Way back in 2017 we created a company that was ‘AI-first’ in supply chain. We felt like we’d caught the first wave. A new way of tackling an age-old problem with tools - machine learning - still in their infancy. Machine learning (often interchangeable with ‘AI’) back then was for cool stuff like self-driving cars, but it wasn’t really applied to traditional industries like supply chain management or freight forwarding.
Even in the rare cases that AI and supply chain were mentioned in the same breath, the value of AI was always discussed from a top-down point of view, like modeling complex supply chains using big data, instead of looking at operations from the ground-up. One of the main reasons for this oversight was simple: companies with operational know-how didn’t have machine learning engineers, and vice versa. Put another way, the venn diagram of companies with access to both profiles looked like a figure of eight. So we saw an opportunity.
From the very start we worked closely with a few freight forwarders - partners - to use AI to solve the most difficult problems they faced in operations. This meant years (five and counting) of technical iteration while we built the many layers required, from our core data pipelines to our human-in-the-loop and operator experience platform, to management dashboards and more. It also meant years refining our understanding of what the industry needed.
We realized pretty early on that the future of freight forwarding is human, we just needed to build the best technology to support them, and so our goal was to create a new platform based on a new framework; one that combined operational best practices across our customer base with automation front and center, not just as an afterthought.
Today, we’re getting closer to realizing this ambition. We’ve built out an operations automation framework, and built it to scale. We have 50+ paying customers using our automation platform across the shipment lifecycle, and across globally distributed teams.
Every year we process tens of millions of documents and even more emails, helping thousands of users worldwide work more effectively, in turn helping our customers to make real savings of millions of dollars. At a time when our forwarding customers are being squeezed from both sides: dropping revenue as rates and volumes soften post-covid, and higher costs as a result of rising wage inflation, operations automation has never been so important.
And this brings us to our rebrand.
As we continue to evolve, the scales are tipping evermore towards the value-add that we can bring on top of our automation platform. For example, automating accounts payable unlocks the ability to help our forwarders pay their service providers directly within our platform. Understanding line-items from a packing list allows us to understand SKU-level visibility and communicate that to end-customers. There are many more examples.
We’re moving to a business model that, while built on operations automation, uses that foundation to add further value to the people that work in our industry. It seems therefore appropriate that our name, vector.ai, a machine learning term which we chose back in November 2017 and reflected a world where we were AI-first, should change to a name that reflects our commitment to our industry. I’m therefore pleased to announce our new brand and name: ‘Raft’.
We’re excited to share what we’ve been up to. Find out more at raft.ai.
James
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