For any automobile company repairs and services are an important pillar of their business which impacts customer experience, brand perception, Net Promoter Score, Asset Lifetime Value, etc apart from being a major revenue generator. In a typical automobile service workshop, there are multiple services performed every day, with a majority of these service requests probably relate to the top 5 frequently reported issues, which in turn, consume the majority of the time of a service advisor in issue detection and diagnosis. If you look at the numbers, 1-in-8 machines in the heavy motors industry fail leading to thousands of dollars lost for every hour of downtime! Research has shown that 1-in-10 customers report mystery noise as the reason for servicing their machines. If we can find a way to automate "listening" itself, we would be able to more intelligently monitor our world and its machines day and night. We could predict the failure of engines, rail infrastructure, oil drills, and power plants in real-time notifying humans of the moment of an acoustical anomaly. Wouldn't that be a game-changer?
We believe “noise” is an important “big data stream” which can potentially give lots of insights and you can unlock massive value for your organization by using intelligent noise and voice tech. The question is, how can this noise data be leveraged in faster fault detection to reduce overall turnaround time for your service technicians thereby reducing the cost of service? If you look at any machine-based industry, like the automobile sector, the turnaround time of a service technician is an important parameter. Currently, issue detection is ad-hoc and involves manual intervention, and is often iterative guesswork which takes a significant time of the technician in detecting and diagnosing the issue, apart from impacting the customer experience. So, the core problem we want to solve is “How can we help a technician with a superior issue detection ability using noise analytics and reduce their turnaround time which can directly reduce the overall cost of servicing for the servicing company?” To solve this problem, we put together a team of subject matter experts, technicians, and business developers and started brainstorming an efficient way to analyze sound patterns in a machine. Thus was born the “Hark engine” a sound pattern analyzer technology powered by AI + ML + Sound analytics technology that can leverage sound as a data stream to transform variations in sound into value through our proprietary algorithms.
Our team behind the Novolytics platform brings domain, technical and business building experience. We strongly believe that we are first and foremost customer advocates where we see our customers as development partners and our singular focus is to provide value to them with deep empathy and build something they truly want, all while making the world a better place. We are on a mission to unlock value from sound. Excited? Well, come join the rocketship :)
By Haritash Team Novolytics
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