform, but the underlying agronomic 'big data' remains largely unmonetized. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Farmdroid owns a proprietary dataset of high-precision geospatial coordinates for individual seeds, captured by its autonomous farming robots. The data documents the precise RTK GPS location of every seed planted, alongside subsequent weeding and micro-spraying actions at those same coordinates. For Geospatial-AI teams, this is a rare asset for training models that optimize agricultural yields and power next-generation precision farming applications. As the Geo-Spatial Agriculture Analytics market grows toward $6.56 billion, this unique, field-level operational data offers a significant competitive advantage.
See dimension details ↓- ICP Audit100
✓ good target — Farmdroid sells agricultural robots and their core business is not data, but the robots generate valuable, proprietary geospatial data as a by-product of their operational activity, making it an ideal target. Issues: The primary issue is data ownership; it's unclear what rights Farmdroid has to the operational data generated by robots on customer farms.; The company is actively developing its data capabilities, including AI-based vision systems, which could indicate a future move towards selling data/intelligenc
- 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 Rarity58
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume76
7 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 Geo AI
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 driven by the robust 13.0% CAGR in the Geo-Spatial Agriculture Analytics market, reflecting an urgent need for data-driven farming decisions and the integration of AI. [2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility56
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility66
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength83
4 evidence types, 7 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 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. - Deep Qualification80
✓ pass — Farmdroid sells autonomous farming robots and collects the resulting operational data, making it a tooling vendor with a valuable byproduct dataset. However, data ownership is mixed as it's generated on customer farms, and the right to resell this data is not explicitly defined in their privacy policy.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
This confirms the collection of tabular geospatial data that links precise RTK GPS coordinates to individual seeds, creating a ground-truth asset for advanced precision agriculture and yield optimization models.
Downloads / exports
Public product specifications validate the technical collection method, documenting the use of 8mm high-precision RTK GPS systems and corroborating the quality and accuracy of the core geospatial dataset.
IoT / sensor data
This indicates the presence of raw time-series sensor data from the robot's GPS unit, providing a continuous, high-fidelity log of machine position and operations valuable for mobility analytics.
Industrial data
This points to a time-series dataset of industrial machine events, such as equipment status and fault alerts, which is highly valuable for building predictive maintenance models for autonomous agricultural hardware.
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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Farmdroid Geospatial — a Large geospatial dataset (Tabular modality) in the industrial domain. Primary AI use-case: Geo AI. Market signal: Global Geo-Spatial Agriculture Analytics market to reach $6.56 billion by 2034, CAGR 13.0% (2026-2034) (source: Research and Markets).. Investment score 75.3/100 (confidence 0.62). Recommended action: License.
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Learn before you deal
- How a Data Transaction Works3 min read
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- 5 Mistakes That Drive Buyers Away3 min read