Innovation for energy solutions

We will give you a read-only login to Deep Energy AI to evaluate your current against default market tariffs.

DeepEnergy provides like-day analysis, load variability disaggregation, 20-year cash-flow and much more!

Fill out the form below, and we will obtain electricity data on your behalf and load it into our software platform.

From there you can explore your energy data, tariffs and costs, export images or raw data samples and much more!

Artificial Intelligence and Machine Learning algorithms have grown in popularity for language models in recent years, despite AI+ML having been 'created' during the 1940s by Turing.

Using modern techniques, applied to 5-minute intervals, an enormous amount of value can be extracted from utility data alone.

Utility data is the 'source-of-truth' when it comes to finance, accounting, carbon reporting or certificate generation. It is also ubiquitous and standardised - if there is a meter, there is metering data.

This allows Virtual Energy Assessments to be conducted across a large volume of metering points and metering data, rapidly!

Connecting to BMS/SCADA is usually a lengthy process due to a lack of data or communications standards, or it being proprietary in nature. Detailed energy assessments can be initiated from the results of a Virtual Energy Assessment, allowing resources to be focused upon poorly performing assets. At this point, behind-the-meter data can be analysed for fine-tuning of the building by experts in the field.

A Virtual Energy Assessment can use a bottom-up (metering) or top-down (modelling) approach. We use a hybrid approach for existing buildings, and a top-down approach for new buildings.

We can adopt existing modelling outputs and mesh them with metering data to provide a synthesis of both.

While energy is a focus, we are experts in technology in the built environment.

Our experience provides us with a holistic perspective across different industries, typologies and use cases.

We engage our clients on a multitude of aspects of technology in buildings, with a principal focus on digitalisation, building optimisation and reporting through development of design briefs, review and markup of specifications and high-level integration of subsystems.

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Our method: develop physics based modelling to simulate energy consumption for a full year, incorporating the building fabric, weather conditions, occupancy scheduling and optimum system selection and sizing to satisfy Section J requirements. The output hourly energy load profiles can then be used to accurately generate cost benefit modelling of additional scenarios

For example, tariff options, alternative HVAC systems selection, and building facade options too produce benefit to cost ratio (BCR) as well as the net present value (NPV) at key periods, incorporating equipment life-cycle replacement costs to understand the total cost of ownership over the long term.