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AI for Automotive Prognostics Offers a Critical Advantage Through Preteckt’s Real-time Analytics Platform

Recognizing that over $700B is being spent annually on motor vehicle maintenance that also incurs $340B in wasted downtime, Preteckt, a  provider of Vehicle Prognostics as a Service ((VPaaS), leverages its proprietary real-time automotive data architecture to help connected and autonomous vehicle manufacturers and service providers. Through use of continuous integration of AI, Deep Learning and Machine Learning algorithms of automotive data, Preteckt provides real-time analytics that provides a 100x speed advantage over typical Big Data solutions.

Las Olas, a B2B venture capital firm focused on enterprise tech startups, recently invested in Preteckt to further the company’s VPaaS that addresses missed schedules and unnecessary maintenance that reduces downtime waste at time when transport solutions are becoming more complex.

"While the general state-of-the-art of AI is becoming quite good – say perhaps 80% accurate – 80% good isn't good enough for most commercial applications that rely on mission critical data accuracy," said Dean Hatton, LOVC Founding Partner in a press statemenet. "To improve accuracy, Human-in-the-Loop computing is required to supplement the machine learning process.  In the near term, the companies that figure out how to make HITL efficient will be winners in the AI space.  The Preteckt team has made great advances already and is laser-focused on perfecting the model for automotive prognostics.