Dataset opportunity
Balfego — Gelegenheid voor sensortelemetergegevens
Matige dataset met sensortelemetergegevens van Balfego, bruikbaar voor voorspellend onderhoud en anomaliedetectie.
Score
71.2
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
49%
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 Predictive Maintenance market = $13.65B in 2025, CAGR 24.30%.
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
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Partial
Legal
Owned by the company — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Balfego beschikt over een aanzienlijke Sensor Telemetry Dataset bestaande uit industriële IoT-gegevens en bedrijfsgegevens uit zijn aquacultuuractiviteiten. Deze Time Series-gegevens, die operationele parameters in realtime vastleggen, zijn zeer geschikt voor het ontwikkelen en trainen van AI-modellen voor Predictive Maintenance, waardoor uitval van apparatuur in hun unieke fysieke omgeving kan worden voorzien.
De wereldwijde markt voor Predictive Maintenance is een belangrijke waardestuwende factor, geschat op $13,65 miljard in 2025 en naar verwachting zal groeien met een CAGR van 24,30%. [10] Hoewel de toegang complex is vanwege de diepe integratie van de gegevens met fysieke operaties en de aanwezigheid van propriëtaire vetniveau-meetgegevens, maken de zeldzaamheid en directe toepasbaarheid op dit snelgroeiende AI-gebruiksscenario het een waardevol bezit voor kopers die een concurrentievoordeel zoeken in industriële efficiëntie. ⚠ Zorgvuldigheid (waardevolle gegevens, toegang om te onderhandelen): Gegevens zijn diep geïntegreerd in fysieke aquacultuuractiviteiten; Traceerbaarheidssysteem is al gedigitaliseerd, maar ruwe biologische datasets blijven intern; Propriëtaire vetniveau-meetgegevens zijn een uniek concurrentievoordeel · bedrijf: onafhankelijk.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Dit bewijs toont aan dat Balfego een propriëtaire time-series dataset bezit van industriële sensoren die de volledige levenscyclus van hoogwaardige biologische activa monitoren. De gegevens leggen precieze metingen vast voor gezondheidsmonitoring en operationele optimalisatie, waardoor het een krachtige real-world analoog is voor predictive maintenance modellen. In een markt die groeit tot $13,65 miljard in 2025, stelt deze zeldzame sensor telemetry dataset industriële AI-leveranciers in staat om superieure anomaly detection algoritmen te trainen en te valideren, wat een aanzienlijk concurrentievoordeel oplevert.
See dimension details ↓- Dataset Specificity62
dominant 'iot_data', sector other, 2 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 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 Value74
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 very high, driven by the need to optimize industrial operations in a market growing at a CAGR of 24.30%. [10]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
ownership=company_owned, 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 Audit92
✓ good target — Balfegó is an ideal target; its core business is fishing and selling high-quality bluefin tuna, and it generates extensive, proprietary traceability and telemetry data as a by-product to guarantee quality, not as a primary commercial product. Issues: The company has over 335 employees and ~€119M in revenue, placing it at the upper end of the SME definition, bordering on a large enterprise.
- Deep Qualification90
✓ pass — Balfego is a data_holder selling bluefin tuna, with a highly plausible and valuable byproduct dataset from its industrial aquaculture operations, including unique traceability and proprietary fat-level data, with no apparent licensing restrictions.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
business_records
Public records confirm the company operates a unique traceability system, documenting the origin, weight, and analysis of each asset, which validates the existence of a disciplined and structured data-capture process.
IoT / sensor data
The company's own statements confirm the use of IoT devices and precise measurement data to optimize harvesting, providing direct evidence of a valuable time-series signal for operational efficiency models.
Industrial data
Evidence shows the collection of industrial data related to feeding, growth, and health monitoring, offering a rich source of longitudinal sensor telemetry ideal for training predictive health algorithms.
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
Scanned sources
Deliverable
Premium dataset report
Balfego Sensor Telemetry — a Moderate sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $13.65B in 2025, CAGR 24.30% (source: Fortune Business Insights). Investment score 71.2/100 (confidence 0.49). Recommended action: Acquire.
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