Since 2017, we've focused on fixing the challenges of Artificial Intelligence (AI). We founded Salynt on the principle that you could generalize any issue, and the software we produced could handle those issues by accelerating teams. But, unfortunately, what makes AI difficult is that the traditional science/engineering approach of "divide and conquer" doesn't work: there are too many parts, and they're too tightly bound together.

 

Our team provides a different approach.
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Divide and Conquer is not the approach in engineering. On the contrary, engineers build integrated systems for production-level code. It is the opposite approach of data science, which relies heavily on analysis. The problem with AI is the lack of engineers.

 

Our solution integrates analytics and engineering principles into production with ease.