Dataset opportunity
Everactive — Industrial Sensor Dataset Opportunity
Moderate industrial sensor dataset held by Everactive, 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
58%
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
Global Predictive Maintenance Market size was valued at around $10.93 billion in 2024, with a projected CAGR of 25.10% (source: MarkNtel Advisors). [11]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-12
How much is trade policy influencing imports?
freightwaves.com ↗ - 📰press2026-07-10
Micron ups US manufacturing, supply chain pledge to $253B
manufacturingdive.com ↗ - 📰press2026-07-10
Tariff exemptions: Ford, Nestlé and others seek relief from proposed levies
supplychaindive.com ↗ - 📰press2026-07-10
Trump chooses trade talks over tariffs after aircraft probe
supplychaindive.com ↗ - 📰press2026-07-09
Scotts Miracle-Gro widens tech partnership for supply chain AI
supplychaindive.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
Restricted
Legal
Mixed ownership — clean to license · PII/regulated
Buyer persona
Industrial AI & maintenance-optimization vendors
Everactive holds a substantial Industrial Sensor Dataset, primarily composed of high-frequency Time Series data from its fleet of batteryless IoT devices. Evidence from its developer portal, raw IoT data feeds, and maintenance logs confirms the availability of rich, granular information on equipment performance, which is directly applicable for training sophisticated Predictive Maintenance models to anticipate equipment failures.
The business value is significant, tapping into the global market for Predictive Maintenance, which was valued at approximately $10.93 billion in 2024 and is projected to grow at a CAGR of 25.10%. [11] While data ownership is likely shared with industrial clients, the core proprietary value lies in the aggregated, anonymized sensor streams. This makes the dataset a rare and valuable asset for AI buyers, justifying the negotiated access required to leverage it. ⚠ Diligence (valuable data, access to negotiate): Data ownership is likely shared with industrial clients under IoT-as-a-service contracts; Proprietary value lies in the aggregated, anonymized high-frequency sensor streams across their fleet · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Everactive owns a continuous, high-volume stream of proprietary industrial sensor data, including crucial labeled failure events. This dataset directly serves the rapidly growing predictive maintenance market, valued at nearly $11 billion and expanding at over 25% annually. For industrial AI vendors, this is a rare opportunity to acquire the ground-truth data needed to train and validate next-generation predictive maintenance models, offering a significant competitive edge by anticipating equipment failures before they occur.
See dimension details ↓- Dataset Specificity78
dominant 'iot_data', sector industrial, 2 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
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 Value74
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand95
AI buyer demand is extremely high, driven by the rapid expansion of the Predictive Maintenance market, which is growing at a 25.10% CAGR. [11]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
open/API access
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 Strength77
4 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 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 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, 5 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 Audit75
⚠ review — Everactive's core business is selling an end-to-end solution, including hardware, networking, and cloud-based analytics as a service, making it a seller of intelligence, not a holder of dormant data. Issues: The company's business model is explicitly 'as-a-service', providing customers with a dashboard for real-time insights, analysis, and alerts. [8, 9, 17]; The core product is the continuous, cloud-based analytics derived from their batteryless sensors, which is what customers pay for. [7, 9, 15]; This is a company selling intelligence/AI software, which is an explicit exclusion criterion for a 'good target'. [16, 17]; The company pivoted from selling chips to providing a full-stack solution because the market wasn't ready to build its own analytics on the hardware. [9]
- Deep Qualification90
✓ pass — Everactive sells end-to-end predictive maintenance solutions, not dormant data. The data generated by its batteryless sensors is integral to its service offering, which includes analytics and alerts. Data ownership is likely mixed, with clients owning their raw data and Everactive retaining rights to aggregated data, but specific terms are not public.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
Technical product descriptions confirm the generation of high-frequency time-series data—at a scale of 20 million records per day—from continuous, batteryless sensors, providing the uninterrupted stream required for robust model training.
Developer portal
Documentation from the company's developer portal explicitly states their intent to generate hyperscale IoT data specifically to feed machine learning models, confirming a high degree of data maturity and AI-readiness.
User-generated content
Public-facing content confirms the company's strategic vision is to capture and analyze data from physical-world assets, validating their focus on the industrial IoT space that predictive maintenance vendors target.
Maintenance logs
Operational service logs demonstrate that the dataset contains labeled data linking sensor readings directly to equipment failures and inefficiencies, which is the essential ground truth for supervised learning.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Everactive 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 size was valued at around $10.93 billion in 2024, with a projected CAGR of 25.10% (source: MarkNtel Advisors). [11]. Investment score 48.0/100 (confidence 0.58). Recommended action: Acquire.
Data Academy
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