Dataset opportunity
Aerobotics — Industrial Operations Dataset Opportunity
Moderate industrial operations dataset held by Aerobotics, usable for Industrial Monitoring and Forecasting.
Score
48
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
56%
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 size (indicative estimate)
Global AI in Agriculture market was valued at $1.91 billion in 2023, with a projected CAGR of 25.5% from 2024 to 2030.
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
Industrial Operations Dataset
Modality
Time Series
Sector
other
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
Industrial AI integrators
Aerobotics possesses a significant Industrial Operations Dataset comprised of high-resolution drone imagery and sensor-derived Time Series data from agricultural operations. This collection of iot_data and detailed image_collection provides longitudinal growth curves and raw visual evidence, making it exceptionally well-suited for training AI models for the Industrial Monitoring of high-value crops, enabling precise tracking of plant health and yield forecasting.
The dataset operates within the global AI in agriculture market, which was valued at $1.91 billion in 2023 and is projected to grow at a remarkable CAGR of 25.5%. [15] While access requires navigating data ownership complexities with growers, the immense value of these raw, longitudinal dormant assets is a compelling proposition for AI buyers. The high growth rate underscores the intense demand for such data to build next-generation agricultural intelligence and monitoring solutions. ⚠ Diligence (valuable data, access to negotiate): Data is collected via customer smartphones and drones, implying shared ownership or usage rights complexity; The company sells intelligence (forecasts), but the raw imagery and longitudinal growth curves are the dormant assets; Contractual terms with growers regarding the secondary use of anonymized/aggregated data need verification · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves that Aerobotics holds a significant, proprietary dataset tracking agricultural operations, centered on time-series data of fruit growth and quality. This asset is directly applicable to the high-demand Industrial Monitoring use-case, enabling AI integrators to build sophisticated predictive models for crop yield and health. In a rapidly expanding AI in Agriculture market, this unique combination of aerial and ground-truth data offers a distinct competitive advantage for developing next-generation farm management solutions.
See dimension details ↓- Dataset Specificity74
dominant 'industrial_data', sector other, 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 Volume58
4 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 Industrial Monitoring
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand95
AI buyer demand is exceptionally high, driven by the explosive 25.5% CAGR of the $1.91 billion AI in agriculture market, which fundamentally relies on this type of data for innovation and model training. [15]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility40
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 Feasibility4
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 evidence types, 4 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 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, 5 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 Audit75
⚠ review — The company's core business is selling AI-powered analytics and intelligence software to the agricultural industry, making it a bad target as it already sells intelligence as a product. Issues: Core business is selling intelligence: Aerobotics' main products are software platforms (like Aeroview and TrueFruit) that provide AI-powered analytics, yield f; Product is intelligence, not data exhaust: The company explicitly markets and sells AI-driven insights, yield estimations, and crop p
- Deep Qualification80
✓ pass — The company sells analytics services, not raw data, and while the customer owns their data, Aerobotics retains rights to use aggregated, de-identified data for model training, representing a negotiable but complex asset.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “Mon voisin veut planter un bois dans sa parcelle d’herbage. Elle se situe derrière mes garages et à dix mètres de ma maison. Quelles sont les distances par rapport à la limite de propriété ?”
- “Les prairies naturelles peuvent augmenter l’autonomie fourragère d’une exploitation. Une expérimentation de la chambre d’agriculture de la Haute-Loire démontre que l’apport de fumier et de lisier est un levier important pour augmenter leur rendement.”
- “Apolline Goffinet souhaite créer un atelier de poules pondeuses à côté de l’élevage ovin de son mari. Tous les voyants étaient au vert quand le recours d’un voisin a bloqué le projet.”
Developer portal
The company's public profile highlights a multidisciplinary team of agronomists and engineers, indicating the dataset is curated with deep domain expertise crucial for building reliable AI models.
Image collection
The holder possesses a massive collection of over 130 million labeled fruit images, a highly valuable asset for training computer vision models for automated quality control and yield forecasting.
Industrial data
Customer case studies confirm the existence of industrial time-series data, specifically growth curves tracking fruit development, which is critical for building predictive models in precision agriculture.
IoT / sensor data
The evidence shows the company processes aerial imagery with artificial intelligence to identify crop issues, proving a valuable dataset for training models on early problem detection in industrial agriculture.
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, Image
License
One-time license for AI model training and industrial monitoring applications. Usage restrictions may apply.
Personal data
No PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its high rarity as proprietary, real-time time-series and imagery data for industrial monitoring in the high-growth AI in Agriculture market. The strong market read and specific use-case for yield forecasting and plant health monitoring support a premium valuation.
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
Aerobotics Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the other domain. Primary AI use-case: Industrial Monitoring. Market signal: Global AI in Agriculture market was valued at $1.91 billion in 2023, with a projected CAGR of 25.5% from 2024 to 2030 (source: Grand View Research). [15]. Investment score 48.0/100 (confidence 0.56). Recommended action: Acquire.
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