Our services


Helping clients take ownership of methodologies or technologies through advice and direct interventions. It includes data evaluation mandates and feasibility assessments of AI projects.

Experimental development

When there are technological or scientific uncertainties related to a client project, CRIM is called upon to exploit applied research results and technologies and to prepare an experimental development plan to de-risk the project. Work is carried out with a view to a technological breakthrough.

Applied research

Upstream research on more significant issues that may result in scientific publications. Work is aimed at advancing scientific knowledge with a view to a precise practical application.

Why choose CRIM?

CRIM researchers and experts use the Technology Readiness Level (TRL) scale to determine the stage of your initiative. They can assist you in the various phases of innovation. Thanks to their scientific knowledge and practical know-how, they increase your innovation project’s chance of success.

CRIM can assist you in the short, medium or long term, from stage 2 to stage 6. Whether through a support service, experimental development or applied research, knowledge transfer is ensured in the methodology to allow our customers to be autonomous through the next steps. 

CRIM scale RTL

By choosing CRIM as your innovation partner, you ensure that you have access to professionals who perfectly combine the latest scientific and technological knowledge and their concrete applications to help you create value.

Mathieu Barreau
Director, Business, Communications and Partnerships

Examples of interventions carried out

Data preparation

  • Data consistency
  • Machine learning pipelines
  • Unstructured data processing
  • Time-series modeling
  • Prediction methods
  • Recommendation systems
  • Visualisation

Audio and speech

  • Signal processing
  • Channel targeting
  • Speaker recognition
  • Language recognition
  • Speech recognition
  • Analysis of emotions
  • Copy detection
  • Fake detection

Vision and image

  • Object segmentation
  • Instance recognition
  • Automated video indexing
  • Industrial inspection
  • Fake detection
  • Image description
  • Video description

Automatic natural language processing

  • Finding and extracting information
  • Specific entity recognition
  • Textual classification
  • Analysis of sentiments
  • Chatbots
  • Representation of knowledge
  • Ontology


  • Observation and remote control
  • Forecasts and predictions
  • Climate projections
  • Biodiversity monitoring


  • Internet of things
  • Attribution of attacks
  • Analysis of user behavior
  • Voice biometrics
  • Facial biometrics
  • Electronic contact validation

Formal methods

  • Systems modeling
  • Model inference
  • Tests and verification

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