Dataset opportunity
Opera Energie — Regulatory Records Dataset Opportunity
Moderate regulatory records dataset held by Opera Energie, usable for Regulatory RAG and Compliance Copilots.
Score
68.2
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
56%
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 Artificial Intelligence in RegTech market = $2.57B in 2025, CAGR 36.9%.
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.
- 📦Data product
Observatoire des prix de l’énergie (Energy Price Observatory)
source ↗
Profile
Dataset profile
Type
Regulatory Records Dataset
Modality
Text
Sector
other
Volume
Moderate
Freshness
Real-time
Rarity
Medium
Accessibility
Partial
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
RegTech & compliance-AI vendors
Opera Energie holds a Regulatory Records Dataset in Text modality, comprising detailed business_records and regulatory filings. This dataset contains granular B2B energy consumption patterns, contract terms, and internal market analyses, making it a prime source for training a Regulatory RAG system to accurately answer complex compliance and market-related queries.
The business value is underscored by the Artificial Intelligence in RegTech market, which was valued at $2.57 billion in 2025 and is projected to grow at a 36.9% CAGR. Despite access complexities, such as client data ownership, the dataset's rarity is a key asset. The proprietary market benchmarks and supplier pricing history are highly valuable and justify negotiating access, given the explosive growth and demand for specialized data to power AI compliance tools. ⚠ Diligence (valuable data, access to negotiate): Data includes sensitive B2B consumption patterns and contract terms; Ownership of consumption data likely resides with the end-clients (SMEs/Copropriétés); Proprietary market benchmarks and supplier pricing history are the most accessible assets · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Opera Energie possesses a unique corpus of French energy regulatory documents, directly linked to real-world commercial activity. The dataset includes energy audits and compliance obligations, enriched by business records from over 10,000 SMEs and real-time operational data. For RegTech and compliance-AI vendors, this is a high-value asset for developing sophisticated regulatory RAG systems, enabling them to capture a share of the rapidly expanding AI in RegTech market, which is growing at a CAGR of 36.9%. This data provides the ground truth needed to power next-generation compliance automation tools.
See dimension details ↓- Dataset Specificity62
dominant 'regulatory', sector other, 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 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 Value74
fit for Regulatory RAG
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 explosive growth of the AI in RegTech market (CAGR 36.9%) as companies urgently seek specialized data to build and train advanced compliance models.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility56
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 Strength74
4 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 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 Orientation39
1 data-appetite signals (1 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 Audit92
✓ good target — The company is a perfect fit; it's an energy broker for businesses, a real-world service whose operations generate proprietary client consumption data as a by-product, and it does not sell data or software as its core product.
- Deep Qualification90
⚠ needs review — Opera Energie is a strong data holder candidate whose core business as an energy broker generates a valuable by-product dataset of B2B consumption data and market/regulatory analysis. However, the data is owned by the end-customer and legal documents explicitly prohibit sharing with commercial or advertising actors, making direct resale of the raw data unlikely. [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.
business_records
This evidence indicates a collection of commercial records detailing supplier offers and subscription management for over 10,000 SMEs, providing valuable ground-truth for models analyzing business compliance.
IoT / sensor data
The holder possesses time-series IoT data used for real-time monitoring and analysis of energy transmission parameters, offering a technical, operational layer essential for verifying regulatory compliance models.
Regulatory records
This text data consists of energy audits and compliance documents related to French regulatory obligations, forming the core corpus for training and validating regulatory intelligence AI systems.
Data catalog / marketplace
This points to a curated data catalog or market report, demonstrating the holder's capability in structuring and analyzing energy market data, which signals a higher-quality, more organized dataset for AI training.
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
Opera Energie Regulatory Records — a Moderate regulatory records dataset (Text modality) in the other domain. Primary AI use-case: Regulatory RAG. Market signal: Global Artificial Intelligence in RegTech market = $2.57B in 2025, CAGR 36.9% (source: Research and Markets).. Investment score 68.2/100 (confidence 0.56). Recommended action: License.
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Learn before you deal
- Data licensing, term by term4 min read
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