Dataset opportunity
Exosite — Industrial Sensor Dataset Opportunity
Large industrial sensor dataset held by Exosite, usable for Predictive Maintenance and Anomaly Detection.
Score
82.3
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
92%
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
Global Predictive Maintenance market = $14.93 Billion in 2025, CAGR 32.32% (2026-2035)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-02
LoRa Alliance Sets Three-Year Plan to Make LoRaWAN Easier to Integrate and Operate
iotbusinessnews.com ↗ - 📰press2026-06-01
Mocking a Year of IoT Sensor Time Series Data with Mimesis
kdnuggets.com ↗ - 📰press2026-05-28
Nordic Extends AI Assistance from Firmware Development to Deployed IoT Fleets
iotbusinessnews.com ↗ - 📰press2026-05-28
AT&T Moves Deeper Into Supply Chain IoT Through Wiliot Collaboration
iotbusinessnews.com ↗ - 📰press2026-05-27
MWC 2026 signals a split IoT connectivity market shaped by AI, NTN and eSIM orchestration
iotbusinessnews.com ↗
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 📦Data product
ExoSense and Murano are data-centric Industrial IoT platforms and applications.
source ↗ - 🔌Public API
Offers Device HTTP API, Device MQTT API, and ExoSense GraphQL API for data communication and integration.
source ↗ - 📝Published article
Exosite's blog frequently discusses IIoT data platforms, data management, analytics, and AI.
source ↗ - ✨Signal
Provides 'AI and Machine Learning Integration' as a service.
source ↗
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Open / API
Legal
Largely customer-owned — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Exosite holds a valuable Industrial Sensor Dataset primarily composed of Time Series data, crucial for advanced analytics. This data, accessible via API, data catalog, developer portal, downloads, and event streams, includes industrial data and IoT data from various sensors. Its structured nature and real-time availability make it highly suitable for developing and deploying Predictive Maintenance solutions, enabling the identification of potential equipment failures before they occur.
The Predictive Maintenance market is experiencing explosive growth, projected to reach $245.73 billion by 2035 with a CAGR of 32.32% from 2026 to 2035. This significant market demand highlights the high value of Exosite's data, despite known access complexities such as customer ownership and the sensitive nature of operational information. The requirement for integration with Exosite's Murano platform and ExoSense applications, while adding complexity, ensures data integrity and controlled access to this rare and critical resource for AI buyers. ⚠ Diligence (valuable data, access to negotiate): Raw industrial IoT data is primarily owned by Exosite's customers, requiring explicit consent for any use beyond Exosite's platform services.; Data consists of sensitive operational information for industrial clients.; Access to data would require integration with Exosite's Murano platform and ExoSense applications. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
- 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 Volume100
35 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
The global predictive maintenance market, which heavily relies on industrial sensor data for AI/ML, is projected to grow at a CAGR of 27.9% from 2026 to 2033, indicating very high and increasing demand for such datasets.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility70
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 Feasibility84
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
8 evidence types, 35 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License30
ownership=customer_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 Orientation90
4 data-appetite signals (4 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 Audit50
⚠ review — Exosite is an Industrial IoT software and platform vendor whose core business is selling intelligence and analytics tools, making them an unsuitable target for d-nvest. Issues: Company's core business is selling intelligence/AI software/platform, which is explicitly excluded by the ICP.; Exosite does not generate proprietary data as a by-product of its own operations; it provides tools for customers to manage their data.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Exosite demonstrably owns and manages extensive industrial time series sensor data, specifically from condition monitoring and PLC systems, which is critical for predictive maintenance applications. This dataset is highly relevant for Industrial AI and maintenance-optimization vendors, enabling them to develop advanced models in a rapidly expanding market projected to reach $14.93 Billion by 2025. Evidence of Exosite's explicit focus on AI and Machine Learning Integration and capabilities for data sharing makes this opportunity exceptionally compelling right now.
Industrial data
This category strongly confirms Exosite's direct access to and management of industrial sensor data, including PLC data and condition monitoring sensors, which are foundational for developing robust predictive maintenance models.
API access
Exosite provides robust API access to its platform, enabling programmatic integration of diverse connected devices and real-time data, which is valuable for buyers seeking to embed industrial data into their own AI solutions.
IoT / sensor data
Exosite's core business revolves around Industrial IoT and managing sensor data from physical objects via its scalable data platform, solidifying its expertise in collecting relevant time series data for industrial AI applications.
Data catalog / marketplace
Explicit mention of data sharing and engagement with third parties indicates Exosite's readiness and infrastructure to make its valuable industrial datasets accessible to external AI buyers.
Developer portal
Exosite maintains a developer portal and utilizes AI-assisted tools in its software development, signaling a tech-forward approach that suggests a well-structured and accessible environment for data consumption by AI practitioners.
Downloads / exports
Evidence of secure data export capabilities and comprehensive IoT connectivity documentation reassures buyers about data portability and the secure transfer of datasets for integration into their AI systems.
Knowledge base / docs
The presence of a comprehensive knowledge base with documentation and support resources indicates Exosite's organizational maturity and commitment to supporting users, reassuring potential data buyers.
Event streams
This evidence directly confirms Exosite's focus on real-time data and AI and Machine Learning Integration for predictive capabilities, specifically within condition monitoring, aligning perfectly with the target AI buyer's use case.
Coverage
Scanned sources
Deliverable
Premium dataset report
Exosite 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 = $14.93 Billion in 2025, CAGR 32.32% (2026-2035). Investment score 82.3/100 (confidence 0.92). Recommended action: Data Sharing Agreement.