Software

AI about AI

Roughly 90% of the world’s data was created in the past two years, and over 80% of that data is unstructured – videos, images, sounds, and text. Ayata’s patented software analyzes hybrid data – a combination of structured (numbers) and unstructured data – to predict what will happen, when, and why, and then prescribe how to take advantage of this predicted future without disrupting other priorities.
Our growing Intellectual Property portfolio consists of 35 US patents – 11 issued – covering some of our technology inventions.

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Artificial Intelligence (“AI”), simply put, is the science of predictions using all types of data (more, and more varied, the merrier). AI – though immensely useful and insightful – is not always actionable. Enter Operations Research (“OR”) and Metaheuristics – they are often referred to as the science of decision making. Ayata’s software is AI controlling and combining the science of predictions with the science of decision making.

Many of our inventions are in mixing and matching Machine Learning (including, Deep Learning), Computer Vision, Natural Language Processing, Speech Recognition, and Signal Processing with Operations Research and Metaheuristics. For predictions, our software used Machine/Deep Learning (for numbers, images, videos, sounds, and text), Computer Vision (for videos and images), Natural Language Processing (for text), Speech Recognition (for voice), and Signal Processing (for sounds other than human voice). For prescriptions, our software uses Operations Research and Metaheuristics.

Ayata’s technology architecture is inspired by the Central Nervous System (“CNS”) in the human body. The CNS orchestrates and controls most of the body’s activities even though such processes are rarely conscious. Ayata’s software does the same for complex, mission critical operations. We developed an AI platform to automatically control and combine AI disciplines with Operations Research and Metaheuristics.

Think of our software as “actionable AI” for industrial applications that can’t afford incorrect, untimely, or otherwise suboptimal decisions.

5 Pillars of Prescriptive Analytics

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Hybrid Data

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Integrated Predictions and Prescriptions

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Feedback and Recalibration

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Adaptive and Automated

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Algorithms about Algorithms

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