Dataset opportunity
Scanreach — Industrial Sensor Dataset Opportunity
Large industrial sensor dataset held by Scanreach, usable for Predictive Maintenance and Anomaly Detection.
Score
81.1
Confidence
79%
Action
Data Sharing Agreement
Market
The global predictive maintenance market was estimated at USD 13.65 billion in 2025 and is projected to reach USD 97.37 billion by 2034, with a CAGR of 24.30% (2026-2034).
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 🔌Public API
API for data consumption by clients
source ↗ - 📦Data product
ConnectPOB service for tracking crew members
source ↗ - 📦Data product
ConnectFuel for vessel fuel consumption data
source ↗ - 📝Published article
Involvement in Green AI for Sustainable Shipping (GASS) project for AI-driven insights
source ↗ - ✨Signal
CEO statement on contextualizing human behavior with machine data
source ↗
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Partial
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
Industrial AI & maintenance-optimization vendors
Scanreach holds time-series industrial sensor datasets, including geographical and IoT data, originating from client vessels. This data is crucial for the development and improvement of predictive maintenance AI models, enabling the anticipation of equipment failures and significantly reducing unplanned downtime and maintenance costs in the maritime sector. Despite potential client-related access restrictions and the need to manage PII (Personnel On-Board) data in accordance with GDPR, the ability to reduce maintenance costs by 20-30% and unplanned downtime by 70-90% makes this data extremely valuable for AI buyers.
The global predictive maintenance market is projected to reach USD 97.37 billion by 2034 with a CAGR of 24.30%. The specific maritime predictive maintenance market is projected to reach USD 3.058 billion by 2034 with a CAGR of 21.6%.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
- Dataset Specificity90
dominant 'iot_data', sector industrial, 3 specific types
- Dataset Rarity58
proprietary domain data (open lowers rarity)
- Dataset Volume100
13 evidence hits
- Dataset Freshness82
real-time/streaming
- Training Value84
fit for Predictive Maintenance
- Legal Accessibility60
open/API access
- Acquisition Feasibility84
medium difficulty, independent
- Evidence Strength100
5 evidence types, 13 hits
- Right to License28
ownership=mixed, licensing=gdpr_sensitive
- Corporate Independence90
independent
- Data Orientation100
5 data-appetite signals (4 types)
- Buyer Demand90
The global AI in manufacturing market, where predictive maintenance is a dominant application, is expected to grow by 35.3% (CAGR) between 2025 and 2030, indicating a very high and growing demand for the d-nvest.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Market read
Scanreach possesses a robust collection of industrial sensor data, primarily time series, directly enabling predictive maintenance applications. This evidence confirms their capability in acquiring and structuring critical operational data from diverse industrial assets, particularly within the maritime and energy sectors. For Industrial AI and maintenance-optimization vendors, this dataset offers a foundational resource to develop and refine solutions in a market projected to reach nearly $100 billion by 2034.
IoT / sensor data
Time Series · 7 hitsThis extensive evidence demonstrates Scanreach's core strength in wireless IoT sensor data acquisition, providing the foundational time-series data essential for real-time industrial monitoring.
API access
Multimodal · 2 hitsThis evidence confirms Scanreach provides programmatic API access for seamless data consumption and integration into external platforms, crucial for AI buyers seeking efficient data pipelines.
Industrial data
Time Series · 2 hitsExplicitly linking to machine monitoring and predictive maintenance, this data type includes specialized industrial formats like NMEA, directly addressing the AI buyer's core use-case for operational efficiency.
Geospatial data
Tabular · 1 hitScanreach collects valuable geospatial data for asset and personnel tracking, offering critical contextual intelligence for optimizing industrial operations and maintenance strategies.
Downloads / exports
Tabular · 1 hitScanreach's engagement across sectors like Commercial Maritime and Energy indicates a broad base of industry-specific data and expertise, valuable for buyers targeting diverse industrial verticals.
Deal room
Deal Room — Scanreach — Industrial Sensor Dataset Opportunity
Industrial Sensor Dataset (Time Series, industrial). Best AI use-case: Predictive Maintenance. Target buyers: Industrial AI & maintenance-optimization vendors. Market: Le marché mondial de la maintenance prédictive était estimé à 13,65 milliards USD en 2025 et devrait atteindre 97,37 milliards USD d'ici 2034, avec un TCAC de 24,30 % (2026-2034).. Rarity: Medium; accessibility: Partial. Key risk: Mixed ownership — GDPR-sensitive (PII review). Recommended deal structure: Data Sharing Agreement. Investment score 79.0/100.
Buyer persona
Industrial AI & maintenance-optimization vendors
Market
The global predictive maintenance market was estimated at USD 13.65 billion in 2025 and is projected to reach USD 97.37 billion by 2034, with a CAGR of 24.30% (2026-2034).
Risk
Mixed ownership — GDPR-sensitive (PII review)
Action
Data Sharing Agreement
Coverage
Scanned sources
Deliverable
Premium dataset report
Scanreach Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Le marché mondial de la maintenance prédictive était estimé à 13,65 milliards USD en 2025 et devrait atteindre 97,37 milliards USD d'ici 2034, avec un TCAC de 24,30 % (2026-2034).. Investment score 79.0/100 (confidence 0.79). Recommended action: Data Sharing Agreement.