Dataset opportunity
Flowmetrix — Industrial Sensor Dataset Opportunity
Moderate industrial sensor dataset held by Flowmetrix, usable for Predictive Maintenance and Anomaly Detection.
Score
70.8
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
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 $13.4 billion in 2025, projected to grow at a CAGR of 23.2% (2026-2035).
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
Medium
Accessibility
Restricted
Legal
Largely customer-owned — licensing rights to clarify
Buyer persona
Industrial AI & maintenance-optimization vendors
Flowmetrix possesses a valuable collection of Time Series data derived from industrial sensors monitoring municipal water systems. This multi-decade aggregation of `industrial_data`, including `event_streams` and `iot_data` on water flow and rainfall, provides the deep historical evidence required to train robust Predictive Maintenance AI models for anticipating equipment and infrastructure failures.
The global Predictive Maintenance market was valued at $13.4 billion in 2025 and is projected to grow at a CAGR of 23.2%, reaching approximately $106.1 billion by 2035. [1] While access to this data requires navigating municipal contracts and privacy regulations, its rarity and geographic breadth make it a highly strategic asset. For AI developers, this dataset offers a unique opportunity to build and validate high-value models for this rapidly expanding $106.1B market. [1] ⚠ Diligence (valuable data, access to negotiate): Primary data ownership likely resides with municipal clients (e.g., Region of Peel, Toronto Water).; Access requires navigating municipal service contracts and potential public sector privacy regulations.; Value lies in the aggregated, multi-decade historical flow and rainfall patterns across different geographies.; Company acts as a data processor/custodian via their web-based delivery platform. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Flowmetrix possesses a significant, multi-decade corpus of time-series data from hundreds of deployed industrial sensors. This dataset is a prime asset for industrial AI vendors seeking to develop and validate predictive maintenance algorithms, particularly for hydraulic modeling and equipment calibration. In a predictive maintenance market projected to grow at over 23% annually, this long-term monitoring data offers a rare opportunity to train models on real-world operational and failure events.
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 Volume58
4 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 Demand92
AI buyer demand is exceptionally high, driven by the rapid 23.2% CAGR of the predictive maintenance market, which is fueled by the convergence of IoT and AI in industrial applications. [1]
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 Feasibility50
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 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 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 — 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 — Flowmetrix is an ideal target as it provides specialized field services for water/sewer infrastructure monitoring, generating vast, proprietary sensor data as a by-product which it does not appear to sell directly. [3, 8] Issues: Data ownership is a key question, as the data is generated on their clients' (municipalities) infrastructure and rights to resell would need careful verificatio; The company uses third-party machine-learning software ('infinitii ai FlowWorks') for its services, but does not appear to be the vendor of this software. [8]; An unrelated data analytics consultancy exists at a similar domain ('flowmetrix.com'), so care must be taken to engage the correct entity at 'flowmetrix.ca'. [7
- Deep Qualification90
⚠ needs review — Flowmetrix is a service provider that collects and manages environmental data for its municipal clients; the data is a work product owned by the customer and not a saleable asset of the company. [data is owned by the company's customers]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
The company provides data via downloadable tabular logs, indicating structured datasets optimized for streamlined data ingestion by AI development teams.
IoT / sensor data
Flowmetrix operates a large-scale IoT network, with evidence of over 350 deployed sewer sensors, generating valuable real-world data for complex use cases like municipal hydraulic modeling.
Industrial data
The dataset includes specialized flow meter data from both laboratory and in-situ field tests, providing the ground-truth calibration events essential for training accurate predictive models.
Event streams
With over two decades of project history, the company offers continuous event streams from long-term monitoring programs, providing the rich historical data needed to capture seasonality and rare equipment failures.
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
Flowmetrix 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 was valued at $13.4 billion in 2025, projected to grow at a CAGR of 23.2% (2026-2035). [1]. Investment score 70.8/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
From the marketplace
Explore live data opportunities
Enerkem — Regulatory Records Dataset Opportunity
View opportunity →retailBargainhardware — Maintenance Logs Dataset Opportunity
View opportunity →industrialExplor — Industrial Operations Dataset Opportunity
View opportunity →Data Academy
Learn before you deal
- How a Data Transaction Works3 min read
- What you are entitled to sell3 min read
- 5 Mistakes That Drive Buyers Away3 min read