Dataset opportunity
Zunder — Mobility Telemetry Dataset Opportunity
Moderate mobility telemetry dataset held by Zunder, usable for Predictive Maintenance and Anomaly Detection.
Score
74.3
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
Data Sharing Agreement
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 = $9.21B in 2025, CAGR 26.19%.
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.
- 🤝Data partnership
Interoperability partnerships with Gireve and Hubject requiring real-time data exchange
source ↗
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 — GDPR-sensitive (PII review)
Buyer persona
Industrial AI & maintenance-optimization vendors
Zunder holds a Mobility Telemetry Dataset structured as Time Series data, which includes event_streams, geo_data, iot_data, and transaction_data from its EV charging network. This rich combination of operational, transactional, and sensor data provides a comprehensive foundation for developing and training Predictive Maintenance models, enabling the anticipation of hardware failures and optimization of maintenance schedules for charging stations.
The global Predictive Maintenance market was valued at $9.21 billion in 2025 and is projected to grow at a CAGR of 26.19%. [10] While access to the dataset is subject to GDPR, national security sensitivities, and potential investor restrictions, the rarity and depth of this real-world operational data offer a significant competitive advantage for AI buyers seeking to build high-fidelity predictive models in a rapidly expanding market. ⚠ Diligence (valuable data, access to negotiate): User-specific charging history is subject to strict GDPR PII protections; Infrastructure data may have national security or grid stability sensitivities; Potential data sharing restrictions from lead investor Mirova (Natixis IM) · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Zunder owns a rare, proprietary dataset of real-world EV telemetry from its active charging network in Southern Europe. The data's core strength is its detailed time-series logs of ultra-fast charging events, which directly enable the development of advanced predictive maintenance and battery degradation models. For Industrial AI vendors, this is a unique opportunity to acquire training data that addresses a critical need in the rapidly growing global predictive maintenance market, which is projected to reach $9.21B by 2025.
See dimension details ↓- Dataset Specificity100
dominant 'iot_data', sector mobility, 4 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity94
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 Value94
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI buyer demand is high, driven by the rapid growth of the Predictive Maintenance market, which is projected to grow at a 26.19% CAGR. [10]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
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 License62
ownership=company_owned, licensing=gdpr_sensitive
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 Orientation39
1 data-appetite signals (1 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
✓ good target — Zunder is a good target as it operates a large physical EV charging network, generating valuable proprietary telemetry data as a by-product, but its existing SaaS platform for third-party charger management indicates a partial data monetization strategy is already in place, reducing its 'dormant data' potential. Issues: The company offers a 'SaaS platform' to 'Manage and monetize your electric charging points', which suggests they are already in the business of selling software; Their stated goal is to 'manage more than 40,000 charge points through its platform by 2025', which is 10x the number they plan to own, indicating a strong focu; The company was founded on designing charging point management software before building the physical network, so data/software is core to their DNA, not just an
- Deep Qualification90
✓ pass — Zunder is a data holder operating its own EV charging network and selling a SaaS platform to other operators, generating a rich telemetry dataset as a byproduct. A €225M financing in July 2024 to fund massive expansion makes it a prime target, though its data is a mix of proprietary and customer-owned, and is subject to GDPR.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This dataset contains granular, real-time time-series data capturing the electrical performance of charging hardware, including power delivery and voltage fluctuations, which is essential for predicting component failure.
Event streams
It includes detailed technical event logs documenting how different EV models respond to ultra-fast charging, providing invaluable ground truth for training AI models that predict battery degradation.
Geospatial data
The dataset provides high-resolution tabular data on EV traffic flow and station utilization patterns, enabling buyers to model real-world operational stress and optimize maintenance logistics.
Transaction data
It offers aggregated transactional data detailing charging frequency and energy consumption by vehicle type, adding crucial context to usage patterns for more accurate predictive modeling.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
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Deliverable
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Zunder 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 = $9.21B in 2025, CAGR 26.19% (source: Precedence Research). Investment score 74.3/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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