Dataset opportunity
Agri Tech — Sensor Telemetry Dataset Opportunity
Large sensor telemetry dataset held by Agri Tech, usable for Predictive Maintenance and Anomaly Detection.
Score
40
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
72%
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 Agriculture Analytics market was valued at $2.3 billion in 2023, with a projected CAGR of over 10% (2024-2032).
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
Sensor Telemetry Dataset
Modality
Time Series
Sector
other
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Open / API
Legal
Mixed ownership — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Agri Tech holds a substantial Sensor Telemetry Dataset with a Time Series modality, evidenced by event_streams, geo_data, and extensive iot_data from its IrrigiX platform. This granular data, capturing real-time equipment and environmental metrics, is directly applicable for developing Predictive Maintenance models to forecast machinery failures and optimize operational schedules.
The global Agriculture Analytics market was valued at $2.3 billion in 2023 and is projected to grow at a CAGR of over 10%, underscoring the significant demand for this type of data. [1] While access requires navigating data held in customer-specific accounts and clarifying ownership of aggregated regional benchmarks, the dataset's value is enhanced by historical soil and crop data spanning 30+ years, which offers rare, long-term depth for AI model training once digitized. ⚠ Diligence (valuable data, access to negotiate): Data is partially held within customer-specific accounts on the IrrigiX platform.; Historical soil and crop data spanning 30+ years may require digitization or aggregation from legacy consulting records.; Ownership of aggregated regional benchmarks needs to be clarified against individual farmer rights. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Agri-Tech owns a proprietary, high-rarity dataset of real-time IoT sensor telemetry from precision farming operations. The data captures critical environmental and equipment metrics like soil moisture, pH, and EC, directly feeding the high-demand AI use case of predictive maintenance. For industrial AI vendors, this is a rare opportunity to acquire the ground-truth data needed to train models that optimize resource use and prevent costly system failures in a global agriculture analytics market projected to grow at over 10% annually.
See dimension details ↓- Dataset Specificity98
dominant 'iot_data', sector other, 5 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 (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 Value100
fit for Predictive Maintenance
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 high, driven by the rapid growth of the Agriculture Analytics market which is expanding at a CAGR of over 10% as companies seek data for high-value predictive maintenance solutions. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility78
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 Strength100
6 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 License58
ownership=mixed, 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 Orientation73
3 data-appetite signals (3 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. - ICP Audit33
⚠ review — The most relevant companies found under this generic name have a core business of selling AI-driven analytics and insights, which is an explicit exclusion criterion. Issues: The provided URL https://www.agri-tech.co.uk does not resolve to an active company website.; The name 'Agri Tech' is generic; multiple companies use similar names, most of which are data/analytics providers.; A similarly named Kenyan company, AgriTech Analytics, explicitly sells an AI-driven analytics platform and insights as its core product, making it a bad fit. [1; A UK entity named 'Agri-Tech Engineering' was found, but there is insufficient information to verify its business model or confirm it holds a sensor telemetry d
- Deep Qualification40
✓ pass — Agri-Tech is a plausible data holder with a coherent sensor telemetry dataset from its precision agriculture services. However, the complete absence of a privacy policy or terms of service on its website makes data ownership and licensing rights entirely unknown, posing a critical diligence risk.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
Agri-Tech explicitly deploys IoT technology and smart irrigation systems to capture real-time metrics like pH and EC, providing the core time-series data required for predictive analytics.
Downloads / exports
The company provides a mobile app for farmers to log structured field observations and sensor readings, offering valuable human-in-the-loop data to contextualize automated streams.
Event streams
This confirms the dataset includes continuous event streams based on real-time data, which is essential for training dynamic AI models that optimize water and nutrient use.
Industrial data
The data originates from professional, industrial-scale services like precision soil sampling, signaling a commercially-validated and structured dataset suitable for enterprise AI applications.
Regulatory records
This data is sophisticated enough to inform complex models like university-developed disease forecasting systems, demonstrating its high quality and scientific relevance.
Geospatial data
The dataset is geographically referenced using precise RTK mapping technology, enabling the development of location-aware AI models for precision agriculture.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Agri Tech Sensor Telemetry — a Large sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Agriculture Analytics market was valued at $2.3 billion in 2023, with a projected CAGR of over 10% (2024-2032) (source: Global Market Insights, Inc.). Investment score 40.0/100 (confidence 0.72). Recommended action: License.
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