This article explores how the Data Science team at RIVIGO created a serverless store to retrieve features needed by different machine learning models.   Introduction   Tejas – A serverless feature store enables Rivigo data science team to store and retrieve features needed by machine learning models. Every machine learning lifecycle starts with creating a

The article gives a high-level overview of the architecture of the RIVIGO Goal App, an android application to empower sales teams with data-driven decision making. It also covers in more detail two of the application’s features, namely, daily organizer and travel reimbursement.

The continuum captures events occurring in succession, ranging from past to the present and even into the future. It understands and predicts the behaviour of an entity and maps it to intelligent events. In RIVIGO’s context, Vehicle Continuum is business intelligence over GPS data.

An overview of how we implemented MQTT to minimize data consumption and maximize battery life, thereby enabling effective relay of a continuous stream of valuable data from our pilots’ smartphones.

Relentless curiosity, imagination and never settling for anything but the best is the key to building great technology products for the future. The note talks about how lessons from history can help envision outstanding products for users today.