Briefly
Program description
Optimizing energy consumption using an AI tool for energy audits.
Within the challenge, it is proposed to develop an AI-supported system that analyzes technical and non-technical data of enterprises, automatically creates foundations for energy audits, generates recommendations, integrates expert edits, meets legislative requirements and increases the efficiency of consulting for SMEs.
Main Information
Supported Activities
AI analysis of technical (consumption, load schedules, operational data) and non-technical data (processes, reports, web information).
Formation of basic and draft energy audits in accordance with legislation (Energieeffizienzgesetz, Kurzberichtsverordnung, ÖN EN 16247-1).
Identification of main energy consumers, KPIs, benchmarking.
Providing recommendations for improving efficiency (lighting, engines, compressed air, waste heat).
Integration of expert experience of consultants.
Scalability across industries and company sizes.
How to Apply
Applications are submitted through the F6S application submission tool.
Evaluation Criteria
Business criteria:
- How well the solution meets Energie AG challenges.
- Available capacity (resources, technical base, team).
- Implementation speed and scalability.
- Partnership potential.
- Presence of proof of effectiveness (prototypes, similar products, existing partnerships, etc.).
Additional criteria:
- Desirability: How precisely does the idea solve the identified problem? Is the solution directly relevant to the posed challenge?
- Feasibility: Can the idea be implemented in practice? Does it take into account the technical, financial and operational constraints of the company and industry?
- Viability: Is the solution economically feasible? Does it provide a favorable cost-benefit ratio? What is the expected return on investment?
- Sustainability: A particularly important aspect for the energy sector. How environmentally friendly and sustainable is the proposed solution?
- Degree of Innovation: How innovative and different is the idea from existing solutions? Does it offer a new approach or perspective?
- Team and Expertise: Who is behind the idea? Does the team or startup have the necessary experience and knowledge to implement the project?
FAQ
The goal is to develop an AI-supported assistance system that enables more efficient and solution-oriented energy consulting and audits for clients. The system should help SMEs and consultants fulfill legal obligations and go beyond them, using available corporate data and documents for energy audits and energy efficiency measures.
Startups that offer innovative solutions for AI-supported energy audits and consulting are eligible to participate.
Consultants and companies face problems such as labor-intensive internal research, difficulty finding the right data and documents, and limited human resources. Most of the necessary data is already available but not used effectively.
- Automatically analyze and structure corporate, energy and sustainability data, as well as technical documentation and plans.
- Generate reports and designs for energy audits/consultations in accordance with relevant regulations.
- Identify main energy consumers and provide benchmarking and KPIs.
- Offer specific action recommendations in various areas (e.g., lighting, engines, compressed air).
- Integrate expert knowledge to validate and refine AI results.
- Be scalable across different industries, company sizes and thematic areas.
- Technical data (energy consumption, load profiles, operational data, questionnaires, etc.).
- Non-technical data (websites, documentation, reports, process descriptions, etc.).
- Various file formats (at least PDF, CSV, XLSX, DOCX, JPEG, etc.).
The solution must support compliance with relevant standards and regulations (e.g., Energieeffizienzgesetz, Kurzberichtsverordnung, ÖN EN 16247-1).
The system should allow experts to validate and refine AI-generated results, ensuring accuracy and practical relevance.
The solution must ensure GDPR-compliant data processing, secure storage and transparent traceability of AI decisions.
The system should highlight irregularities, deviations, errors or missing data. Manual review should be available for image data extraction.
Yes, the solution should be scalable in functionality, data types and volumes and be modular to ensure future expansion (e.g., sustainability reporting, carbon footprint, supply chain resilience, climate risks).
Yes, future extensions should include sustainability reporting, CO₂ reports, climate risk analysis, supply chain resilience and additional support tools (e.g., linking measures to funding, cost evaluation, API integration with energy management systems).
Yes, future versions should allow API integration with existing energy management systems.