Dataset opportunity
Livingpackets — Mobility Telemetry Dataset Opportunity
Large mobility telemetry dataset held by Livingpackets, usable for Predictive Maintenance and Anomaly Detection.
Score
48
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
79%
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 = $15.10B in 2025, CAGR 31.1%.
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
Mobility Telemetry Dataset
Modality
Time Series
Sector
mobility
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify · PII/regulated
Buyer persona
Industrial AI & maintenance-optimization vendors
Livingpackets holds a Mobility Telemetry Dataset generated by its proprietary 'THE BOX' IoT hardware on active customer shipments. This Time Series data, evidenced by `iot_data` and `event_streams`, captures granular metrics such as shocks, temperature, and routes, making it directly applicable for training Predictive Maintenance models to anticipate equipment and transit failures.
The business value is significant, as the global Predictive Maintenance market was valued at $15.10 billion in 2025 and is projected to grow at a 31.1% CAGR. [11] While access requires negotiation due to data originating from client shipments and the company's high awareness of its value, its demonstrated use for 'forensic-grade' insights underscores its rarity and strategic worth for buyers aiming to gain a competitive edge in logistics. ⚠ Diligence (valuable data, access to negotiate): Data is generated via proprietary IoT hardware (THE BOX) but involves customer shipments.; Telemetry data (shocks, temperature, routes) is likely aggregated by LivingPackets, but specific cargo details belong to clients.; Company already uses data for 'forensic-grade' logistics insights, suggesting a high awareness of data value. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
The evidence proves Livingpackets possesses a substantial proprietary dataset covering over 23m kilometers of operational shipment telemetry. This unique collection of IoT sensor data and real-time event streams directly addresses the core needs of industrial AI vendors developing predictive maintenance solutions. In a predictive maintenance market growing at over 30% annually, this dataset offers the ground-truth operational data required to train models that can anticipate and prevent costly failures in logistics and high-value shipping.
See dimension details ↓- Dataset Specificity90
dominant 'iot_data', sector mobility, 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
13 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 Demand95
AI buyer demand is exceptionally high, driven by the Predictive Maintenance market's explosive projected growth at a 31.1% CAGR, which is fundamentally reliant on high-quality, real-world telemetry data. [11]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility34
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 Feasibility66
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
5 evidence types, 13 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
ownership=mixed, 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 Audit75
⚠ review — The company's core business is selling a 'Packaging-as-a-Service' subscription which includes data and alerts, making it a seller of intelligence, not just a holder of dormant data. Issues: The company's business model is explicitly 'Packaging-as-a-service', where customers pay a subscription for using the smart boxes and associated services. [1, 3; The service includes an interface/app to track and get alerts for all deliveries, which constitutes selling intelligence derived from the data. [10, 8]; The pricing page explicitly offers a 'data and alerts offer' and mentions building custom data solutions for clients, confirming they productize the data. [12]; The company provides an API to connect with client systems (WMS, TMS), further indicating that the data/intelligence is a core part of their product offering. [
- Deep Qualification80
✓ pass — Livingpackets operates a 'packaging-as-a-service' model where the telemetry data is a by-product, making it a data_holder. However, data ownership is mixed and licensing rights for resale are unclear due to the data's origin from client shipments, requiring careful negotiation.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
This evidence consists of tabular data from the company's published industry studies, providing valuable market context on the financial impact of shipping failures for feature engineering.
Event streams
These are high-value time-series data streams capturing discrete failure events like breakage and theft, providing the critical labels needed to train and validate predictive models.
IoT / sensor data
This is the core dataset of continuous sensor data from live shipments, providing the raw operational data essential for training predictive maintenance algorithms to anticipate real-world equipment stress.
Developer portal
This reference to an in-house team of developers and engineers signals the technical talent behind the data systems, providing confidence in the data's quality and architectural integrity.
Claims records
These are structured records of loss and damage claims, providing the ground-truth financial data that directly links sensor telemetry to tangible business outcomes for building ROI-focused models.
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
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Deliverable
Premium dataset report
Livingpackets Mobility Telemetry — a Large mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market = $15.10B in 2025, CAGR 31.1% (source: Market Research Future). [11]. Investment score 48.0/100 (confidence 0.79). Recommended action: Data Sharing Agreement.
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