Chris Augeri was discussing the idea of visually simulating products around the time that Tracy Morgan was rear-ended by a tractor trailer. The driver of this trailer for Wal-Mart was largely at fault for the collision. This is when Chris began to look at using these products to help avoid crashes in the future, and to better train truck drivers. He began contacting the federal government and the Global Insurance Accelerator to gather interest in his company.
At first when Chris joined the accelerator and was working on recruiting early investors, Driver Spotter was a hardware company. Some of the best feedback that Chris got from investors was that the initial start-up costs of $25 million, was too much. In order to bring in investors, he had to find a way to decrease costs. Chris decided to pivot the company, after realizing that he could bring that cost way down if he changed into a software only company. In the last round of funding, they raised $750,000, as a result of redirecting their company.
Drive Spotter provides its customers with the biggest video search engine available. Drive Spotter creates the software needed for fleet managers to collect and review footage of their drivers, and to analyze their performance. The footage tracks interactions on the roadways, and filters the incoming video stream based on the analytics that the fleet manager is looking for. For example, if a particular driver is having problems with cans bursting while they are in transit, then a manager can use the software to understand driving behavior and then take corrective action to reduce this breakage, which ultimately helps to reduce costs. It has a dashboard that will tell the fleet manager more specifically that a driver made 15 hard stops, 5 of which was his fault, and 10 other stops were the fault of something happening outside of the driver's control. This footage can then be used for training purposes or as cash incentives for drivers. The software is a white glove analytics service, meaning that is is customizable to the fleet's individual needs.
The anticipated launch date for the public is in the fall of 2016. They are however, actively accepting fleets who are interested in being apart of their early adoptor programs. Currently, they are in the alpha and beta stages. He invisions his company in the future to build video search engine capability to better integrate vehicle autonomy. Merging and passing are unsolved problems with driverless cars, and his software would be able to help with this. Some autonomous vehicles can drive themselves completely, and others can only adjust speed or track lanes. As the capabilties of these driverless vehicles grow, Chris believes so will their role in trucking. Therefore, creating a need for his product to be developed into a roadmap. This is just one of the future applications that his software can have, and he has gained interest from other motion platforms.
The Global Insurance Accelerator has really helped him achieve his goals by giving him the opportunity to have talent, mentorship, and seed investments. He really likes vertically focused accelerators such as the Global Insurance Accelerator, and thinks that they provide more value. The access to top-tier experience in insurance, and ability to connect him to fleets that are interested in his product, has been extremely beneficial. He said that he was able to complete more in three months as apart of the accelerator than he would have in three years on his own.