Those involved in energy efficiency and decarbonization know how difficult it is to develop an energy efficiency proposal for an industrial plant.
And they have probably already faced one or more of these problems:
Impossible to analyze hundreds of options, you are forced to work with the technologies you already know, without knowing if they are the best.
Too many factors, too many variables, little time to make informed decisions, and tools – like Excel – that are inadequate for the type of complexity faced.
The J4Energy Sales Co-Pilot eliminates these difficulties, speeding up the creation of precise and advantageous commercial proposals for the customer.
Thanks to the Sales Co-Pilot, it is not necessary to have access to all the plant data to start.
The software integrates basic data (bills, processes, nameplate data) with synthetic data, creating a high-fidelity digital copy (Digital Twin) of the plant.
Thanks to the Digital Twin of the plant, the Sales Co-Pilot simulates hundreds of technologies and configurations in a few minutes, using our proprietary library of energy solutions.
Thanks to the Digital Twin of the plant, the Sales Co-Pilot simulates hundreds of technologies and configurations in a few minutes, using our proprietary library of energy solutions.
The analysis generated by the Co-Pilot can be transformed directly into a clear and structured commercial proposal, ready to be presented to the customer.
A new approach to decarbonization:
The analysis and creation of decarbonization proposals are complex activities, traditionally entrusted to manual processes and specialist studies.
The idea that software can automate this process is new for many companies and raises doubts about its effectiveness.
For this reason, the Sales Co-Pilot has been tested in the field on over 3000 complex energy analyses, demonstrating an average accuracy of 97% compared to traditional methods.
The models and algorithms of j4energy are the result of the scientific research of our Co-Founder and CTO Stefano Moret, Group Leader at ETH Zurich and winner of the ERC Grant 2024.
The algorithms and models have been tested and validated by comparison with real datasets, integrating advanced optimization, machine learning and energy simulation methodologies, to ensure accurate and replicable results.
From Academia
to Industry
Energy Co-Pilot uses models and algorithms developed by Stefano Moret, Group Lead at ETH Zurich and winner of the ERC Grant 2024.
For 12 years, Stefano has been studying the application of mathematical models to complex energy systems in the best engineering schools in the world.
Discover how a large Italian utility reduced proposal creation time by 93% and doubled the closing rate.
Who is the Sales Co-Pilot for?
The Sales Co-Pilot is designed for any company involved in creating decarbonization and energy efficiency proposals, such as ESCOs, Utilities, Consulting Firms and Engineering companies.
Increase the number of offers generated by up to 10 times, accelerating the sales cycle and maximizing closing opportunities.
Reduces proposal creation time from weeks to a few hours, improving operational efficiency without increasing structural costs.
Eliminates complex manual activities and allows you to generate more precise and competitive offers without depending on technical resources.
Allows sales teams to present personalized and optimized proposals without waiting weeks for analysis.
Simulates hundreds of technologies and configurations in a few minutes, identifying the most advantageous solution for each customer.
More proposals, more sales
Generate up to 10 times more proposals in the same time.
Speed
Reduce proposal creation time from weeks to hours.
Better precision
Analyses based on advanced energy models, enabled by a proprietary library containing hundreds of energy technologies.
Greater independence
The sales team can develop offers without depending on offer engineering.
More ROI for customers
Offer solutions with the best possible economic and environmental impact.
Precision
Output accuracy of 97% compared to traditional analyses.
More effective customer screening
Identify and focus resources only on opportunities with greater potential, avoiding wasted time.
Differentiation for utilities
Go from a simple supplier to a solution provider, offering customers a specialized consulting service, allowing them to monetize in a short time, and avoiding competing ONLY on the price of energy.
Frequently Asked Questions
Can the Sales Co-Pilot handle the complexity of an energy analysis?
Yes, J4Energy is built on over 15 years of energy research conducted at ETH Zurich. By combining artificial intelligence (AI) with proprietary algorithms, it is capable of simulating complex scenarios with extremely high precision. The system has already been successfully tested and implemented by major corporations such as Shell, Electrolux, and the Florence Group, confirming its robustness and reliability in real-world applications.
How difficult is it to use the software?
The Sales Co-Pilot from J4Energy has a user-friendly and intuitive interface, designed with simplicity in mind so that even non-technical users can operate it effectively. The platform is built to reduce the learning curve, ensuring that users can start generating results quickly without the need for specialized knowledge. Additionally, J4Energy offers personalized support and training, guiding each client step-by-step through the process. This approach ensures a smooth and swift implementation, enabling users to start benefiting from the software’s results from the very first day.
What kind of data does the platform require?
The platform’s data input process, known as the “wizard,” is designed to be straightforward and requires only a few simple pieces of information:
- Location of the plant, working days, and industry code (ATECO)
- Energy services: For all selected energy services, daily profiles can be entered or defined custom profiles can be created.
- Energy resources: The system requires information on energy consumption and costs, with the option to upload your own consumption profiles or scan bills directly.
- Installed technologies and their respective sizes (if known).
Once this basic data is provided, the tool can run simulations that yield accurate results, even if some data is missing. In the absence of certain inputs, the system uses synthetic data generated specifically for the relevant scenario. This ensures that the analysis remains accurate and reliable despite missing information.
Operational data needed for the plant management:
- Production schedule
- Shift patterns
Field data obtained from monitoring systems (if available) The system can also integrate predictive data on energy prices, weather, and solar/radiation data for photovoltaics and wind turbines, as well as data from the J4Energy database regarding machine specifications.
Is it possible to integrate my own technologies?
Absolutely. The platform already comes with an extensive library containing the best technologies available on the market. However, if the technology you’re interested in isn’t included, it can be easily added. Users can add new technologies (respecting privacy rules) by specifying key details such as: capital expenditure (CAPEX), maintenance costs, lifetime, capacity factor, and maximum capacity. If the plant doesn’t have monitoring systems, J4Energy offers support for the installation of necessary solutions, ensuring a smooth transition without disrupting operations.
How long does the analysis take?
The initial analysis, which follows the data input procedure (the “wizard”), typically takes between 3 and 5 minutes. The result is an “as-is” energy analysis of the reference plant. In addition, two simulations are automatically created: “light_decarb” and “high_decarb”. The first focuses on a technological configuration that optimizes costs, while the second maximizes savings in terms of greenhouse gas emissions, requiring a larger investment and longer payback times. Each additional simulation created with the tool takes around 5 minutes to process and deliver precise, comprehensive results.
How accurate is the analysis?
The analysis conducted by the tool, along with the subsequent simulations, is highly accurate. The typical accuracy rate compared to traditional energy analysis proposals from our clients ranges between 95% and 98%. To validate the tool’s accuracy and the level of detail it can provide, we perform an analysis that has already been validated (in black box mode) using the tool ourselves. We then present the output results to the client, demonstrating the tool’s precision and reliability. This hands-on approach allows the client to experience firsthand how accurate and dependable the system is.
Please feel free to write to our support team.
