Solution | Qualia - Information that finds you

Information that finds you

Qualia is a global social intelligence tool that analyzes on-line conversations about your brand, products, competition and industry. Interact with Qualia in Slack, Messenger, Trello, e-mail and its web application.


Qualia proposes a new type of search. One that starts with the user keywords, retrieves relevant data, breaks down the business questions into signals that are computed from the data and makes sense of the signals in order to answer your initial questions. Qualia is a digital assistant that delivers to the user the most actionable data that is needed immediately and everywhere.


Is there a specific business question you need to answer from your data? Looking for direction and perspective in your market? Facing a business choice or dilemma? Got an idea? We'd love to help. It all starts with a contact.


Qualia provides, apart from its platform, a full suite of services across different aspects of business intelligence. We are a full service data science company. All our services are made by humans for humans, with the help of the machine.

Slack Integration

Qualia is an agent that analyzes millions of information sources around the world such as news, blogs and social media, and notifies you when it identifies an event of special importance that concerns your topics of interest. Connect Qualia to Slack and power your team collaboration and communication with smart alerts and instant insights.


The ways a crisis might evolve

A large brand finds itself having to recall a significant number of its products. They want to estimate how long this topic will attract attention and its magnitude, in order to understand the damage to the brand's public image and to successfully resolve the crisis.
We worked on the estimation of the possible outcomes of the event. We compared the current properties of the event with historical data. We calculated the number of mentions of the event every day (or hour) since the beginning of the crisis. And then we searched for past cases that exhibited similar patterns. From the current state of the system and the history of similar cases, we were able to propose different values of confidence about the possible outcome.
The crisis remained active for several days as predicted until it finally subsided. The actual magnitude of the event in the following days was close to the mean value of the distribution that we had used for estimation (technically within one standard deviation). The company preferred a quick, honest, full disclosure response to the crisis in order to inform its customers and to minimize the damage.