Dataset opportunity
Gravisrobotics — Industrial Sensor Dataset Opportunity
Moderate industrial sensor dataset held by Gravisrobotics, usable for Predictive Maintenance and Anomaly Detection.
Score
40
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
51%
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 = $13.65B in 2025, CAGR 24.30% (2026-2034).
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-18
Autonomous equipment tech firm Gravis Robotics raises $200M
constructiondive.com ↗ - 📰press2026-08-17
$200M Funding Round Set for Automated Equipment Startup Gravis Robotics
enr.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.
- 📣Press / announcement
Raised $200M Series A from SoftBank for Physical AI scaling
source ↗ - 🧑💻Hiring a data role
Recruiting Perception and Platform engineers for autonomous fleet management
source ↗ - ✨Signal
Deployment of autonomous excavators across global jobsites generating real-world execution data
source ↗
Profile
Dataset profile
Type
Industrial Sensor Dataset
Modality
Time Series
Sector
industrial
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Partial
Legal
Owned by the company — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Gravisrobotics holds a proprietary Industrial Sensor Dataset generated by its Gravis RACK hardware retrofitted onto heavy machinery. This Time Series data, including `industrial_data` and `iot_data`, captures real-world operational metrics directly from client construction sites. The dataset is structured to directly support Predictive Maintenance models, aiming to forecast equipment failure and optimize maintenance schedules.
The value of this data is underscored by the global Predictive Maintenance market, which was valued at $13.65 billion in 2025 and is projected to grow with a CAGR of 24.30% between 2026 and 2034. [3, 6] While access requires navigating client-specific data sharing clearances due to on-site collection, the dataset's rarity and direct applicability to this high-growth market present a significant opportunity. High-value perception data (Lidar/Vision) is also held, representing future potential. ⚠ Diligence (valuable data, access to negotiate): Data is generated via proprietary hardware (Gravis RACK) retrofitted on third-party machinery.; Operational data is collected on client construction sites, potentially requiring site-specific data sharing clearances.; High-value perception data (Lidar/Vision) is likely stored for model training but not yet externalized. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Public evidence confirms Gravisrobotics possesses proprietary time-series sensor data generated by autonomous heavy machinery, including 30-ton excavators. This machine telemetry, captured during real-world physical execution, is a critical asset for AI vendors developing predictive maintenance solutions. In a market projected to reach $13.65B by 2025 and growing at over 24% annually, this rare industrial data offers a significant competitive advantage for training robust AI models that can anticipate equipment failure.
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 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 for Predictive Maintenance solutions is exceptionally strong, driven by a market projected to grow at a CAGR of 24.30%. [3, 6]
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 Feasibility30
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength65
3 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=company_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 Orientation73
3 data-appetite signals (3 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 2 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 — Gravis Robotics' core business is selling an AI-powered software and hardware kit that provides intelligence and autonomy to heavy machinery, making it a technology vendor and not a holder of dormant data. Issues: Company's core product is selling intelligence/AI software (the 'Gravis Rack' and associated OS), which is an explicit exclusion criterion. [6, 7, 11, 14]; The company is a technology vendor that retrofits equipment, not an operational business that accumulates data as a by-product. [10, 14, 17]; Following a $200M Series A, the company is valued at $1B and is scaling rapidly, potentially exceeding the 'SME' and 'giant' criteria. [6, 8, 9]; While their systems generate vast amounts of data ('continuous site sensor'), this data is integral to their AI product's operation and improvement, not a dorma
- Deep Qualification70
✓ pass — The company's model of retrofitting excavators with its 'Gravis RACK' autonomy kit confirms it is a data_holder, generating a valuable industrial sensor dataset as a by-product of its core business. [6, 10] However, as the data is collected on client-owned machinery at third-party sites, ownership and licensing rights are undetermined, representing the main diligence hurdle.
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 points to high-frequency machine telemetry data, essential for training AI models to understand and react to complex physical forces in real-time.
Image collection
The company collects image data of its heavy machinery in operation, a valuable asset for developing computer vision models that complement sensor-based analytics.
Industrial data
This confirms the collection of industrial data from autonomous heavy machinery operating on global jobsites, proving the dataset's real-world operational relevance and scale.
Marketplace
Dataset details
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
Scanned sources
Deliverable
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Gravisrobotics 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 = $13.65B in 2025, CAGR 24.30% (2026-2034) (source: Fortune Business Insights). Investment score 40.0/100 (confidence 0.51). Recommended action: Acquire.
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