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Home » Robust.AI Introduces “Crawl, Walk, Run” Automation Model with ShipLab Deployment in Vista, CA
Press Release

Robust.AI Introduces “Crawl, Walk, Run” Automation Model with ShipLab Deployment in Vista, CA

By News RoomJuly 8, 20263 Mins Read
Robust.AI Introduces “Crawl, Walk, Run” Automation Model with ShipLab Deployment in Vista, CA
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SAN FRANCISCO, July 08, 2026 (GLOBE NEWSWIRE) — Robust.AI, a leader in AI-driven warehouse automation, today announced a partnership with ShipLab, a San Diego-area ecommerce fulfillment and third-party logistics provider, to deploy Carter™ collaborative mobile robots at ShipLab’s Vista, CA facility. The deployment follows a phased model designed to let ShipLab validate performance at each stage before expanding, with an initial go-live planned for July 2026.

The partnership begins with a pilot in which Carter will automate tote transport between fulfillment and packing stations. Upon successful validation, the deployment will expand to a full fleet of Carter robots operating in a broader set of applications across their picking operation. The phased approach, which Robust.AI structured as a “Crawl, Walk, Run” model, allows ShipLab to build operational confidence incrementally, with RaaS payments deferred at each phase until performance targets are jointly confirmed.

“Every technology investment we make has to earn its place, and that means proving it works in our environment before we commit to scaling it,” said Jake Brenner, CEO, ShipLab. “The Crawl, Walk, Run model Robust.AI brought to the table was the right approach for us. We get to validate performance at each step, we only pay when the system delivers, and we don’t have to touch our existing operation to make it work. For a growth-focused business like ours, that combination removes the risk that usually holds operators back from automation.”

Robust.AI’s Carter™ is a collaborative mobile robot designed to work seamlessly alongside warehouse associates without requiring changes to existing facility infrastructure. Carter’s software-defined functionality allows operations to evolve and expand from simple applications like point-to-point transport to more sophisticated ones like fully integrated order picking, all using the same fleet. Its performance-based RaaS model ensures customers only pay once the system is operational and delivering results.

“ShipLab has built a reputation for accountability and speed that the most demanding ecommerce brands rely on. Ecommerce fulfillment moves fast, and the teams running it need automation that keeps up without getting in the way,” said Anthony Jules, co-founder and CEO of Robust.AI. “The phased approach we designed reflects our shared belief that automation should prove its value before you scale it, and that is precisely what Carter was built to do.”

About ShipLab

Founded in 2017, ShipLab is an ecommerce fulfillment and third-party logistics provider based in Vista, CA, serving brands of all sizes with ecommerce pick and pack, LTL warehousing, kitting, Amazon fulfillment, and project-based logistics services. Founded by entrepreneurs with firsthand experience in ecommerce operations, ShipLab combines technology-driven fulfillment with 99.9% accuracy standard and same-day shipping commitments. For more information, visit www.shiplabsd.com.

About Robust.AI

Founded in 2019, Robust.AI brings together real-world physical AI and user-centric design to make robots that work for people. The company’s flagship robot, Carter™, combines industry-leading commercial robotics and groundbreaking human-robot interaction to make it broadly useful, effortless to adopt, and delightful to use. Robust.AI’s solutions prioritize seamless, safe human-robot collaboration to drive higher productivity across picking, putaway, value-added services and material handling, no infrastructure changes required. For more information, visit www.robust.ai.

Media Contacts

Anita Whiteside
[email protected]

Josh Pedro-Kriner
[email protected]

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/9dcce6bd-f7e1-4d6d-b883-cb8feefb872c

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