Humanized Recommendations. Built to Scale.

  • Our engineers develop the algorithms.
  • Our data crafters capture moods and emotions into semantic data.
  • We bring the right content, to the right person at the right time.

Personalized Discovery based on  Trust, Transparency, and Controllability.

Humanized Recommendations. Built to Scale.

  • Our engineers develop the algorithms.
  • Our data crafters capture moods and emotions into semantic data.
  • We bring the right content, to the right person at the right time.

Personalized Discovery based on  Trust, Transparency, and Controllability.

0
unique Semantic Fingerprints
10 Million
Users per month
0 Billion
Recommendations per month

Empower your Teams

CONTENT

Build knowledge on content and users to serve relevant & dynamic curation

PRODUCT

Intuitive, personalized and dialogue-driven experiences

MARKETING

Business Intelligence through users’ tastes and interests

ENGINEERING

Integrate recommendation seamlessly with the most simple API

User Semantic Fingerprint™

  • Powerful Data Visualization
  • Meaningful Recommendations
  • Transparent Results
  • Fully Controllable

How can you explain to your customers why they get recommendations without being creepy? 

Our User Semantic Fingerprint™ allows you to gain trust from your customers. They can clearly visualize every interaction they have with your platform. They can understand the consequences of each of their actions.

Customer Stories

SVOD platforms need recommender systems

The collaboration with Spideo began in 2016, with an aligned vision. The business model was made on the basis of the growth of the ADN platform, which perfectly scaled with their needs throughout the years.

Explanations matter as much as Recommendations

With MyCanal, Canal+ engages customers and builds user loyalty by bringing together all video platforms into one coherent premium experience.

Recommendation is the new Customer Relationship

Televisa launches Blim in order to retain subscribers with exclusive Spanish speaking content on its own On-Demand platform.

sky gray

Avoiding seasonal churn with a 2-week integration

SVOD and OTT services experience the risk of churn due to seasonality. How can accurate and relevant recommendations help them in delivering the right content and avoid churn in such a context?

Seamless User Experience

Full Personalization

  • Higher Engagement
  • Accurate Recommendations
  • User Friendly UI
  • Humanized Interactions

Create business rules to improve performance.

The Faces Behind Recommendations

The Faces Behind Recommendations

  • François Martin

    Senior Content Analyst

  • Paul Noferi

    Tech Lead
  • Jordan Godefroy

    VP Content & Data
  • Chakib Khaldi

    Junior Developer

  • Jérôme Benac

    Customer Success Manager

  • Yohann Célérien

    Developer

  • Clément Charasson

    Senior Developer

  • Jean Cayre

    Content Analyst

  • Cécile Grabit

    Product Owner

  • Alexis Augusto

    Content Analyst

  • Gabriel Mandelbaum

    CEO and Co-founder

  • Amanda Batista

    Content Analyst

  • Paulo Henrique

    Head of Delivery and Operations

  • Viviane Jordan

    HR Manager
  • Youssef Kitane

    Analytics Engineer

  • Yohann Célérien

    Developer

  • Paul Renet

    Product Owner

  • Clément Charasson

    Senior Developer

  • Soumonos Mukherjee

    Head of Data Science & Analytics

  • Némésis Srour

    VP Product

  • Jordan Godefroy

    VP Content & Data
  • Cosmin Illes

    Head of Product Marketing

  • Thierry Tomegah

    Junior DevOps

  • Julien Deflesselle

    Developer

  • Maguelonne Harang

    Quality Assurance Editor

  • Jérôme Benac

    Customer Success Manager

  • Bryant Lotaut

    DevSecOps

  • Edith Esclapes

    Office Manager
  • Paul Noferi

    Tech Lead
  • Serge Nogues

    VP API Product

  • Hannah Taïeb

    Head of Business Development

  • Farah Kraled

    Product Designer

  • Myrtille Vandemeulebrouck

    Software Architect

  • Jade Ventard

    Content Analyst

  • Théo Paillusson

    Business Affairs

  • François Martin

    Senior Content Analyst

  • Tom Borel

    Senior Developer

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