Dataset opportunity
Moonsurgical — Sensor Telemetry Dataset Opportunity
Moderate sensor telemetry dataset held by Moonsurgical, usable for Predictive Maintenance and Anomaly Detection.
Score
66.1
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
46%
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 = USD 14.93 Billion in 2025, CAGR 32.32% (2026-2035)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-02
Petal Surgical adds more funding for incisionless surgical robot
therobotreport.com ↗ - 📰press2026-05-29
J&J recalls Impella heart pumps after patient dies
medtechdive.com ↗ - 📰press2026-05-28
Ōura to add blood pressure feature following FDA policy change
medtechdive.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.
- 📦Data product
Maestro Insights cloud-based analytics platform
source ↗
Profile
Dataset profile
Type
Sensor Telemetry Dataset
Modality
Time Series
Sector
healthcare
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — GDPR-sensitive (PII review)
Buyer persona
Industrial AI & maintenance-optimization vendors
Moonsurgical holds a rich Sensor Telemetry Dataset (modalité Time Series) derived from IoT data and medical records within healthcare settings. This unique combination provides granular, continuous insights into medical device performance and patient physiological parameters, making it exceptionally valuable for Predictive Maintenance applications. By analyzing these temporal patterns, potential equipment failures can be anticipated, and maintenance schedules optimized, ensuring operational continuity and patient safety.
The market for such data is experiencing significant demand, with the global Predictive Maintenance market valued at USD 14.93 billion in 2025 and projected to reach USD 245.73 billion by 2035, exhibiting a CAGR of 32.32%. The healthcare segment is noted as the fastest-growing within this market. Despite the inherent complexities of accessing GDPR-sensitive data, navigating specific agreements with healthcare providers in hospital settings, and addressing patient privacy concerns through anonymization requirements, the substantial business value in reducing downtime and improving patient outcomes makes this data highly sought after. ⚠ Diligence (valuable data, access to negotiate): GDPR-sensitive data due to healthcare context; Data generated in hospital settings requires specific agreements with healthcare providers; Potential for patient privacy concerns and anonymization requirements · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This opportunity presents access to proprietary sensor telemetry data from Moonsurgical's advanced surgical platforms, directly addressing the critical need for predictive maintenance in high-stakes healthcare environments. With evidence of capturing intra-operative data, OR environment metrics, and kinematics, this dataset is uniquely positioned to empower industrial AI and maintenance-optimization vendors. It offers a rare window into operational efficiencies and equipment performance within a rapidly expanding Global Predictive Maintenance Market, projected to reach USD 14.93 Billion by 2025.
See dimension details ↓- Dataset Specificity78
dominant 'iot_data', sector healthcare, 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 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 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
The global AI in healthcare market, which heavily relies on sensor telemetry data for applications like predictive maintenance, is projected to grow at a CAGR of 43.96% from 2026 to 2034.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
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 Strength56
2 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 License62
ownership=owned, licensing=gdpr_sensitive
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 Orientation39
1 data-appetite signals (1 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 3 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 Audit67
⚠ review — Moonsurgical is not a good target because its core business involves selling surgical robotics that provide AI-powered analytics and insights to healthcare providers, which means they are already selling intelligence derived from their data as a product. Issues: Moonsurgical's Maestro system includes 'Intraoperative analytics and digital OR insights' and 'Maestro Insights', a cloud-based analytics platform that consolid; The company explicitly states they 'enable healthcare providers
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 Moonsurgical's collection of time-series sensor telemetry from live surgical procedures, encompassing intra-operative data, OR environment metrics, and kinematics, which is highly valuable for vendors seeking to develop predictive maintenance and operational efficiency solutions.
Medical records / imaging
This data type indicates Moonsurgical's access to image-based medical records and procedural metrics from over 2,300 patient treatments, offering crucial context for understanding surgical outcomes and the broad application of their platform across diverse clinical indications.
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, JSON
License
One-time license for predictive maintenance use cases, with restrictions on redistribution and secondary sales.
Personal data
Contains PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its proprietary, high-granularity sensor telemetry from surgical devices and patient data, crucial for predictive maintenance in the rapidly growing healthcare sector. The strong market demand for predictive maintenance, with a projected CAGR of 32.32%, underpins its significant valuation.
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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Moonsurgical Sensor Telemetry — a Moderate sensor telemetry dataset (Time Series modality) in the healthcare domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market = USD 14.93 Billion in 2025, CAGR 32.32% (2026-2035). Investment score 66.1/100 (confidence 0.46). Recommended action: Data Sharing Agreement.
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