Shell.ai Futures Pitch

Shell.ai Futures Pitch 2024

A competition that aims to bring together the start-up ecosystem and Shell to accelerate and explore opportunities for joint learning and collaboration on some of the world's toughest energy challenges.

Competition format

At the Shell.ai Futures Pitch 2024 Competition, start-ups can pitch their innovative solutions for one of the two problem statement in the area of future energy systems.

The start-ups can demonstrate how their solutions can address the selected problem statement. Following an initial submission round, a virtual jury will shortlist the top start-ups for the finale. These top start-ups then pitch their solutions live to the jury members at the Changemakers of Tomorrow event.

Eligibility

The competition is open to all registered start-ups (minimum 2 staff members).

Startups can be in different TRL levels: -

  • 2-5 stage or have received only pre-seed or seed funding; or
  • 6-9 stage with early revenues, market validation by pilot(s), series A funding (or higher).​

Rewards

The cash prizes that will be awarded are:

  • USD 5000 for the first prize winner
  • USD 3000 for the second prize winner

The winning start-ups may be awarded a collaboration opportunity with Shell to develop their proof of concept.

Choose your problem statement:

  • Site procedures management for Oil and Gas industry
    In the oil and gas industry, effective site procedures management is essential for ensuring safety, regulatory compliance, and operational efficiency. This involves the systematic development, implementation, and continuous improvement of standardized procedures for all site activities. Key components include risk assessment, emergency response planning, environmental protection measures, and adherence to industry regulations. By optimizing these procedures, companies can minimize risks, enhance productivity, and maintain a safe working environment for all personnel.
  • Virtual Assistant for Field Development Planning in Oil and Gas industry
    A digital advisor to support engineers and planners that streamlines and optimizes the field development planning process by providing data-driven insights, automating routine tasks, and supporting decision-making. It can assist with tasks such as data analysis, project scheduling, resource allocation, and risk assessment, ultimately enhancing efficiency and decision-making processes in field development projects.

Shell.ai Futures Pitch 2024 Winners

Winner: Squint.ai

Squint.ai

Squint is a production wisdom platform that collects specialized knowledge, implements standard procedures, and provides comprehensive analysis, all within one interface.

Challenge - Site procedures management for Oil and Gas industry

Runner-up: Energective.com

Energective.com

Energective leverages advanced analytics and AI to extract valuable insights and propels digital workflows, equipping oil and gas operators to take full advantage of cutting-edge technologies.

Challenge - Virtual Assistant for Field Development Planning in Oil and Gas industry

Shell.ai Futures Pitch 2023 Winners

Winner: Uptime.ai

Uptime.ai

UptimeAI is an artificial intelligence-based operation excellence platform that combines predictive maintenance with explainable failure modes/recommendations and self-learning workflows to maximize uptime, process efficiency, and drive sustainability. Shell, Petroleum Development Oman, Bharat Petroleum, BASF, and the world's top refiners have unlocked ROI within 90 days.

Challenge: Predictive analysis of oil and gas production facilities (plants)

1st Runner-up: V2T.io

V2T.io

V2T uses a combination of Digital Twin, AI and Simulation (DAS) technologies to transform business operations by integrating high-fidelity visuals, spatial physics, behaviors, and effervescent data without fixed rules, enabling accurate predictions and decision support.

Challenge: Transport fleet scheduling for multi-product, inventory-based supply chain

2nd Runner-up: Gentian.io

Gentian.io

Gentian is a faster and more efficient way to monitor nature. They combine high resolution remote-sensing images with computer vision, decades of ecological expertise, and trained AI algorithms, to recognize and separate different biodiversity habitat types remotely and autonomously. Independently verified as over 97% accurate versus manual surveys, this approach greatly improves the speed, cost and accessibility for measuring, monitoring and predicting ecology. This is especially important for fast-growing new and regulated markets where biodiversity carries high value.

Challenge: Biodiversity assessment toolkit