A Few Words

About Us



AI-Nova is a startup based on AI applied to i + R & D processes to help you create food.

Our customers will easily be able to develop products on our platform that are more sustainable, entirely new, plant-based, or nutritionally identical to their animal counterparts, without the need for long and expensive product development periods.


Pamela Rocha CEO of Ainova Food. Food Engineer of the University of Chile, PgD Food Marketing of the University of Chile and PgD Project Administration of the Pontifical Catholic University of Chile. 

She has extensive experience in i+R&D in large food companies in Chile like Soprole and Ariztía, and also in SME like Slimbar and Home Baker, her own business before Omaigut. 

She also has experience in marketing, QA, coordination and project management.

Her other skills include using Adobe design programs and web page development.

Always concerned about the environment and health. She belongs to the Inca people, which has influenced her tastes for taking advantage of local and Latin American ingredients. 

Katherine Shepherd COO & Chief Chef of Ainova Food. Oral surgeon at Finis Terrae University in Chile, with Biochemistry courses and experience in Biological Sciences. 

She studied to become a Chef at Ecole, a French culinary school in Chile. After that, she specialized in Spain.

She is in charge of general operations in Omaigut and the making of recipes for our system.

She has a creative and shrewd-minded and is also the founder of her own entrepreneurship, La Pastora Dulcería.

Her other skills include small business accounting and digital marketing.

Alvaro Arriagada CTO of Ainova Food. We call him the man of numbers, his specialization in recent years has been in data science development in the financial area.

International Trade Engineer, MSc. Industrial Engineer

Pg.D Data Science, Pg.D Bussiness Intelligence & Data Mining, Pg.D Project Management, Pg.D Innovation Management,  20+ Exp

Specializations in SQL, Python, R, Descriptive and inferential statistics, Machine learning, Econometrics and Descriptive and predictive model.


  • Predictive models of customer churn
  • Predictive model of fraud detection by identity theft
  • Predictive model of purchase propensity
  • Clustering clients for management
  • Among others.
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