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Our Way of working

We excel at technology and applying strategic design, with one aim in mind:
creating relevant services and products.

In order to do that, we explore ways in which data forms the basis for new revenue streams

  • Machine Learning and data science exponentially increase the value of your data asset.
  • Users insights and validations are gathered with different qualitative and quantitative methods, adapted to capture key insights in every phase of the process.
  • We use data as the core for your new lines of revenue by merging data and machine learning output with your digital development methods.

Best Network
  • Quality
  • Smart responses to issues
  • Micro product management
Efficient Operations
  • Efficient operations
  • Predictive management of assets
  • Revolutionary pricing paradigms
  • Managing customers using smart knowledge
Closing the Loop
  • New services imply new knowledge
  • Acquire that new knowledge quickly
  • Be fast in monetizing the new knowledge
  • Be fast at consolidating and scaling success
Intimate Knowledge
  • Know who your customers are as human beings
  • Use all data
  • Enrich at a larger scale
Consumer Relationships as an Asset
  • Base your product ideas on your new asset
  • Discover then design
New Services
  • Monetize your relationships through new B2C and B2B services
  • Engage consumers at more touchpoints and interactions
  • Enter new areas and collect new data

We use data in a completely new way to build capabilities

Insights as Service

Combine augmented raw data with data science techniques and machine learning to deliver insights. For instance, expose location interpretation as a service to developers.

Profiling & Micro-Segmentation as Service

Turn your consumer data into precise knowledge of who they are as human beings in a format that is useful to them. Expose profiles for developers and integration services.

Micro-services Delivery

Ability for developers to access data services and build micro-services in agile and iterative manner.

Machine Learning as Service

Develop data applications based on a combination of your data and third-party data to deliver value-added products. Example: performance scores based on IOT data.