We support organisations in the design and implementation of ethical and sovereign AI systems.
By combining cutting-edge data science expertise with a focus on system performance, impact, and resource efficiency, we enable the deployment of robust and resilient AI systems.
Our approach focuses on anticipating resource consumption and finding the best trade-offs to achieve optimal performance levels.
This environmental impact analysis is conducted using evaluations based on proven scientific methodologies.
The objective is to enable organisations to control the return on investment and the sustainability of the systems developed.
The rise of generative AI (GenAI) has demonstrated remarkable versatility and unparalleled power in accomplishing a wide range of tasks. However, this capability demands increasing computational resources, heavily reliant on electricity, water, and rare metals, thereby contributing to a growing ecological footprint.
Our eco-responsible design methodology ensures that AI systems incorporate principles of frugality, optimising resource use and minimising environmental impact.
Large generative models like LLMs deliver impressive results, but meeting SLA requirements demands advanced techniques to ensure reliability and performance. The use of proprietary models also raises risks related to data compliance, security, and privacy.
Through our support combining strategic consulting, skills transfer, and responsible implementation, we aim to ensure a robust and sustainable adoption of AI.
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