Now more than ever, global citizens need the ability to navigate safely through an ever more complex and obscure cyber landscape. At Infinite IQ, our specialized search engine maps this landscape by finding, sourcing, and cataloguing massive amounts of data into reliable, user-driven systems with an emphasis on complete transparency. We don’t just find the needle in the haystack; we illuminate every piece of straw along the way.

Powered by machine learning, original genetic algorithms, and our unique data organizing/storage capability, our tools leverage a new way to combine human and computer capabilities. In the labyrinth of modern data complexity, Infinite IQ’s products can act as the foundational enterprise components to harness the knowledge of your people and enhance your competitive advantage.

Technologists once theorized that complex insights could be stored, and therefore gleaned, within relational databases. But these databases proved insufficient to the task when they were unable to efficiently execute complex equations. With this knowledge in mind, we chose instead to work with the network database management structure, which was first created by Charles Bachman in 1954.

Bachman’s database is robust enough to hold large, complex networked relationships and organize the knowledge manufacturing process that results from large-scale collaborations between people. But we wanted to incorporate more clear and direct participation and interaction for users. So we extended the network database design to simulate simultaneous similar events and, thereby, build a network of combined reality from which to derive salient patterns.

Our data model is literally the logical combination of Points-of-Views. Our SimPOV engine creates informational Point-of-View databases, which gives teams and organizations ways to evaluate perspectives.

SimPOV is the engine that allows the points-of-view to interact in real-time and predict future behavior. By taking in the news or any platform’s information, SimPOV draws our user’s attention to perspectives that are attracting people and the ways the perspective is likely to influence their behavior in the future. The trends can inform product development, sales distribution, or courses of action.

As the Points-of-View are composed by users in the action/reaction cycle with SimPOV, they are, by definition, transparent. Validation is achieved by continuously determining confidence in the algorithm’s and data’s bias profile. All data and algorithms are biased, with SimPOV the bias is transparent.