Dataset opportunity
Resolvemarine — Mobility Telemetry Dataset Opportunity
Moderate mobility telemetry dataset held by Resolvemarine, usable for Predictive Maintenance and Anomaly Detection.
Score
79.7
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
63%
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 in Maritime Market = $433 Million in 2024, CAGR 21.6%.
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
Partial
Legal
Owned by the company — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Resolve Marine possesses a unique Mobility Telemetry Dataset gathered over 40 years of global salvage operations, presented as a Time Series modality. This collection of industrial_data, iot_data, business records, and imagery provides a rich, multi-modal foundation for developing and training high-fidelity Predictive Maintenance algorithms to anticipate equipment failures in maritime assets.
The data targets the rapidly growing Predictive Maintenance in Maritime market, a segment valued at $433 Million in 2024 and projected to expand at a 21.6% CAGR. While access requires negotiation due to the sensitive nature of government-directed salvage operations and proprietary engineering models, the dataset's unparalleled historical depth and global scope represent a rare and valuable asset for AI buyers seeking to capture this high-growth market. ⚠ Diligence (valuable data, access to negotiate): Data from government-directed salvage operations may have confidentiality restrictions; Proprietary naval architecture and engineering models are core IP; Historical salvage logs span 40 years across all continents · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Resolvemarine holds a proprietary time-series dataset from over 6,500 tagged maritime assets, providing a rare, real-world foundation for training predictive maintenance models. For industrial AI vendors, this is a direct path to developing solutions for the fast-growing, $433M maritime sector, where preventing asset failure is a critical economic driver. The data's lineage from decades of high-stakes salvage and response operations suggests a unique richness in capturing system stress and failure modes.
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 Volume64
5 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 Demand90
AI buyer demand is exceptionally high, driven by the urgent need to reduce operational downtime and costs in a market forecast to grow at a **CAGR** of **21.6%**.
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 Strength86
5 evidence types, 5 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 Orientation67
3 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 Audit92
✓ good target — Resolve Marine is a good target as it's a global marine services company with a large fleet and operational assets, likely generating valuable telemetry and operational data as a by-product of its core business, which is not data sales. Issues: The company has an engineering division and has acquired a software company in the past, which requires verification to ensure their core business is not shifti
- Deep Qualification90
✓ pass — Resolve Marine is a services firm whose operations plausibly generate the hypothesized telemetry data, but data ownership from client projects is likely restricted or customer-owned, making monetization challenging.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Knowledge base / docs
This evidence points to a structured database of global maritime operations, detailing logistical coordination and regulatory compliance across over 120 ports, which is valuable for adding contextual features to AI models.
IoT / sensor data
This is direct evidence of a large-scale time-series dataset generated from over 6,500 tagged assets, providing the foundational telemetry data required to train predictive maintenance algorithms.
Image collection
The holder possesses a unique image collection from drone and underwater surveys, ideal for training computer vision models for automated damage assessment and asset inspection.
Industrial data
This time-series data, quantifying over 184,000 tonnes of removed contaminants, provides a powerful historical record of failure events and their consequences, crucial for modeling operational risk and ROI.
business_records
These records confirm a 40-year history of global salvage and engineering projects, establishing deep domain expertise and a long-term, consistent data-generating process across diverse operational conditions.
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
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Deliverable
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Resolvemarine 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 in Maritime Market = $433 Million in 2024, CAGR 21.6% (source: Market.us). Investment score 79.7/100 (confidence 0.63). Recommended action: Acquire.
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