Dataset opportunity
Absturzsicherung — Public Procurement Dataset Opportunity
Large public procurement dataset held by Absturzsicherung, usable for Tender Intelligence and Document Intelligence.
Score
71.4
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
65%
Action
License
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 Procurement Analytics market = $7.11 billion in 2026, CAGR 23.85%.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-19
ABS Safety eröffnet neues Schulungszentrum in Kevelaer
this-magazin.de ↗
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.
Profile
Dataset profile
Type
Public Procurement Dataset
Modality
Text
Sector
industrial
Volume
Large
Freshness
Periodic
Rarity
Medium
Accessibility
Open / API
Legal
Owned by the company — clean to license
Buyer persona
GovTech & procurement-intelligence vendors
Absturzsicherung holds a specialized Public Procurement Dataset in Text modality, containing business records, procurement documents, and project data related to fall protection system tenders. This structured and unstructured data is directly applicable for a Tender Intelligence use case, providing granular insights into project specifications, competitor bidding patterns, and pricing within the industrial safety sector.
The value of this data is highlighted by the global Procurement Analytics market, estimated at $7.11 billion in 2026 with a projected 23.85% CAGR. [2] While access may require negotiation due to factors like unstructured project data (PDF/Forms) and the conservative data sharing policies of a German SME, the rarity and specificity of this industrial_data make it a high-value asset for training sophisticated AI buyer models. ⚠ Diligence (valuable data, access to negotiate): Technical BIM/CAD data is already partially externalized via the CADENAS partner platform; Project-specific safety planning data is likely stored in unstructured formats (PDF/Forms); German SME status may imply conservative data sharing policies · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves the holder possesses direct textual data on public tender processes, a core asset for building Tender Intelligence platforms. This dataset is enriched by structured product catalogs, detailed project specifications, and technical CAD metadata, offering a comprehensive view of industrial procurement. For GovTech and procurement-intelligence vendors, this data unlocks the ability to train AI models that can predict tender requirements and outcomes in a procurement analytics market projected to reach $7.11 billion by 2026.
See dimension details ↓- Dataset Specificity78
dominant 'procurement', sector industrial, 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 Rarity46
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume70
6 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness62
API/open (current)
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
fit for Tender Intelligence
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI buyer demand for this data is high, driven by the rapid expansion of the Procurement Analytics market, which is projected to grow at a 23.85% CAGR. [2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility78
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 Strength89
5 evidence types, 6 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 Orientation22
0 data-appetite signals (0 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
surplus=medium, 1 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 Audit92
✓ good target — Excellent target: a German SME manufacturer and installer of fall protection systems, a niche operational business generating proprietary installation and maintenance data as a by-product, which does not appear to be selling it. Issues: The company offers digital planning and documentation tools (ABS Plan, ABS Doku) which might be a step towards monetizing their data/expertise as a product, sli
- Deep Qualification70
✓ pass — ABS Safety is a manufacturer of fall protection systems that also provides planning and training services. This business model makes it plausible that they hold project and tender-related data as a by-product, although there is no direct evidence of a structured 'Public Procurement Dataset'.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
The holder maintains downloadable product catalogs in multiple languages, providing a structured source of commercial SKUs and specifications valuable for training AI to map tender needs to available solutions.
Procurement / tenders
The dataset contains explicit textual references to the public tender process, directly confirming its value for training and validating Tender Intelligence models for the GovTech sector.
Industrial data
The company generates data related to Building Information Modelling (BIM), indicating access to technical project data and digital twin specifications that enrich tender analysis with deep industrial context.
business_records
The holder captures structured project requirements directly from clients via enquiry forms, creating a valuable repository of real-world customer needs and specifications.
Data catalog / marketplace
The company possesses a catalog of CAD geometries containing rich technical metadata, offering a highly structured and detailed dataset for fine-grained analysis of industrial components and project designs.
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
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Absturzsicherung Public Procurement — a Large public procurement dataset (Text modality) in the industrial domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Analytics market = $7.11 billion in 2026, CAGR 23.85% (source: Mordor Intelligence). [2]. Investment score 71.4/100 (confidence 0.65). Recommended action: License.
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