Learn About Our Values
Credibility
Computer intelligence and data science can be a complex and fast-changing industry that can be confusing and frequently misunderstood. That’s why our credibility and highly ethical reputation is a cornerstone of our identity.
Dedication
We are extremely dedicated to our clients. Your requirements, issues, and problems always come first, and only with a deep understanding of your business model can we solve those problems together.
Efficiency
We focus on scalability and efficiency as much as our clients do. From our documentation, project management tools, to our development process, efficiency is at the foundation of what we do.
Rigorous
We test, validate, and authenticate all results before sharing them with our clients, and we are upfront with clients when we come across issues that we may discover during any phase of their project, or in their data we analyze.
Collaborative
It’s in our nature to collaborate with our clients and internally within our Odyssy AI teams, the computer intelligence science and data science community as a whole. We frequent and present at AI-related conferences around the world and are happy to share best practices to improve the industry.
Meet our team

Jeff Foster
CEO
Co-Founder, Entrepreneur, Futurist, Professor
jeff@odyssysolutions.com

Dr. Scott Martin
AI Architect
Co-Founder, Author, Inventor, Professor
scott@odyssysolutions.com

James Casey
Product Development
Co-Founder, Producer, Author, Professor
james@odyssysolutions.com

Matthew Toloczko
Senior Business Advisor
Co-Founder, Entrepreneur, Analyst
matthew@odyssysolutions.com
Peruse Our Publications
Serious Games in Personalized Learning, 1st Edition
Scott M. Martin, James Casey, Stephanie Kane
- Publisher: Routledge; 1st edition (July 13, 2021)
- Language: English
- Paperback: 290 pages
- ISBN-10: 0367487500
- ISBN-13: 978-0367487508
Serious Games in Personalized Learning investigates game-based teaching and learning at a time when learning and training systems are increasingly integrating serious games, machine-learning artificial intelligence models, and adaptive technologies. Game-based education provides rare data for measuring, assessing, and evaluating not just a game’s effectiveness but the acquisition of information and knowledge that a student may gain through playing a learning game. This book synthesizes contemporary research, frameworks, and models centered on the design and delivery of serious games that truly personalize the learning experience. Scholars of educational technology, instructional design, human performance, and more will find a comprehensive guide to the history, practical implications, and data-collection potential inherent to these fast-evolving tools.
Artificial Intelligence, Mixed Reality, and the Redfinition of the Classroom
Scott M. Martin
- Publisher: Rowman & Littlefield Publishers (June 5, 2019)
- Language: English
- Paperback: 190 pages
- ISBN-10: 1475847270
- ISBN-13: 978-1475847277
Artificial Intelligence, Mixed Reality, and the Redefinition of the Classroom highlights new interpretations, understandings, and emerging technologies that radically remake traditional educational models, structures, and systems, and upend how faculty teach, and students learn. It explores new educational economic models that no longer depend on buildings to educate, and describes the growing applications of artificial intelligence, machine-learning algorithms in teaching and learning. This book also defines new approaches to personalize learning, including the use of artificial cognitive learning maps that mimic a learners’ biological learning map, that can also be applied to create a learner’s secure silhouette useful for truly personalized academic intervention recommendations. The emerging and maturing technological advances that allow these transformational opportunities may also upend the traditional educational institution: the familiar spaces, walls, and buildings, but also the delivery methods of knowledge, and the learner’s method of knowledge acquisition. Artificial Intelligence, Mixed Reality, and the Redefinition of the Classroom promises to inform the teacher, administrator, and board member to hopefully not just passively read about new and exciting innovations and tools available to improve the practice of education, but also to excite and inspire each to apply these innovations to better prepare our learners to succeed within this 4th Industrial Revolution.
Learning Engineering for Online Education: Theortical Contexts and Design-Based Examples
Chapter 8: Creating Personalized Learning Using Aggregated Data from Students’ Online Conversational Interactions in Customized Groups.
Scott M. Martin
- Publisher: Routledge; 1st edition (October 24,2018)
- Language: English
- Paperback: 232 pages
- ISBN-10: 081539442X
- ISBN-13: 978-0815394426
Learning Engineering for Online Education is a comprehensive overview of the emerging field of learning engineering, a form of educational optimization driven by analytics, design-based research, and fast-paced, large-scale experimentation. Chapters written by instructional design and distance learning innovators explore the theoretical context of learning engineering and provide design-based examples from top educational institutions. Concluding with an agenda for future research, this volume is essential for those interested in using data and high-quality outcome evidence to improve student engagement, instructional efficacy, and results in online and blended settings.
The State of Functional Games and Education (English to Mandarin)
Scott M. Martin, James Casey
Tencent IEG Social Value Insights Publishing. 2019 09 L0190475(6) 2-35.
Not Just for Entertainment Anymore- How mobile games can improve the human condition using the power of creativity and technology
Tencent Game’s Annual Conference. Tencent Publishing international, May 2019. March 21st, 2019, Beijing, China
Our Inventions
Deep academic learning intelligence and deep neural language network system and interfaces
SM Martin, JR Casey – US Patent App. 15/901,476, 2018
SM Martin, PH Martin, ML Trang, R Naidich… – US Patent App. 15/686,144, 2018
SM Martin, IIJR Casey, C Etesse, J Damici – US Patent App. 15/813,922, 2018
SM Martin, ML Trang – Learning Engineering for Online Education, 2018
SM Martin, PJ Chick, DS Te, BP Williams – US Patent 10,319,251, 2019
SM Martin – US Patent 9,691,291, 2017