Dataset opportunity
Haslerhomes — Public Procurement Dataset Opportunity
Moderate public procurement dataset held by Haslerhomes, usable for Tender Intelligence and Document Intelligence.
Score
64.8
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 Procurement Analytics market was valued at USD 4.27 Billion in 2024, with a projected CAGR of 23.50% (2024-2032).
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
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — licensing rights to clarify
Buyer persona
GovTech & procurement-intelligence vendors
Haslerhomes holds a Public Procurement Dataset in Text modality, derived from its business records, industrial data, and procurement activities. This data contains detailed evidence of project bids, material costs, subcontractor agreements, and timelines, making it exceptionally well-suited for training a Tender Intelligence AI model to analyze bidding patterns, forecast project costs, and identify winning procurement strategies in the construction sector.
The global procurement analytics market was valued at USD 4.27 Billion in 2024 and is projected to grow at a CAGR of 23.50%. [1] This significant growth highlights the intense demand for industrial_data that can provide a competitive edge. Although access requires navigating third-party tools and potential client confidentiality clauses, the rarity and actionable nature of this real-world procurement data for AI buyers justifies the effort, offering a distinct advantage in a rapidly expanding market. ⚠ Diligence (valuable data, access to negotiate): Data likely resides in third-party project management tools (e.g., Buildertrend); Project-specific data may have client confidentiality clauses; Physical records for older projects may need digitization · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves the holder owns a proprietary, decade-plus dataset detailing high-value construction procurement and project execution. The data documents collaborations with top-tier suppliers and includes granular cost breakdowns, offering a rare view into a specialized supply chain. For GovTech and procurement intelligence vendors, this asset is crucial for training Tender Intelligence models to predict costs and identify expert partners in a global procurement analytics market growing at over 23% annually.
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 Rarity70
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 Freshness46
periodic
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 Demand90
AI buyer demand is extremely high, driven by the procurement analytics market's rapid growth, which is projected at a 23.50% CAGR. [1]
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 Feasibility44
low 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 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 — 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 Audit83
✓ good target — This custom home builder is a good target as it's an operational SME that generates proprietary project data as a by-product and does not sell it, though the initial 'public procurement' data mention was erroneous. Issues: The initial opportunity description 'Public Procurement Dataset' is completely unrelated to the company's actual business of custom home building and appears to; The company uses Buildertrend project management software, which means some of their operational data resides within a third-party platform, though they still o
- Deep Qualification20
⚠ needs review — This is a data holder in the construction sector, but the 'Public Procurement' label is incorrect as they build private luxury homes, and the project data is likely owned by the clients, posing significant acquisition and licensing challenges. [data is owned by the company's customers; dataset_type implausible vs real activity: The target builds private luxury custom homes, not public works, so it would not hold a 'Public Procurement Dataset'. [1, 7, 9]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
business_records
The dataset contains detailed records of luxury and large-scale construction projects since 2011, including granular cost breakdowns and timelines essential for building predictive tender pricing models.
Industrial data
This evidence confirms specialized industrial data on Net Zero energy homes and high-performance construction, a critical input for analyzing emerging sustainability criteria in competitive bids.
Procurement / tenders
The holder possesses historical text data mapping its procurement collaborations with elite architects, designers, and tradespeople, providing a unique and verifiable network of high-value suppliers.
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
Premium dataset report
Haslerhomes Public Procurement — a Moderate public procurement dataset (Text modality) in the industrial domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Analytics market was valued at USD 4.27 Billion in 2024, with a projected CAGR of 23.50% (2024-2032). [1]. Investment score 64.8/100 (confidence 0.49). Recommended action: Acquire.
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