Infer: Revolutionizing Data Analysis for Informed Decision-Making

Infer, a venture founded by analytics veterans Erik Mathiesen-Dreyfus and Ryan Garland, emerges as a solution born from their extensive experience in the field. Recognizing recurring challenges in analytics and data-driven decision-making, they embarked on a mission to rectify the issues they had frequently encountered.

Their journey commenced with a common observation: the prevalent misuse or absence of machine learning and data-driven insights in critical decision-making processes. Instead of diving into the complexity of sophisticated algorithms, Erik and Ryan chose a different path. They focused on optimizing the utilization of existing data, seeking to transform the way businesses internally analyze and leverage information. The ultimate goal was to enable more effective, efficient, repeatable, and dependable decision-making.

Erik Mathiesen-Dreyfus explains their motivation, stating, "This is a challenge that we are intimately familiar with and have encountered many times during our careers in data science and analytics – both from the leadership side, seeing bad decisions being made, as well as from the practitioner’s side, seeing bad analysis being done. Preventing this from continuing to happen was our motivation for starting Infer."

One glaring issue they identified was the lack of user-friendly, accessible tools for individuals with moderate data analysis and machine learning knowledge to perform advanced analyses. Their vision extended beyond creating a comprehensive end-to-end platform; instead, they aimed to build a bridge—a layer situated between the data layer (e.g., databases) and the data consumer layer, aptly named the "Inference Layer."

In preparation for their public launch, Erik and Ryan sought the expertise of Mast to craft a unique company identity. This identity was carefully tailored to cater to individual analysts, empowering them with the capabilities offered by Infer's innovative model.

Infer stands as a testament to the essence of data democratization, aiming to equip analysts with the tools and insights needed to navigate the complexities of the modern data landscape.