Dataset opportunity
Aloxy — Industrial Sensor Dataset Opportunity
Large industrial sensor dataset held by Aloxy, usable for Predictive Maintenance and Anomaly Detection.
Score
45
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
68%
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 was valued at $15.10 billion in 2025, with a projected CAGR of 31.1%.
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.
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Restricted
Legal
Largely customer-owned — licensing rights to clarify
Buyer persona
Industrial AI & maintenance-optimization vendors
Aloxy provides a unique Time Series dataset composed of aggregated, anonymized telemetry from industrial sensors. This data, which includes event streams and IoT data, captures sensor performance and network reliability metrics from harsh industrial environments, making it exceptionally well-suited for developing and training robust Predictive Maintenance models.
The business value is substantial, as this data serves the global Predictive Maintenance market, which was valued at $15.10 billion in 2025 and is projected to grow at a 31.1% CAGR. [14] While access requires navigating B2B contracts due to client data ownership, the rarity and proprietary value of this aggregated performance data make it a crucial asset for AI buyers aiming to build highly accurate predictive models for industrial applications. ⚠ Diligence (valuable data, access to negotiate): Primary sensor data is owned by industrial clients (e.g., Dow, Orlen).; Proprietary value lies in the aggregated, anonymized telemetry of sensor performance and network reliability across harsh industrial environments.; Access requires navigating B2B contracts regarding data usage for model training. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Evidence confirms Aloxy holds proprietary, event-based time-series data from its industrial IoT sensors, capturing critical operational events like valve positioning in real time. This dataset is a direct fit for AI vendors developing predictive maintenance models for high-value sectors like energy and chemicals, as validated by investments from Dow and Emerson. In a market projected to grow at over 30% annually, this data provides the ground truth needed to train algorithms that can prevent costly failures and optimize industrial operations.
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 Rarity58
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume94
10 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 Demand95
AI buyer demand is extremely high, driven by the rapid growth of the Predictive Maintenance market, which is projected to grow at a 31.1% CAGR. [14]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility36
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 Feasibility66
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength92
4 evidence types, 10 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License8
ownership=customer_owned, licensing=rights_unclear
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 Orientation22
0 data-appetite signals (0 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 Audit50
⚠ review — Aloxy's core business is selling an end-to-end IIoT solution—sensors and a data platform—to its industrial customers, making it a technology vendor, not a holder of proprietary, dormant operational data. Issues: The company's core product is an intelligence and data-delivery system (sensors and an IIoT hub) which it sells to clients. [3, 4, 8]; Aloxy is a technology vendor that enables its customers to generate data; it does not accumulate data as a by-product of its own separate, real-world operations; The data on valve positions is generated on its clients' assets and integrated into their systems, meaning the clients are the data owners. [6, 8]
- Deep Qualification80
✓ pass — Aloxy is a tooling vendor selling industrial IoT sensors and a software hub. The raw sensor data is owned by its clients, but the opportunity lies in the aggregated performance telemetry Aloxy creates. Access to this data is not publicly documented and must be negotiated within B2B contracts.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This evidence confirms the collection of time-series data from real-world industrial IoT deployments, including event-based signals critical for building robust AI models.
Industrial data
The dataset includes rich industrial time-series signals that go beyond primary measurements to include crucial operational metadata like network integrity and sensor health.
Downloads / exports
The company captures tabular data from datasheet downloads, representing a valuable source of qualified leads for B2B marketing in the industrial sector.
Event streams
The holder explicitly captures high-value event streams, such as real-time valve positioning, which are far more effective for training predictive maintenance algorithms than simple trend data.
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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Aloxy Industrial Sensor — a Large industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at $15.10 billion in 2025, with a projected CAGR of 31.1% (source: Market Research Future). [14]. Investment score 45.0/100 (confidence 0.68). Recommended action: Data Sharing Agreement.
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Learn before you deal
- How a Data Transaction Works3 min read
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- 5 Mistakes That Drive Buyers Away3 min read