Company Name:

Techbricks S.r.l.

Incubation Round:

Explore

Application Track:

Track 2

Proposed by:

IDEA75

Data Provider:

IDEA75

Challenge Name:

DATA DRIVEN TECHNOLOGY FOR EFFICIENCY IN ENERGY INTENSIVE INDUSTRIES

Product Description

Intermittent renewable sources cause imbalance and disruption that costs 20B€/year externalities only in the EU ultimately covered by final bill payers.

FlexyAI aims to develop an Artificial Intelligence (AI) machine learning solution, highly integrated with a Cyber Physical Systems (CPS)/Internet of Things (IoT) platform to introduce energy efficiency and optimize Demand Side Flexibility (DSF). The ‘smart’ energy demand response introduced by this solution will ultimately help the network rebalance.

Within the ‘Reach’ programme the Idea75 challenge “DATA DRIVEN TECHNOLOGY FOR EFFICIENCY IN ENERGY INTENSIVE INDUSTRIES” will be addressed to test the data science module of our solution – powered by a state-of-the-art Artificial Intelligence engine – and to process the CPS/IOT data from energy-intensive industrial plants.

The data science engine in this project is used for the following objectives:

  • An industry, energy consumption AI load forecast tool based on historical active power: current, energy, and voltage.
  • An industry AI load forecast tool based on historical active power: current, energy, and voltage.
  • An energy price forecasting tool to forecast the prices in the next 24-hour window.
  • A set of AI-based predictive models for commodity price forecasting implemented as Robo-Advisory for optimal consumption profile load, aimed at the use of the energy-intensive industry Energy Managers.

Usage of Standards for data interoperability:

At this moment the project does not comply with any particular data interoperability standard, but it follows general guidelines of DISC (Data Interoperability Standards Consortium) and European Interoperability Framework (EIF).

Reach Timeline

*Expose phase is open to all Experiment phase teams

Location:

Italy

Sector:

Energy | Manufacturing / Industry

Website:

https://www.techbricks.io/

Company maturity:

Pre-MVP and MVP

Investment level:

Angel

Funding raised:

< 100,000

Collaboration opportunity:

Product development, Legal / Regulatory, Service / Support, Product testing and revision, Investment

Company Description

TechBricks is a Tech Lab and Venture Studio specialized in the development of ‘deep-tech’ solutions based on exponential technologies, such as Artificial Intelligence, Internet of Things and Blockchain / DLTs.

TechBricks is particularly active in the FinTech and EnerTech innovation ecosystems (Corporate, SMEs and innovative Startups), also thanks to the previous experience of the founders: Manuele Monti – CEO, Founder & Chartered Innovation Manager – and Vladimir Ceperic – CTO, Co-founder & scientific researcher of MIT. On the advisory board, other long-time professionals in the field of IPR management, Legal and product development also oversee the ‘assembly line’ and investment of innovative solutions.

TechBricks develops and invests predominantly into B2B solutions covering real market needs, by offering a validated ‘Deep Tech’ innovation process that goes from Design Thinking to Minimum Viable Product rapid prototyping with the decentralized tools of a Venture Studio, a Tech Lab and a 10k+ professional and technology network.

Techbricks is also active in the corporate space, by offering continuous technological innovation and solutions that can easily integrate with corporate innovation processes.

Manuele Monti

CEO

Ph.D. in Mathematical Modelling and High-Performance Computing from the University of Leicester (UK).

Vladimir Ceperic

CTO

Double Ph.D. and an MBA, research at the University of Cambridge (UK) and Massachusetts Institute of Technology (US).

Milos Ciganovic

PM/Data Scientist

Ph.D. candidate in Quantitative modeling in Economics and Finance with specialization in real-time forecasting.

Kristijan Bartol

Software Engineer

Ph.D. candidate in Computer Sciences with specialization in Deep Learning and Artificial Intelligence