• We analyze financial markets.
  • We perform credit scoring operations.
  • Analyze behavioral patterns in our target markets.
  • We create predictive public health insights.
  • We observe political movements and correlate with financial data.
  • Health data
  • We identify market trends before they happen.

Because there are unlimited combinations of learning setups and vector cloud creation, we see predictive results from theoretical combinations of data.

Imagine posing a question with 100 trillion “if’s,” “when’s” and “but’s,” but then being able to see the path towards the one result that you want to arrive at. We call these theoretical predictive vectors, QSpikes.
To get these insights, QSpike relies on a number of different types of analysis, as shown in the graphic: