Byte-Sized AI is a bi-weekly column that covers all things artificial intelligence—from startup funding, to newly inked partnerships, to just-launched, AI-powered capabilities from major retailers, software providers and supply chain players.
Elm AI scores $2 million
Elm AI, a startup that spun out of Cornell University, announced April 12 that it had secured $2 million in funding. Beta Boom Fund and Working Capital Fund led the round, with further support from Boro Capital Partners, Very Serious Ventures, Gorges Ventures, The Bond Collective and Textbook Ventures.
Elm uses AI to ingest supplier documentation, like audits, and analyze the information. From there, it shares sustainability recommendations for future action, especially related to compliance. The company noted it works with a wide variety of companies, including many mid-sized apparel brands. One of its clients is Reformation, which has consistently worked with startups hawking emerging technologies.
Carrie Freiman Parry, senior director of sustainability at Reformation, said the startup has already helped the brand streamline the mundane pieces of her team’s work.
“Elm AI has been instrumental in transforming our responsible sourcing process, streamlining cumbersome administrative tasks and giving brands more time to focus on what matters most—building programs and management systems that benefit workers by ensuring safe, healthy, and equitable working conditions,” she said in a statement.
Elm AI plans to use its latest funding to upgrade the technology behind its systems and to onboard additional customers off its “extensive waitlist.” As it continues to build, the company hopes to become “the definitive platform for managing comprehensive supplier performance and risk data at global scale.”
C.H. Robinson sees success with agentic AI capabilities
Third-party logistics player C.H. Robinson announced this week that its generative AI-powered agents have performed more than 3 million tasks on behalf of employees.
Arun Rajan, chief strategy and innovation officer for the Minnesota-headquartered company, said that marks a strong measure of success for the technology.
“That’s 3 million manual tasks our people didn’t have to do,” Rajan said in a statement. “We’re at well over 1 million price quotes delivered by AI. In March, we hit 1 million orders processed by AI. Those are two of our most mature generative AI agents, and they’re more capable every day as the models we’ve built get smarter and as we apply them to more of our 83,000 customers. Each additional shipping step we’ve automated beyond those has created new leaps in efficiency for global supply chains and freed our people to do more high-value work for our customers.”
Agentic AI allows companies to handle specific tasks autonomously, without human intervention. The technology is becoming increasingly popular and is often assigned to handle mundane tasks that might take away from a human’s ability to do other work.
C.H. Robinson has used the technology to automate quoting, set up pickups and deliveries, monitor the status of in-transit loads and garnering trucking capacity for less-than-truckload (LTL) orders. Its agents, like freight forwarder Flexport‘s, can also use AI voice tools to call and inquire about the status of an order if it’s missing.
Rajan said as the technology continues to advance—and as additional viable use cases become better known to the company—C.H. Robinson plans to continue building technology to streamline processes for greater efficiency and client satisfaction.
“Greater automation not only makes our operations and our customers’ supply chains more efficient. It lowers our cost to serve while simultaneously raising our quality of service. As we deploy generative AI across more aspects of our business, our teams can spend more of their time on the most complex shipments and the most pressing disruptions and the most valuable supply chain optimizations for our customers. In 2025, we increasingly view generative AI as a growth lever and a critical element of our broader ecosystem of AI capabilities for customers, carriers and the company.”
Mothership uses AI to help avoid rebilling and unnecessary charges
Mothership, a startup that uses AI to match buyers seeking freight availability with carriers, announced earlier this month it had launched an AI agent aimed at preventing buyers from incurring unwarranted accessorial charges and rebills. Accessorial charges are additional fees accrued for additional labor, special tools and other extras that go beyond standard pickup and delivery.
Aaron Peck, Mothership’s CEO and founder, said the company has already saved shippers more than $1 million with the tool.
“Accessorial charges can significantly inflate shipping costs—sometimes by hundreds of dollars per shipment. While the average freight accessorial charge is about $60, some carriers add $526 or more in post-shipment rebills for a single shipment,” Peck said in a statement. “Our AI agent can save shippers thousands of dollars per month, empower them to better manage their shipping costs and ensure on-time delivery. This is just one more way Mothership has made freight more transparent, reliable and affordable.”
Peck’s team built the proprietary technology in house. It allows shippers to receive a freight quote for LTL shipments or same-day shipments in less than a minute; as part of creating a quote, Mothership’s AI agent investigates details about the shipment—where it needs to be picked up, the specs of the freight, expected freight lanes and more. Based on that information, it can include any accessorial charges in the quote at the outset of the transaction. It can also offer discounts based on the order, if those handling the freight are willing to offer complimentary liftgate or pallet-jack services.
Jon Rappaport, Mothership’s principal product manager, said having that information early helps enable clients to have a more transparent picture of the transaction in advance.
“By proactively surfacing risks like suggested accessorials, our AI architecture drives faster, more accurate decision-making, reducing manual effort and eliminating costly surprises.”
