LocoNav, Locus Team up to Automate Supply Chains

Locus, LocoNav, supply chain

Fleet technology company LocoNav has launched a partnership with Locus to provide automation for supply chain operations, the companies announced Wednesday (April 6).

Based in India, Locus uses machine learning, deep tech and proprietary algorithms to deal with complicated last-mile issues. According to the press release, these issues can range from inefficiencies like traffic delays, accidents or thefts to excessive fuel consumption due to idling or speeding — all of which can negatively impact a delivery business.

Meanwhile, LocoNav, also based in India, offers numerous fleet management solutions, including track and trace, fuel monitoring, onboard diagnostics, rich analytics and customized reports, which the company said can help Locus optimize multiple vehicle operations.

In addition, the companies say end-to-end visibility will give Locus customers the chance to improve operational efficiency, reduce costs and streamline the customer experience.

“Collaboration is the first step to growth and we couldn’t have asked for a better partner than Locus to solve for complex supply chain challenges,” said LocoNav co-founders Shridhar Gupta and Vidit Jain. “This partnership will help us unlock great value for the entire ecosystem, supporting us in our mission to democratize fleet tech.”

LocoNav also raised $37 million last year in a Series B round, which saw participation from Sequoia Capital India, Anthemis Group and Quiet Capital.

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PYMNTS explored some of the last-mile challenges facing delivery companies last month in an interview with Andrew Travis, chief operating officer at Onfleet. While many companies still plot routes with Google maps — or good old-fashioned paper and pencils — others have embraced route optimization platforms that use modern geospatial data and machine learning.

See also: Last Mile Delivery Providers Employ Technology to Manage Fuel Costs

“A proper optimization engine can consider more constraints more quickly and more accurately than any human can and really speed up that process as well,” Travis said. “What takes a route optimization engine 30 minutes might take a team of people a year to actually pull off.”