inqiri started with a question: "Why hasn’t widespread computing and massive amounts of information improved decision-making?"

We have more computing power and data than at any time in the history of humanity, but the flood of technology and information hasn’t significantly improved our ability to make better informed, more rational decisions. We believe it is a solvable problem, and one that just needs a unique approach. If we are right, with your help, will change the world.

Even the greatest idea will not amount to anything if you don’t convert concepts into action. In 2012, we started the project that would become inqiri. From our offices in Reno, NV, we secured seed funding, formed a team of experts, and began building the Decision Optimization Engine™ and inqiri, putting our concepts, designs and plans into action.

We are working to create a solution at the intersection of state-of-the-art cognitive science and information technology. A solution that combines the insights of collective intelligence with the power of synthetic intelligence to overcome cognitive bias, improve rational decision-making, and maybe even change the world.


How it Works

The inqiri process is a simple, but powerful combination of collective intelligence and synthetic intelligence designed to enhance your decisions.

inqiri combines input from multiple participants who create an inqiri, select criteria for the inqiri, and propose options. They provide ratings with an easy to use slider system. The inqiri system produces an analysis of the options and the detailed analytics to support the decision-making process.

inqiri and Greek Ladders have partnered to collect data from job candidates and employers to better understand the needs of candidates and employers. The data will be used to reshape and enhance the connectivity between candidates and employers by recognizing the issues, needs, and opportunities facing both parties. The result will be stronger connections, more efficient connectivity, and successful workplace integration.

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