Design and development of a disruptive A.I. program for online public speaking coaching
Eleven has deep knowledge of the technologies specific to and revolving around artificial intelligence (AI) and data science.
With more than 11 years of experience in the field, the firm has experienced first-hand the arrival of all the cutting-edge technologies in machine learning and deployment, and IT development in general. With this history, eleven is now ideally positioned as an expert on cutting-edge technological subjects, with a wealth of experience in old systems and technologies, nowadays referred to as “legacy”.
On behalf of our customers, eleven has tested state-of-the-art technologies such as modular solutions development using container technology (such as Docker) and an all-API structure of the developed use cases. Far from siloing these innovative solutions, our firm makes sure that they are fully integrated with existing systems to ensure their long-term use and scalability.
This dual approach between legacy systems and new technologies allows our firm to support our clients in developing the advanced use cases that require them while favouring integration with existing solutions and systems and/or a smooth and gradual transition to these new technologies.
The strategy that we offer our clients for technological issues is to always begin with a business need and specific operating constraints. Using cloud technologies or ad hoc code deployment solutions in the cloud (such as Azure, AWS, GCP, serverless) allows for flexible, rapid and state-of-the-art deployment, if it serves an upstream business need. If necessary, we also know how to integrate into our clients’ proprietary environments and help them accelerate industrialisation within this framework.
By accompanying our clients on various issues of development and deployment of image learning use cases such as computer vision, generative design or natural language processing (NLP), eleven has built up an internal team of experts on these topics, mastering the reference development language in machine learning (Python, Scikit Learn, Tenserflow, Keras, Pytorch, BERT, etc.) and favouring agile methods and Continuous Integration & Continuous Deployment approaches.
This DevOps vision of the deployment of use cases allows eleven to respond in a relevant way to our clients’ needs without becoming too tied down to any particular conviction. Our experts are committed to continuing to explore new cutting-edge technologies until they are mastered and made available to our clients. This constant curiosity and willingness to learn is at the heart of eleven’s technological expertise.
Eleven is also very sensitive to making sure that algorithms are understood, which is why we have cultivated specific know-how in explaining AI models. On the one hand, this allows us to assure our clients that our algorithms do not contain any biases, whether ethical or of any other nature and, on the other hand, to produce algorithms that are more stable over time.
To help your teams understand and take ownership of the algorithms, we have developed an easy-to-use tool that allows you to explore and visualise the algorithms with each explanatory variable stressed to better understand its impact in the model predictions thanks to the most recent methods in the field (Shapley Value, Partial Dependency Plot, etc.).
Key Technological Enablers
The Blockchain is a technology for storing and transmitting information without a control body, based on the progressive and inviolable enrichment of a chain of blocks. This decentralized infrastructure offers promising opportunities for authentication and the establishment of a chain of trust, which are essential in the Internet age.
The Cloud brings together all the technologies that allow remote data storage and processing, often on shared solutions. The pooling of material costs and the development of platforms give any company access to flexible, high-performance, secure and cost-effective IT infrastructures and services.
Deep Learning uses machine learning in successive layers, allowing engineering features to be automated; it relies heavily on neural networks. New algorithms, access to large computing capabilities and the multiplication of the amount of usable data enabled radical progress in areas previously reserved for humans, such as vision and language.
Modular computing consists of interfacing and connecting interdependent, but autonomous functions. Thanks to open systems and the standardization of means of communication (APIs), the flexibility of information systems increases, and their evolution accelerates.
Machine Learning brings together all the technologies needed to automatically calibrate a model to make it more reliable. The improvement of computing power and the increase in the amount of usable data allows computers to automatically adjust their predictions and behaviors, and the development of more accurate and efficient predictive and decision-making algorithms.