Dataset opportunity
Agilityrobotics — Industrial Sensor Dataset Opportunity
Moderate industrial sensor dataset held by Agilityrobotics, usable for Predictive Maintenance and Anomaly Detection.
Score
47.5
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
49%
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 size (indicative estimate)
Global Predictive Maintenance market was valued at $14.2 billion in 2025, projected to grow at a CAGR of 27.9% (2026-2033).
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.
- 🧑💻Hiring a data role
Recruiting for AI/ML and Robotics Software Engineers
source ↗
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — licensing rights to clarify
Buyer persona
Industrial AI & maintenance-optimization vendors
Agility Robotics holds a unique Industrial Sensor Dataset generated by its bipedal robots in third-party logistics facilities. The data includes rich Time Series modalities crucial for Predictive Maintenance, such as `iot_data` from high-fidelity IMUs and joint torque sensors, `image_collection` data from LiDAR, and operational `event_streams`. This complex telemetry provides a comprehensive foundation for training AI models to anticipate and diagnose hardware failures before they cause operational downtime.
This dataset is exceptionally valuable as it serves the global Predictive Maintenance market, which was valued at USD 14.2 billion in 2025 and is projected to grow at a CAGR of 27.9%. While access involves navigating co-ownership constraints and the data's high strategic value to Agility's own 'Physical AI' stack, its rarity and direct applicability to a multi-billion dollar market make it a compelling asset for any AI buyer focused on industrial automation and asset management. ⚠ Diligence (valuable data, access to negotiate): Data is generated within third-party logistics facilities (e.g., Amazon, GXO), potentially creating co-ownership or privacy constraints.; High technical complexity of raw robotics telemetry (LiDAR, IMU, joint torques) requires specialized decoding.; Strategic value of data for their own 'Physical AI' stack may make them reluctant to license to competitors. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Agility Robotics possesses a substantial and proprietary dataset of time-series sensor data, generated from over 65,000 hours of real-world industrial robot operation. This unique data is a critical asset for AI vendors developing predictive maintenance solutions, enabling them to train models that can anticipate failures in complex robotic systems. In a market projected to grow at a CAGR of 27.9%, this dataset offers a rare opportunity to gain a competitive edge in industrial automation and maintenance optimization.
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 Volume52
3 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 Demand90
Buyer demand is extremely high, driven by the rapid growth of the Predictive Maintenance market, which is projected to expand at a 27.9% CAGR as industries heavily invest in AI to reduce equipment downtime.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
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 Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
ownership=company_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 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 — 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 Audit58
⚠ review — Agility Robotics is a poor fit because its core business model includes Robots-as-a-Service (RaaS) and a cloud software platform (Agility Arc) for fleet management, which constitutes selling intelligence and a data-driven service. Issues: Company's core business is selling AI-enabled robots and a software platform, which is a form of selling intelligence, making it a bad fit per the ICP.; The business model is explicitly Robots-as-a-Service (RaaS) and outright sales, both of which include software, maintenance, and a cloud platform (Agility Arc) ; The company is not an SME; it has between 410 and 500 employees and is valued at over $1.75 billion. [1, 2, 4]; The data generated by the robots is not 'dormant'; it is actively used to improve the 'Physical AI' models and is a core part of the value proposition for their
- Deep Qualification90
✓ pass — Agility Robotics is a strong data holder candidate. It sells humanoid robot automation as a service, generating a vast and unique industrial sensor dataset as a by-product. While data is generated at customer sites (Amazon, GXO), creating a mixed ownership model, Agility explicitly carves out rights to use aggregated and anonymized data to improve its core AI platform. An imminent SPAC-led public offering creates a compelling trigger for negotiation.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This represents a massive collection of time-series sensor data, logged over 65,000 hours of continuous industrial operation, which is invaluable for training robust predictive maintenance algorithms.
Event streams
The dataset includes event streams cataloging over 100,000 discrete tasks, allowing AI models to correlate specific operational actions with sensor-level performance and potential degradation.
Image collection
This points to a corresponding image collection used to train the robot's AI stack, providing crucial visual context for environmental conditions and physical states that can augment time-series maintenance models.
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
Agilityrobotics 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 $14.2 billion in 2025, projected to grow at a CAGR of 27.9% (2026-2033) (source: Grand View Research).. Investment score 47.5/100 (confidence 0.49). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Portus Datacenters — Maintenance Logs Dataset Opportunity
View opportunity →industrialTek Trol — Industrial Sensor Dataset Opportunity
View opportunity →industrialPme Benelux — Maintenance Logs Dataset Opportunity
View opportunity →Data Academy
Learn before you deal
- Data licensing, term by term4 min read
- Is Your Data Worth Money?3 min read
- What is a Dataset Worth?3 min read