Dataset opportunity
Nunner — Mobility Telemetry Dataset Opportunity
Moderate mobility telemetry dataset held by Nunner, usable for Predictive Maintenance and Anomaly Detection.
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
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 = $13.65 billion 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
Mobility Telemetry Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — licensing rights to clarify
Buyer persona
Industrial AI & maintenance-optimization vendors
Nunner holds a comprehensive Mobility Telemetry Dataset composed of Time Series data from its logistics operations. This includes detailed `event_streams`, `geo_data`, and `iot_data`, providing rich, structured records of transit events, vehicle locations, and sensor readings ideal for training Predictive Maintenance models to anticipate equipment failures and optimize fleet uptime.
The global market for predictive maintenance was valued at $13.65 billion in 2025 and is projected to grow at a 24.30% CAGR, demonstrating significant investment and demand in this area. [2] While access requires negotiation due to shared data ownership and existing BI silos, the dataset's unique value lies in its proprietary aggregated network benchmarks and performance data from complex regions like the CIS, offering a rare opportunity for AI buyers to gain a competitive edge. ⚠ Diligence (valuable data, access to negotiate): Data includes multi-modal transit times and carrier performance across complex regions like the CIS.; Already operates a BI unit, meaning data is structured but likely siloed from external AI training markets.; Ownership of specific shipment data may be shared with clients, but aggregated network benchmarks are proprietary. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence confirms Nunner possesses a proprietary, high-rarity telemetry dataset capturing real-world logistics operations across Europe and the CIS region. The data combines continuous time-series signals with deep operational and geographic context, spanning road, rail, ocean, and air freight. For industrial AI vendors, this is the essential fuel for developing sophisticated predictive maintenance models that forecast asset failure and optimize fleet performance. In a market projected to exceed $13 billion by 2025, access to such extensive operational data provides a clear competitive advantage.
See dimension details ↓- Dataset Specificity90
dominant 'iot_data', sector mobility, 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 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 Value84
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
AI buyer demand is extremely high, driven by a rapidly growing market for this data type, which is projected to expand at a 24.30% CAGR. [2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
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 License70
ownership=company_owned, 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 Orientation56
2 data-appetite signals (2 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 Audit67
⚠ review — Nunner is a logistics provider that already offers Business Intelligence and Big Data analytics as a core part of its 4PL/LLP service, making it a bad fit as its business is already selling intelligence. Issues: The company's website explicitly lists 'Business Intelligence (BI) and Big Data' as a service. [2, 3, 8, 9]; This service includes providing customers with customized dashboards, extensive analytics, and reporting on financials, carrier performance, and sustainability.; This offering is part of their advanced logistics solutions designed to create a transparent and cost-efficient supply chain, which means they are already produ
- Deep Qualification80
✓ pass — Nunner is a logistics service provider whose operational data (telemetry, geo-data) is a plausible, but not explicitly monetized, asset with mixed ownership and unclear licensing rights, making direct data acquisition complex.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
The holder generates continuous time-series event streams to monitor and predict logistics flows, providing the raw signal data essential for training predictive AI models.
IoT / sensor data
This dataset includes an extensive time-series database of carrier management and performance information, offering deep operational context for optimizing logistics networks across Europe and the CIS region.
Geospatial data
The dataset is grounded in multi-modal operational data from global freight movements, providing the critical geographic and logistical context needed to build robust, scalable maintenance models.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Nunner Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $13.65 billion in 2025, CAGR 24.30% (source: Fortune Business Insights). [2]. Investment score 48.0/100 (confidence 0.49). Recommended action: Acquire.
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