Manchester Prize Round 1

Manchester Prize Round 1: Energy, Environment & Infrastructure

The Manchester Prize, an initiative of the UK Department for Science, Innovation and Technology, will award £1 million every year to a team of innovators with the most cutting-edge AI solution for public good.

The first Manchester Prize runs from November 2023 to March 2025, and will award £2 million in two phases.

In its first year, the Manchester Prize awarded innovators with the most innovative and impactful AI solution which demonstrates social benefit by overcoming challenges in the fields of energy, environment and infrastructure

10 of the most promising solutions were each awarded £100,000 grants and additional non-financial support in May 2024. The finalists are currently developing their prototypes capable of winning the £1 million grand prize in spring 2025.

One finalist will win the £1 million grand prize in early 2025.

Find out more about Round One of the Manchester Prize

The finalists are:

Aiolus team

Aiolus leverages AI and creates digital twins to enhance wind farm operations and predict maintenance needs, boosting energy capacity, lowering the average cost of electricity for people and accelerating the UK towards its Net Zero target.

AssetScan team

AssetScan by CC Informatics is an AI system which aims to identify defects in buildings and infrastructure assets from large photographic datasets, such as those collected by drones, using an image-to-image processing technique.

CRE.AI_.TIVE_ team

With the impacts of climate change threatening global food security, Phytoform Labs uses its proprietary CRE.AI.TIVE platform to discover drought tolerant, disease resistant and yield boosting traits for a diverse variety of crops. CRE.AI.TIVE is a ‘foundational genomics model’, that learns about the genome of plants and accelerates the search for useful mutations to increase the resilience of crops.

EvoPhase-10 team

EvoPhase Explore is an innovative AI-driven solution designed to optimise the design and operation of industrial equipment. It leverages evolutionary algorithms to reduce energy consumption, minimise waste, and enhance overall efficiency in manufacturing processes. 

gAIn-Water-1 team

gAIn Water leverages advanced predictive AI technologies to integrate real-time sensor data from the UK’s water network with environmental and demographic inputs, including weather, soil conditions, pipe integrity, and population trends. The system dynamically optimises water flow and maintenance schedules to significantly reduce leaks and lower energy consumption, offering measurable benefits to water utilities, governing bodies, and communities across the UK. 

greyparrot-1 team

The Greyparrot AI waste analytics system “sees” and tracks every piece of waste entering a sorting or recycling plant via monitoring units positioned over conveyor belts. It aims to create a complete digital map of the world’s waste flows to track what happens when waste is discarded and support the value chain to improve packaging design, policy-making and recycling rates.

Polaron-1 team

Polaron uses AI algorithms to rapidly analyse potential material designs and identify the best manufacturing processes to maximise performance. Applied to battery electrodes, Polaron’s technology can yield a 10% increase in power, while reducing the cost by more than 50%, revolutionising battery manufacturing and unlocking the next generation of materials. 

Quartz-Solar team

Quartz Solar AI Nowcasting uses AI to forecast cloud formation hours ahead of time, allowing solar energy to be more efficiently integrated into the electricity grid through better prediction of periods of intermittent supply. By leveraging satellite imagery and live solar generation data, it helps better manage solar energy resources and balance a renewables-heavy grid.

Sapphire team

Sapphire will be an AI tool to help reduce water pollution from storm overflows, agriculture, and urban spaces. It aims to enable water companies to better understand the impact of storm overflows and manage flows more effectively, ultimately resulting in better water quality across the nation.

TraffEase-3 team

TraffEase AI integrates transport and urban mobility data to provide predictive traffic analytics that can inform decision making for efficient and green mobility. The platform supports intuitive natural language queries, making it accessible for non-experts. This empowers city authorities to effectively manage transport to enhance the journey experience for the public. 

Manchester Prize has brought more credibility to our work, particularly in advancing our talks and building our industry connections. This has been particularly useful in establishing our ongoing partnership with Network Rail. Furthermore, the prize has allowed us to be more visible with probably the hardest markets to get into in the UK, so even if we don’t win the 1 million pound grand prize, we are in a much stronger place to go forward and go further for investment.

Key dates

Manchester Prize opens for entries
7 December 2023
Entries to the Manchester Prize close
1 February 2024
10 finalists announced
21 May 2024
Final submissions due
January 2025
Grand Prize winner announced
March 2025
  • 2023
  • 2024
  • 2024
  • 2025
  • 2025

Interested in meeting the teams or joining the Manchester Prize Demo Day in March 2025? Email the Manchester Prize team at: [email protected]

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