The most comprehensive performance audit on the market

Diagnosis through data

It is essential to have a clear picture of the performance of your plant and we belive that none of the traditional methods are satisfactory. We have developed a new and innovative method, based on the analysis of real production data using unique algorithms, to accurately identify degradations.

Discover X-PLORE technology


X-PLORE method

4 steps to make the right decisions

1. Data collection

We retrieve historical production data directly from the inverters. If necessary, we implement a measurement campaign to obtain the most accurate and detailed information possible.

2. Data analysis

Using our unique algorithms, we analyze the collected data to provide you with an accurate diagnosis of your facility's performance, detecting all defects and anomalies that affect your plant's production.

3. Recommandations

On the basis of the analyses contucted, our engineers propose the most appropriate solutions to enable your plant to regain an optimal level of performance. For each type of problem, we are able to propose a solution.

4. A complete analysis report

We provide you with a complete report, which includes all the elements of analysis, with a study of the financial impacts of the identified downgrades and a revenue projection. We also offer you a detailed action plan with a calculation of the return on investment of the recommended solutions.
In a few clicks, evaluate the performance of your plant and discover what Feedgy can do for you

Do you really know the performance of your plant?

How the X-Plore audit guarantees the profitability of your installations



Analysis of all plant parameters

Dynamic vision of production from commissioning

Consideration of all environmental factors



Rigorous methodology based on real data

The invisible revealed through our analysis algorithms

Identification of more than 20 degradations thanks to their electrical signatures



Proposed actions to be taken to increase production

Quantification of historical losses , financial risks and potential gains

Optimization of the costed design for a minimum gain of 10%.