Dataset opportunity

Char — Open Data Asset Opportunity

Large open data asset held by Char, usable for Pretraining and Benchmarking.

Open Data AssetTabularPretraining🌍 United Kingdomchar.gyJun 1, 2026

Score

80

Confidence

80%

Action

Data Sharing Agreement

Market

The global AI in Electric Vehicle Charging Market is projected to reach $6.01 billion by 2030, growing at a CAGR of 25.8% (source: openPR.com, The Business Research Company).

Data appetite4 signals

Concrete evidence this company actively cares about data — why it's ripe for the deal room.

  • 📝Published article

    Uses in-house data experts to accurately forecast future EV demand.

    source
  • 🧑‍💻Hiring a data role

    Mentions 'Data Analysts' in careers section.

    source
  • 🔌Public API

    Provides open data via OCPI for locations and tariffs to comply with regulations.

    source
  • 🤝Data partnership

    Partnership with Sitetracker to gain real-time insight into project status, survey data, and field activity.

    source

Profile

Dataset profile

Type

Open Data Asset

Modality

Tabular

Sector

mobility

Volume

Large

Freshness

Real-time

Rarity

Medium

Accessibility

Partial

Legal

Owned by the company — GDPR-sensitive (PII review)

Buyer persona

Foundation-model labs

Char.gy possesses a rich Open Data Asset in a Tabular modality, encompassing a diverse range of data types including a data_catalog, downloads, event_streams, geo_data, iot_data, and open_data. This comprehensive dataset, particularly valuable for Pretraining AI models, offers granular insights into electric vehicle (EV) charging patterns and infrastructure utilization. The combination of real-time IoT data and historical records makes it highly suitable for developing sophisticated AI algorithms for predictive analytics and optimization in the mobility sector.

The business value of such data is substantial within the rapidly expanding AI in Electric Vehicle Charging Market, projected to reach $6.01 billion by 2030 with a CAGR of 25.8%. Despite the complexity of data access, influenced by significant investments from Zouk Capital and the UK Government-backed Charging Infrastructure Investment Fund (CIIF), and the necessity for GDPR compliance due to the inclusion of personal data of EV drivers, the data remains highly valuable. Its utility for enhancing charging efficiency, optimizing energy services, and informing smart city initiatives underscores its worth, even with the requirement for careful negotiation and adherence to regulations like the Public Charge Point Regulations 2023. ⚠ Diligence (valuable data, access to negotiate): Significant investment from Zouk Capital and the UK Government-backed Charging Infrastructure Investment Fund (CIIF) may influence data access decisions.; Data includes personal data of EV drivers, requiring careful GDPR compliance.; Some aggregated data may be shared with local authorities for scheme management.; Complies with Public Charge Point Regulations 2023 by making some open data available via OCPI. · corporate: independent.

Scoring

Scored dimensions

Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.

SpecificityRarityVolumeTraining ValueBuyer DemandEvidence StrengthData Orientation
  • Dataset Specificity90

    dominant 'open_data', sector mobility, 3 specific types

  • Dataset Rarity58

    proprietary domain data (open lowers rarity)

  • Dataset Volume100

    11 evidence hits

  • Dataset Freshness82

    real-time/streaming

  • Training Value74

    fit for Pretraining

  • Buyer Demand90

    The AI in mobility market is projected to grow at a Compound Annual Growth Rate (CAGR) of 44.6% from 2026 to 2035, indicating a very high and increasing demand for data to train AI models in this sector, including open data assets for pre-t

  • Legal Accessibility48

    open/API access

  • Acquisition Feasibility66

    medium difficulty, independent

  • Evidence Strength100

    6 evidence types, 11 hits

  • Right to License62

    ownership=owned, licensing=gdpr_sensitive

  • Corporate Independence90

    independent

  • Data Orientation100

    4 data-appetite signals (4 types)

  • ICP Audit92

    ✓ good target — Char.gy operates an electric vehicle charging network, generating valuable operational data as a by-product of its core service, and does not appear to sell this data or derived intelligence as its primary business.

Evidence

Dataset evidence & lineage

What the typed evidence proves the company holds — reframed for clarity and set against the market.

Market read

Char.gy demonstrably owns a rich, multi-modal dataset derived from its rapidly expanding network of over 4,700 electric vehicle charging points across the UK, with plans to reach 100,000 by 2030. This includes time-series operational data, geographic location data, and tabular open data on tariffs and availability, made accessible via OCPI. For foundation model labs, this dataset offers critical, real-world inputs for pretraining advanced AI models to optimize EV charging infrastructure and capitalize on the projected $6.01 billion AI in EV Charging Market by 2030. Its structured nature and explicit compliance with open data standards make it immediately actionable for developing predictive analytics and smart mobility solutions.

Downloads / exports

Tabular · 2 hits

This evidence points to user interaction data from their charging app and aggregated environmental impact metrics, valuable for understanding user behavior and sustainability performance.

Open data

Tabular · 1 hit

Char.gy explicitly commits to providing open data and adheres to the OCPI standard, indicating a structured and accessible source of information for market analysis and regulatory compliance.

IoT / sensor data

Time Series · 1 hit

Char.gy operates a large network of over 4,700 public EV chargers, generating time-series operational data on charger status, usage, and remote management, critical for network optimization.

Geospatial data

Tabular · 1 hit

This confirms the geographic location data for Char.gy's extensive and rapidly growing network of EV charging points, essential for spatial analysis and infrastructure planning.

Event streams

Time Series · 1 hit

Evidence of high network availability and remote management indicates time-series event data detailing the operational status and performance of individual charging points, valuable for reliability modeling.

Data catalog / marketplace

Multimodal · 1 hit

Char.gy complies with regulations by providing open data via OCPI endpoints for locations and tariffs, confirming a structured and programmatically accessible data catalog.

Deal room

Deal Room — Char — Open Data Asset Opportunity

status: open

Open Data Asset (Tabular, mobility). Best AI use-case: Pretraining. Target buyers: Foundation-model labs. Market: The global AI in Electric Vehicle Charging Market is projected to reach $6.01 billion by 2030, growing at a CAGR of 25.8% (source: openPR.com, The Business Research Company).. Rarity: Medium; accessibility: Partial. Key risk: Owned by the company — GDPR-sensitive (PII review). Recommended deal structure: Data Sharing Agreement. Investment score 80.0/100.

Buyer persona

Foundation-model labs

Market

The global AI in Electric Vehicle Charging Market is projected to reach $6.01 billion by 2030, growing at a CAGR of 25.8% (source: openPR.com, The Business Research Company).

Risk

Owned by the company — GDPR-sensitive (PII review)

Action

Data Sharing Agreement

Coverage

Scanned sources

https://char.gyingested
https://char.gy/ev-charging-insightsingested
https://char.gy/impact_report_2024.pdfingested
https://char.gy/aboutingested
https://char.gy/contactingested
https://char.gyinferred
https://char.gy/contact-usingested

Deliverable

Premium dataset report

Char Open Data — a Large open data asset (Tabular modality) in the mobility domain. Primary AI use-case: Pretraining. Market signal: The global AI in Electric Vehicle Charging Market is projected to reach $6.01 billion by 2030, growing at a CAGR of 25.8% (source: openPR.com, The Business Research Company).. Investment score 80.0/100 (confidence 0.8). Recommended action: Data Sharing Agreement.

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