Dataset opportunity
Enereco — Public Procurement Dataset Opportunity
Moderate public procurement dataset held by Enereco, usable for Tender Intelligence and Document Intelligence.
Score
69.8
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
Global Procurement Analytics market was valued at $3.8B in 2022 and is projected to register a CAGR of over 23% between 2023 and 2032 (source: GMI)
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
Public Procurement Dataset
Modality
Text
Sector
industrial
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
GovTech & procurement-intelligence vendors
Enereco holds a substantial Public Procurement Dataset composed of text-based documents from its long history in the industrial engineering sector, covering project bids, regulatory filings, and procurement contracts. This body of industrial_data provides a rich foundation for training AI models on Tender Intelligence, allowing a buyer to dissect historical bidding strategies, identify success patterns, and forecast procurement trends in the high-value energy market.
The business value is anchored in the global Procurement Analytics market, which was valued at USD 3.8 billion in 2022 and is projected to grow at a 23% CAGR between 2023 and 2032. [12] While access to this high-value data requires navigating strict NDAs with major energy clients and potential data extraction from legacy formats, its rarity and direct applicability for AI buyers make it a compelling asset for gaining a competitive edge in a rapidly expanding market. [12] ⚠ Diligence (valuable data, access to negotiate): Project data is often subject to strict NDAs with major energy clients (e.g., ENI, Total).; Engineering designs and BIM models are high-value but require technical extraction from legacy formats.; Ownership of specific site data may be shared with the end-asset owner. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Enereco holds a proprietary, multi-modal dataset covering the full lifecycle of major industrial energy projects. It combines deep procurement data on vendors and costs with exclusive regulatory assessments and detailed engineering specifications. For GovTech and procurement-intelligence vendors, this dataset is a rare asset for building next-generation Tender Intelligence platforms, targeting a global market projected to grow at over 23% annually.
See dimension details ↓- Dataset Specificity90
dominant 'procurement', 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 Freshness46
periodic
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
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 exceptionally high for Tender Intelligence applications, driven by a large and fast-growing Procurement Analytics market projected to expand at over 23% CAGR. [12]
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 Feasibility30
medium 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 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 Audit100
✓ good target — Enereco is an ideal target; it's a privately-owned SME engineering firm whose core business is providing project services for the energy and infrastructure sectors, which likely generates a significant amount of dormant operational data as a by-product. Issues: The initial lead mentioned a 'Public Procurement Dataset', which seems incorrect; their procurement services are a consultancy for clients, not a data product t; A different company, 'Eneco', has a large Data & AI department, which caused initial confusion but is unrelated to 'Enereco'.
- Deep Qualification90
⚠ needs review — Enereco is an engineering services firm, not a data seller. The data generated from its procurement and engineering activities for major energy clients is highly sensitive and client-owned, making it legally and practically inaccessible for resale. [data is owned by the company's customers; licensing restricted]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
This is a collection of proprietary engineering designs and technical specifications that provides bidders with a granular understanding of project scope and requirements.
Procurement / tenders
The dataset contains an extensive, proprietary database of international vendors, material costs, and logistics data, essential for competitive benchmarking and supply chain analysis.
Regulatory records
This includes exclusive environmental impact assessments and feasibility reports, offering critical insights into the regulatory risks and compliance hurdles of complex energy projects.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Enereco 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 $3.8B in 2022 and is projected to register a CAGR of over 23% between 2023 and 2032 (source: GMI). Investment score 69.8/100 (confidence 0.49). Recommended action: Acquire.