A.I. models explainability
Support of a major French services operator in his reflexions on A.I. audit and models' explainability
Have you produced POCs, but are having trouble industrialising them? Do you have a lot of data, but are having trouble optimising it? Are your industrialisation cycles very long?
We combine experience on agile projects in state-of-the-art environments (DevOps, Cloud, Continuous Delivery, Serverless, etc.) and on concrete cases in large companies with very high security and compliance requirements as well as legacy systems.
We can help you inject flexibility and efficiency into your projects, taking into account your regulatory, technological and human constraints.
Our consultants know how to diagnose the right changes to industrialise your use cases at an optimal cost.
From data acquisition to data processing and exposure, eleven has the ability to leverage its internal skills and its ecosystem of technology partners to provide its customers with the solutions that meet their demands.
For data acquisition, eleven’s expertise ranges from its theoretical and empirical knowledge of connected objects and their day-to-day management on adapted low frequency networks, to data simulation or generation in the context of a generative design project via web scraping and collection by API.
Ensuring data quality and relevance to our clients’ needs is at the heart of eleven’s vision of extract, transform, load (ETL) strategies: When talking about an artificial intelligence (AI) or data science project, having biased or imperfect input data will very often result in a biased or imperfect solution.
Thanks to its range of experience in AI development and use case implementation projects, eleven has a comprehensive overview of the solutions and technologies on the market and a good mastery of the best technical practices associated with them.
When required by clients’ needs, eleven can draw on its in-house expertise in artificial intelligence on a variety of subjects and technologies such as image recognition, natural language processing, and generative design. To do this, we primarily use the Python programming language, although we have development capabilities in other languages such as R or C#.
eleven believes that the best performing solution is useless if it cannot be provided to the relevant end user in a meaningful way. As a result, exposure strategies are key to the firm’s industrialisation projects. From cloud deployments with Azure, AWS or GCP to on-premise deployments through hybrid strategies, eleven has gained experience in all the major ways of deploying solutions in a wide variety of industrialisation scenarios.