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Pioneering Business
CEO & Founder Andrew Reiland combines his successful Software Engineering career, experience building neural networks, and proven growth in business to provide a one-of-a-kind, all-encompassing Data and AI lifecycle suite for businesses, government, and eventually consumers.
Reason's technology provides businesses and government industry-grade data lake security, availability, performance, and usability.
Our innovative approach to AI focuses only on our customer's data and workflows. Each AI model is completely unique, specifically trained and tailored specifically to each customer's needs, while keeping humans ethically centered at every point of the Data and AI lifecycles.
Our engineering-led company continues to see significant cost and time savings as we navigate with instant expert level foresight and insight. This efficiency has further enabled our scalability as we continue to rapidly and reasonably grow.
Kick GPTs to the curb.
Learn alongside your AI.
While the accessibility and quick extensibility of Generative Pre-Trained (GPT) models might suggest a convenient tool, relying on GPTs in sensitive domains and unsupervised environments is ill-advised and landing many in the news.
These generative models are pre-trained and cannot learn in realtime (i.e. GPT), hallucinate 30% of the time, and draw significant power/cost needs.
Machine Learning:
Safe and Ethical AI
Simply put - Machine Learning has better outcomes and can be fully audited. Beyond its fullly transparent nature: In machine learning there is 0% hallucinations, ML can learn in realtime, and sees 90% reduction in infrastructure and power needs leading to significant cost savings.
Sensitive domain support should require a deep, consistent, and representable understanding of context over extended and continued usage.
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