effectivRAI's Three Key Technologies

effectivRAI simulations provide the only objective, validated instrument for efficiently identifying how individuals and groups apply good judgment. Teams should see the whole picture and yet zero in on a specific problem others haven’t been able to diagnose. Almost intuitively, they can make the right decision, at the right level, with the right people. Our approach is a quantum leap beyond testing for personality, behavior, Intelligence Quotient, or Emotional Intelligence.

Participants encounter twelve simple activities which are timed—adding real world urgency. Dynamic APIs analyze and track each user’s preferred ways of answering, and the fluency of response. 

There are no “good” or “bad” results. Our purpose is to leverage synergies, fill any gaps, and boost the effectiveness of those specialized cross functional “A Teams” which are accountable for effective RAI adoption.

We can use agents—which are autonomous software tools that interact intelligently

with their environment—for discrete, valuable tasks. One is to help companies embed RAI practices into their alignment of Leaders, Operations, and Strategy. The result is optimum Execution. This is a powerful way to help orchestrate the enterprise for effective RAI adoption and use. 

Yet agents have risks. It is a delicate balance, which effectivRAI helps to strike in tandem with the company’s experts. Adequate controls and governance are again prioritized, as are external reviews and monitoring.

Throughout the journey of putting effective RAI to use, we are ensuring that humans oversee key decisions. We check that clear principles exist, examine how they are enforced, and we scrutinize those circumstances which need to keep personnel out of the loop.

Our proprietary technology fuses human/machine interaction naturally into “hybrid intelligence.” It is used when accuracy is vital. Subject Matter Experts within a corporate workflow who refine data produced with AI/ML can do so with unprecedented speed and precision—and to a level of exactness that can’t be achieved through automated algorithms alone.

One result is that enterprises get maximum value for their data. They move further ahead of competitors by having reliable, legal, and proprietary data at scale—and being able to profit from it quickly.  

The platform is often the missing piece to a corporate technology stack. It fills the gap between AI-based data processing and the ability of SMEs to be in control of their content. With this technology, we’re innovating on multiple fronts.  It can be used without a pre-existing data model. It treats metadata as data. And it works with any language, not just English.