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

User Intelligence from people’s 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 you can 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

Gracenote Advanced Discovery

Gracenote Advanced Discovery is powered by the Spideo Technology in order to provide tailored, relevant movie and TV suggestions that adapt in real-time to viewing tastes.

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

  • Cosmin Illes

    Marketing Manager

  • Vivien Phou

    Product Owner

  • Farah Kraled

    UX Researcher

  • Yohann Célérien

    Developer

  • Randa Zarkik

    VP Engineering

  • Némésis Srour

    Product Manager

  • Myrtille Vandemeulebrouck

    Software Architect
  • Némésis Srour

    Product Manager

  • Tom Borel

    Senior Developer

  • Viviane Jordan

    HR Manager
  • Giovanna Alvarez

    Content Analyst

  • Thibault D’Orso

    COO and Co-founder

  • Paul Noferi

    Senior Developer
  • Maguelonne Harang

    Content Analyst & Quality Assurance Editor

  • Jordan Godefroy

    VP Content & Data
  • Soumonos Mukherjee

    Data Scientist

  • Randa Zarkik

    VP Engineering

  • Clément Charasson

    Senior Developer

  • Aveek Mukherjee

    VP SaaS & Analytics

  • Edith Esclapes

    Office Manager

  • Cosmin Illes

    Marketing Manager

  • Paulo Henrique

    Head of Delivery and Operations

  • Yohann Célérien

    Developer

  • Myrtille Vandemeulebrouck

    Software Architect
  • Théo Paillusson

    Business Affairs

  • Bryant Lotaut

    DevSecOps

  • Chakib Khaldi

    Junior Developer

  • Gabriel Mandelbaum

    CEO and Co-founder

  • Vivien Phou

    Product Owner

  • François Martin

    Senior Content Analyst
  • Serge Nogues

    VP Enterprise Business

  • Juliette Ducru

    Content Analyst
  • Alexis Augusto

    Content Analyst

  • Jade Ventard

    Content Analyst

  • Hannah Taïeb

    Marketing Manager

  • Farah Kraled

    UX Researcher