Paxafe is a company that aggregates critical data from the supply chain, enabling more intelligent shipping and cargo insurance. In this episode, I am with Ilya Preston, CEO, and co-founder of Paxafe and he talks about how the company is aiming to address global supply chain insurance issues, such as a lack of real-time visibility, theft, counterfeit product, damage, and product loss, all of which results in a loss of over $600 billion a year in the B2B and B2C shipping markets.
Ilya explains that there are many existing solutions for shipping data, however, they do not provide real-time data or contextualization of the data, leaving manufacturers at a loss for how to improve the supply chain. Paxafe on the other hand has created machine learning and analysis in order to best understand the current status of a shipment and to explain any issues that may have arisen during the shipment. In addition to explaining their competitive advantages, Ilya also shares the pivot they had from a previous startup to where they are now, growing their network, and the impact they’ve experienced as a participant of an accelerator program.
Topics in this episode
Pre-commercial beta testing
How Covid-19 has affected current fundraising
Creating machine learning and analysis
Reversed logistics
Benefits of participating in an accelerator program
Pivoting a startup to a new target industry
Partnering with insurance companies
Contact Info
Email: [email protected]
Website: https://www.paxafe.com/
LinkedIn: https://www.linkedin.com/company/paxafe/jobs/
Quote card: We provide contextual intelligence. We’re able to tell you precisely what happened with your package, and that enables us to partner with insurance companies.
Audiogram: 30:09 We’re trying to set the gold standard in asset tracking and asset IOT tracking. The market, as I mentioned, is very fragmented. There’s a lot of solutions out there, and there is no one kind of clear leader... so we’re trying to use machine learning and various analytics principles to set the standard in the accuracy, consistency, and reliability of the data to provide much more contextual insights so that companies aren’t just getting data, but are then getting data that can answer ‘So what?’.