Dataset opportunity
Utilidata — Industrial Sensor Dataset Opportunity
Large industrial sensor dataset held by Utilidata, usable for Predictive Maintenance and Anomaly Detection.
Score
76.7
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
56%
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 = $15.60 Billion in 2025, CAGR 21.01% (2026-2034) to reach $91.04 Billion by 2034
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
MISO’s resource outlook improves as forecast generation additions outpace demand growth
utilitydive.com ↗ - 📰press2026-06-03
Customer experience, better modeling can boost demand-side portfolio: report
utilitydive.com ↗ - 📰press2026-06-03
7 states sue Trump administration over TotalEnergies offshore wind lease buyout
utilitydive.com ↗ - 📰press2026-06-03
Constellation’s Three Mile Island nuclear restart gets boost with FERC waiver
utilitydive.com ↗ - 📰press2026-06-03
Google to fund 100-MW virtual power plant in PJM in ‘first-of-its-kind’ deal
utilitydive.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.
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Partial
Legal
Owned by the company — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Utilidata possesses a specialized Industrial Sensor Dataset of Time Series data, encompassing real-time power flow and operational metrics from customer-owned infrastructure like utilities and data centers. This rich, granular data, including event streams and IoT data, is exceptionally valuable for Predictive Maintenance applications, enabling the early detection of anomalies and potential equipment failures in critical energy and IT infrastructure.
The global predictive maintenance market is experiencing significant growth, projected to reach $91.04 billion by 2034 with a CAGR of 21.01%. Despite the complexities of data sharing agreements and the highly specialized nature of this information, its direct applicability to reducing downtime and optimizing operational efficiency in high-value assets makes this data immensely valuable, further highlighted by its rarity and strategic importance. ⚠ Diligence (valuable data, access to negotiate): Data is collected from customer-owned infrastructure (utilities, data centers), requiring specific data sharing agreements.; The data is highly specialized, focusing on real-time power flow and grid/data center operational metrics.; Strategic partnerships with major industry players (e.g., NVIDIA, Hubbell, Deloitte) may influence data access and licensing terms. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Utilidata possesses a unique and proprietary collection of high-resolution industrial sensor data, offering unparalleled insights into energy consumption and asset performance. This dataset is exceptionally valuable for Industrial AI & maintenance-optimization vendors seeking to capitalize on the rapidly expanding Predictive Maintenance market, projected to reach $91.04 Billion by 2034. Its granular, real-time insights into industrial operations are critical for developing advanced predictive models and unlocking significant operational efficiencies now. This offering represents a rare opportunity to acquire data essential for next-generation industrial intelligence.
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 Volume74
4 evidence hits, explicit data-volume mention
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 Demand92
The buyer demand for industrial sensor datasets for AI predictive maintenance is very high, as the global predictive maintenance market, heavily reliant on such data for AI-driven solutions, is projected to grow at a CAGR of 27.9% from 2026
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 Feasibility14
high difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 evidence types, 4 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
ownership=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 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, 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 Audit33
⚠ review — Utilidata is not a good target because its core business is selling AI-powered software and intelligence for grid optimization and data center power management, which falls under the exclusion criteria of companies already selling intelligence. Issues: Utilidata's core business is selling AI software and intelligence (Karman platform) for power infrastructure optimization, which is an explicit exclusion criter; Utilidata is not an SME; it has approximately 90 employees, an estimated r
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 availability of high-resolution energy consumption data, capable of measuring server rack usage at 1 million times per second, which is crucial for AI buyers developing predictive maintenance solutions to optimize industrial energy efficiency.
Industrial data
This refers to dynamic power orchestration data from Utilidata's Karman platform, combining advanced metrology with local processing and AI to provide intelligence on grid and data center operations, highly sought after by vendors focused on industrial asset performance and efficiency.
Event streams
This indicates access to ultra-granular event stream data with microsecond resolution and millisecond-level controls, enabling precise real-time energy management and intelligent orchestration, particularly valuable for AI applications requiring high-speed decision-making in critical industrial environments.
Data-volume signal
This highlights the capability to analyze large-scale real-time electricity data through a distributed AI platform, offering a comprehensive foundation for AI buyers building robust predictive analytics and anomaly detection systems across industrial infrastructure.
Coverage
Scanned sources
Deliverable
Premium dataset report
Utilidata 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 = $15.60 Billion in 2025, CAGR 21.01% (2026-2034) to reach $91.04 Billion by 2034. Investment score 76.7/100 (confidence 0.56). Recommended action: Acquire.