Why we invested in Arvist: Transforming Warehouse Operations with Applied AI
Our investment in Arvist broke every mould when it comes to attending industry conferences.
Up until that moment (at least for me), it had been conventional wisdom that such events were meant for having great conversations, keeping up with market developments, and taking in the buzz that filled that beautiful April day in San Francisco.
Our meeting with Nilay Parikh, Arvist’s founder and CEO, had less than a 5% chance of happening. It was the first of nearly a dozen 1:1 meetings at 8:30 am, and we had been double-booked for another call. Little did we know, our next investment was about to take shape.
Nilay presented us with the business case based on his own professional history in logistics. In global shipments, the vast majority of value creation in a warehouse occurs at the dock door - where goods arrive, depart, and are inspected. Yet, much of the work in identification and inspection is still handled manually, where minor errors - from mislabeling to missed or incorrect scans - quietly cost operators 5-10% of annual revenue. Traditional solutions force warehouses to choose between costly automation projects, absorbing inefficiencies, or adding labour in a constrained market.
Nilay approached this problem head-on with disciplined focus. Instead of " solving everything” at once, he concentrated on this critical chokepoint in the supply chain. By addressing the area where the most value can be captured, Arvist delivers solutions that are immediately actionable and highly scalable. We found this kind of disciplined product strategy to be refreshing and highly effective.
Together with Bazyl Horsey and Alec Groff, Nilay built a plug-and-play computer vision platform that brings intelligence directly to the areas where it matters most. Point a camera at the dock, run it for a shift, and you immediately see measurable improvements. The product is a modular, self-install quality control solution that transforms existing cameras, WMS systems, and tablets into automated inspection points. Warehouses can deploy Arvist QC without disrupting workflows, immediately reducing shipment errors, labour costs, and claims. Its flexibility allows it to adapt across dock doors, conveyors, packing stations, staging areas, and even shrink-wrap machines.
This rapid proof of value is rare in logistics precisely because the impact is measurable. Shipment errors - often tracked via OSD (Overages, Shortages, and Damages), OTIF (On-Time, In-Full), or Perfect Order Rate- quietly erode warehouses' profitability. By providing real-time visibility and automated quality control, Arvist directly addresses this gap. Companies no longer need to accept inefficiencies, invest in complex systems, or over-rely on labor; they gain a scalable, effective alternative.
From a technology perspective, we think Arvist represents applied AI at its best. It is solving real problems that operators face every day. The system continuously learns and adapts to warehouse operations, generating actionable insights that improve decision-making and operational efficiency.
To us, Arvist represents the foundation for the next generation of warehouse operations. The company is creating a blueprint for predictive, data-driven logistics by embedding intelligence at the dock and other operational nodes. Warehouses that adopt Arvist run more efficiently and gain visibility and foresight into previously hard-to-track processes. This shift from reactive to predictive operations is how we expect logistics to evolve over the next decade.
At KOMPAS, we back builders who solve high-impact problems with disciplined execution, visionary thinking, and technology that works in the real world from day one. One of our strongest investment theses is supporting applied AI solutions that deliver measurable ROI in critical industries. Arvist exemplifies this approach – reshaping warehouse operations and setting a new standard in logistics technology.
-by Talia Rafaeli, Partner at KOMPAS VC.
