AI for People, Science
and Society

We develop next-generation artificial intelligence, machine learning and advanced automated
data-driven systems.

25 years of experience in AI and machine learning

Advanced AI and machine learning driven solutions, data analytics, predictive modeling, NLP, stream processing, visualization and intelligent automation capabilities across multiple industries.

- Project Flow -

Typical AI Project Life Cycle

01

Scoping

Problem understanding, project planning and what resources to employ to accomplish the project.

02

Data Collection

Data collection (from internal and external sources), data augmentation, preparation, annotation, wrangling, etc.

03

Model Training

Experiment, train, evaluate and tune different types of machine learning and AI models on collected data.

04

Deployment

Model deployment and maintenance in the production environment.

Project Flow -

Typical AI Project Life Cycle

01

Scoping

Problem understanding, project planning and what resources to employ to accomplish the project.

02

Data Collection

Data collection, preparation, cleaning, augmentation, preparation, annotation, wrangling, etc.

03

Model Training

Experiment, train, evaluate and tune different types of machine learning and AI models on collected data.

04

Deployment

Model deployment, web portal, API and maintenance in the production environment.

You don't need millions or TBs of data to start an AI project!

Beaucoup d'entreprises pensent que pour réussir leur transformation digitale et la mise en place de modèles d'intelligence artificielle, ils doivent d'abord construire un data lake, en y intégrant des millions voir des millards de données. Il faut au contraire inverser la logique et se poser la question dès le début des objectifs du système que nous souhaitons construire, et notamment des modèles d'IA que nous souhaitons mettre en place. Un projet IA n'est pas la dernière phase d'un projet data, il doit accompagner la construction des data lakes.

Fields of Expertise

AI & Machine Learning

We design, estimate, test and deploy innovative models, tools and frameworks, using advanced AI and machine learning techniques.

Analytics & DevOps

We help your teams with data analytics, and in the deployment of dedicated and secured APIs, real-time dashboards and web platforms. 

Data Storage

We build reliable and efficient data architectures using traditional DBMS, time series databases, data warehouses or data lakes.

Cloud or On-Premise

Infrastructures can be deployed on most cloud platforms (AWS, Azure, Google, OVH, Scaleway,…) or on-premise.

Security

Securing access to the data and models is always very important for our customers, no matter the project.

Research

We keep up to date with the literature, AI trending topics, deep learning frameworks, advanced text mining techniques and quantum computing.

Use Cases

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Marketing

In the 1990s, the Human Genome Project drastically changed the way we perceive life and researchers working on the Human Microbiome Project have identified more than 100 trillion microbes that may have either positive or negative effects on our health.

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Life Science

In the 1990s, the Human Genome Project drastically changed the way we perceive life and researchers working on the Human Microbiome Project have identified more than 100 trillion microbes that may have either positive or negative effects on our health.

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Anomaly Detection​

In the 1990s, the Human Genome Project drastically changed the way we perceive life and researchers working on the Human Microbiome Project have identified more than 100 trillion microbes that may have either positive or negative effects on our health.

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Data Labeling

In the 1990s, the Human Genome Project drastically changed the way we perceive life and researchers working on the Human Microbiome Project have identified more than 100 trillion microbes that may have either positive or negative effects on our health.

Use Case -

Marketing, branding and customer experience

Natural language processing (NLP), also known as text-mining or language analytics is an artificial intelligence technology that harness insights from large amounts of unstructured text, emails, social media conversations, online charts, survey responses and other forms of textual data.

It can be used in marketing, to extract customers motivations or intentions, from very large textual data sets (ie: customers feedback), and assist your teams on branding, content strategy, customer experience and lead generation. NLP can also help to produce and automate sentiment analysis, text classification, chatbots, text summarization, urgency detection, speech recognition, auto-correction, named entity recognition, etc.

Use Case -

Life Science

In the 1990s, the Human Genome Project drastically changed the way we perceive life and researchers working on the Human Microbiome Project have identified more than 100 trillion microbes that may have either positive or negative effects on our health.

By setting up sophisticated AI and machine learning tools and models, the enormous amount of unstructured data consisting of text, images, numerical data and sounds can be comprehended in a faster and more efficient manner.

Use Case -

Anomaly Detection

Anomaly detection is a data mining process used to determine types of anomalies found in data sets. Organizations need to keep track of anomalies and to study these anomalies to determine details about their occurrences.

Some organizations hire people to manually tag data and identify outliers, but this approach is limited by availability of people, time to label and budget, particularly when we are talking about TBs of data per day. For these cases, we need to label data and anomalies programmatically.

Automated anomaly is the next big thing for digital business and each business incident discovered could be an opportunity to save money, or to potentially create new business opportunities.

Use Case -

Data Labeling

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