Why Pallet Needed Another Raise Just 7 Months After Its Series A

Pallet didn’t plan to raise another round this soon.

The logistics AI startup had only just announced its $21 million Series A last fall when customers began coming back not with complaints, but with dozens of ideas. 

“We built software to complete manual logistics workflows,” says co-founder and CEO Sushanth Raman. “But customers started surfacing new use cases we hadn’t even considered. That’s when we realized: the opportunity wasn’t just large, it was urgent.”

Just seven months later, Pallet raised a $27 million Series B led by General Catalyst, with continued participation from Bain Capital Ventures, Activant Capital, Bessemer Venture Partners, BoxGroup, and Vicus Ventures. The new capital brings Pallet’s total funding to $50 million and accelerates its efforts to automate what Raman calls the “administrative backbone” of global freight.

The catalyst for the raise was not investor momentum, but customer pull. Early adopters saw CoPallet, the company’s AI workforce, as a tool to offload repetitive back-office work and then pushed Pallet to expand its scope. Raman and his team realized that more than $1 trillion of the $11 trillion global logistics spend goes to administrative coordination: order intake, quoting, shipment tracking, updating systems. The entire market for SaaS, by comparison, is smaller.

“This wasn’t a story about hype. It was a story about math,” Raman says. “A midsized carrier reallocated 25 employees doing repetitive order entry. That saved them millions. The ROI was obvious, and our biggest challenge became keeping up with demand.”

Logistics Problem Hidden in Plain Sight

The company’s thesis is deceptively simple: global logistics doesn’t just suffer from physical bottlenecks, it drowns in manual processes. A single shipment might involve shippers, carriers, freight forwarders, brokers, and warehouses, all of whom work on different systems. Keeping everyone in sync means endless typing, reconciliation, and coordination.

“Ten percent of logistics spend goes to administrative work. That’s quoting, data entry, tracking updates all done manually,” says Raman. “That’s the layer we’re automating.”

Pallet’s flagship product, CoPallet, is a set of intelligent AI agents trained to perform logistics workflows the way human coordinators do with context, adaptability, and judgment. Unlike RPA tools, which are rigid and break when a field moves or a UI changes, CoPallet interprets documents and interfaces in real-time.

“If the shipper address on a bill of lading moves from the top left to the bottom left, our agents will figure that out,” Raman explains. “They understand the concept of a shipper address, not just its coordinates on a form. Same with UI changes — if a button moves, our agent still knows what it’s supposed to do.”

Automating the $1 Trillion Glue Layer of Logistics

Pallet is betting on a part of logistics that rarely makes headlines: the back office. According to the company, nearly 10% of the $11 trillion global logistics spend  over $1 trillion  goes to administrative work: quoting, order intake, tracking updates, and system reconciliation. This work touches every shipment, yet remains fragmented across parties, systems, and formats.

The difference, says Raman, is that CoPallet doesn’t rely on templates or scripts. It performs like a human logistics coordinator adapting to exceptions, interpreting documents, and navigating changing interfaces.

In a recent demo, Raman walked through how CoPallet handles variability that breaks traditional tools like OCR or RPA.

“Let’s say the location of the shipper address changed from the top left of the bill of lading document to the bottom left,  the agent will actually know,” Raman explained. “It’ll figure out that the field is now in the bottom left, determine that it’s an address, and catch that difference much like a human would. Traditional OCR is very configured to the format. If the layout changes, it breaks.”

That same flexibility extends to digital interfaces.

“RPA is hard-coded to how a website is laid out. If the ‘Complete’ button moves, the bot breaks,” Raman continued. “But what you saw in the demo was the AI agent scanning all parts of the interface, asking, ‘Which of these buttons looks like the complete button?’ Much like a person would based on visual cues, not coordinates.”

That level of dynamic intelligence has become essential as logistics operators face a wave of pressure from tariffs, global supply disruptions, and rising input costs. Automating administrative friction has become a high-leverage strategy.

Raman says, “It’s not about removing people. It’s about giving operators capacity and flexibility without adding overhead.”

Deep Industry Over AI Hype

That emphasis on domain expertise not just technical ability is what attracted General Catalyst.

“We believe the next wave of iconic companies will come from applied AI not general models, but purpose-built systems for specific, high-friction problems,” says Marc Bhargava, Managing Director at General Catalyst. “Pallet is doing that for logistics. It’s a massive category, and they have the credibility to execute.”

That credibility has been hard-won. At Pallet, product teams spend one week every month embedded with customers not over Zoom, but on-site. Raman says they’ve moved pallets, tracked containers, and even slept on warehouse floors to understand real-world workflows.

“You don’t learn freight quoting by sitting in a demo,” he says. “You learn it by watching someone manage exceptions across five systems while a shipment’s stuck in customs.”

That kind of field work has helped Pallet identify where automation can actually work and where it can’t. CoPallet isn’t a chatbot or a passive interface. It’s a background AI system that acts like a full-time logistics coordinator, handling order ingestion, tracking updates, carrier tenders, and data entry across transport management systems and customer platforms.

Building in a Time of Pressure

The timing for such a platform couldn’t be more relevant. Logistics operators are under growing pressure to do more with less. Tariffs, fuel price volatility, and economic headwinds have made cost discipline critical. But cutting headcount has traditionally meant losing operational capacity. That’s the gap Pallet is trying to close.

“CoPallet is like having a hundred virtual coordinators on staff  at a fraction of the cost,” Raman says. “It gives operators flexibility without sacrificing service.”

Customers aren’t just experimenting. They’re integrating CoPallet into their core operations,  freight forwarders, 3PLs, shippers, and midsize carriers among them. That depth of usage, Raman says, made it clear that the company needed to scale faster than expected, not just on product, but on engineering, onboarding, and support.

With the new funding, Pallet plans to expand its team and deepen its footprint across logistics segments. But Raman is careful not to call this a blitzscale moment.

“The work is still ugly,” he says. “You’re dealing with exceptions, broken systems, last-minute changes. That’s what makes it worth solving. It’s not glamorous but it’s real, and it affects everyone who eats, ships, or buys anything.”