Aatrizinventor Algorithm
for Systematic Innovation

The Aatrizinventor Algorithm applies a unique and disruptive methodology that systematically uses the Nature’s Language of Innovation, unveiled to discover innovative solutions in any area of human development.

We also refer to this methodology as Nature’s L.I., an acronym that sounds like Nature’s Light, because it illuminates innovation with the same logic that nature uses to create its own solutions.

This project is original and valuable, as it enables the resolution of operational problems and multivariable innovation challenges, starting from the identification of up to seven undesired effects and one need to satisfy that define the current state of an innovation challenge.

The methodology identifies in nature 24 undesired effects and 10 needs to satisfy, both described in universal terms.
These 10 needs define the innovation-evolution curve of both nature and human creations or actions.

Within Aatrizinventor, these undesired effects and needs to satisfy are referred to as innovation parameters, whose contradictions are solved using inventive principles—also described universally and organized in the Classical TRIZ Contradiction Matrix, which I recognize as:“The world's first hand-made application of conceptual artificial intelligence IA”

Those who adopt this methodology will discover disruptive solutions to their complex challenges with speed and focus.

Do you have an operational problem or an innovation challenge? Do you need a solution?
Aatrizinventor may be the key you've been searching for.

and more…

Hi, I'm José Roberto Espinoza, an engineer with 30 years of experience in the Chilean mining and electricity industries. My goal is to promote Nature's Language of Innovation and its algorithm, Aatrizinventor, an integrated methodology designed to meet people's true needs.

This language selectively combines concepts from TOC, TRIZ, and Morphological Analysis. It is based on a Hegelian principle verified by Aatrizinventor: “the current situation determines the future, and this will condition the next.”

The central abductive hypothesis: innovation is mathematizable; it is neither chaotic nor merely intuitive, but formalizable through replicable structures and patterns.

We have experimentally validated the methodology, showing its ability to predict innovation-evolution processes in nature and human history—including AI—and its projection toward future developments.