Dataset opportunity
Epyr — Industrial Sensor Dataset Opportunity
Moderate industrial sensor dataset held by Epyr, usable for Predictive Maintenance and Anomaly Detection.
Score
47.5
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 = $17.11B in 2026, CAGR 24.30%.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-10-13
Epyr récolte 15 M€ pour électrifier plus de chaleur industrielle
greenunivers.com ↗
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
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Partial
Legal
Mixed ownership — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Epyr holds an extensive Industrial Sensor Dataset composed of high-frequency Time Series data. This collection includes detailed `event_streams`, `industrial_data`, and `iot_data` from physical units on client sites, making it exceptionally well-suited for developing and validating Predictive Maintenance algorithms.
The global market for Predictive Maintenance is substantial, valued at USD 17.11 billion in 2026 and is projected to grow at a remarkable CAGR of 24.30%. While access is subject to negotiation due to the high sensitivity of production cycles and potential shared telemetry ownership, the rarity and direct applicability of this data for optimizing industrial assets offer a significant competitive advantage to AI buyers in this rapidly expanding market. ⚠ Diligence (valuable data, access to negotiate): Data is generated by physical units located on client industrial sites.; Telemetry ownership may be shared or restricted by industrial service agreements.; High sensitivity regarding industrial production cycles and energy consumption patterns. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Epyr owns a proprietary time-series dataset capturing the real-time performance and energy consumption of industrial heating units. This unique data directly addresses the rapidly growing Predictive Maintenance market, projected to reach $17.11B by 2026, by enabling industrial AI vendors to build sophisticated models. These models can optimize energy efficiency, predict equipment failure, and manage responses to grid volatility, unlocking significant savings in a sector where heat accounts for 25% of global energy use.
See dimension details ↓- Dataset Specificity90
dominant 'iot_data', sector industrial, 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 Demand90
AI buyer demand is extremely high, driven by the market's rapid expansion at a 24.30% CAGR as companies increasingly seek specialized industrial data to deploy predictive maintenance solutions.
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 License58
ownership=mixed, 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, 1 recent external signals — 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 Audit58
⚠ review — Epyr's core business is selling a 'Heat-as-a-Service' solution and thermal storage hardware, not generating data as a by-product, making it a technology vendor and a bad fit. Issues: The company's core product is a technology solution (thermal energy storage systems) sold as a service, not a business that generates data as a byproduct.; The initial prompt describing it as an 'Industrial Sensor Dataset Opportunity' is a complete mischaracterization of its actual business.; Epyr is a technology/equipment provider whose business model includes building, owning, and operating their systems for clients.; The data they handle (energy market data, system performance) is used to optimize their core service, not a dormant asset to be sold.
- Deep Qualification80
✓ pass — Epyr is a strong data_holder candidate. It operates its own thermal storage units on client sites under a 'Heat-as-a-Service' model, generating valuable sensor data as a by-product. However, data ownership and licensing rights are undetermined.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This is time-series data capturing the real-time performance and efficiency of industrial heating units, providing the essential ground-truth signals for developing predictive maintenance algorithms.
Industrial data
This dataset documents patterns of industrial heat consumption, a major component of global energy use, enabling AI models to identify and quantify significant cost-saving opportunities for manufacturers.
Event streams
These event streams track how energy consumption responds to grid price volatility and clean energy availability, a crucial dataset for building models that optimize energy storage and flexibility.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Epyr Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $17.11B in 2026, CAGR 24.30% (source: Fortune Business Insights). Investment score 47.5/100 (confidence 0.49). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Millcreekmotorfreight — Mobility Telemetry Dataset Opportunity
View opportunity →mobilityInova Semiconductors — Mobility Telemetry Dataset Opportunity
View opportunity →industrialChementors — Regulatory Records Dataset Opportunity
View opportunity →Data Academy
Learn before you deal
- Data licensing, term by term4 min read
- Is Your Data Worth Money?3 min read
- What is a Dataset Worth?3 min read