Welcome to this episode of The New Warehouse Podcast, where Kevin speaks with Maanav Iyengar, Co-Founder and CEO of Retina Robotics. Founded by robotics engineers with firsthand exposure to warehouse operations, Retina Robotics makes automation more accessible through computer vision.

In this conversation, Iyengar discusses the challenges slowing automation adoption, how Retina Robotics is helping warehouses improve inventory accuracy, and why the company believes computer vision can transform inventory management.

Making Automation Accessible to More Warehouses

Retina Robotics was founded after Iyengar and his co-founder (Vishrut Bohara) spent months speaking with warehouse operators and managers. As Iyengar explained, “We wanted to answer the question, which was why it is that autonomy is not being broadly adopted at a scale that people have expected it to.” Through those conversations, the team discovered, “over 80% of the warehouses in the US have basically zero automation and are still largely manual.”

According to Iyengar, “We were yet to see a single solution that could manage all types of inventory, all types of operations, such that the end consumer wasn’t changing their warehouse drastically or spending an arm and a leg for a wide array of solutions.” That insight led Retina Robotics to develop WAM, a computer vision device that mounts directly onto forklifts, order pickers, reach trucks, and other equipment already operating within the warehouse.

Preventing Errors Before They Happen

Many inventory systems identify mistakes after they occur. Retina Robotics takes a different approach. The WAM actively communicates with operators during picking and put-away activities to help prevent errors before they impact operations or customers.

Iyengar explained the company’s philosophy, stating, “I don’t think it’s enough to tell somebody that they have made a mistake. I think we must correct that mistake from happening before it could even happen.” The system validates inventory movements in real time and can notify operators when they select the wrong pallet or attempt to place inventory in the wrong location.

As Iyengar described it, “what we wanted to do was build a solution that would actually stop you from picking the wrong item before you could even pick it up, or stop you from putting an item away in the wrong spot.” In addition to validation, WAM captures dimensions, occupancy data, and images throughout the inventory lifecycle. The long-term vision is even bigger. Iyengar noted that “what we are building toward is a truly hands-free scanless future.”

Real-Time Pallet Tracking with WAM™

Turning Everyday Operations into Continuous Audits

Using WAM, operators can collect inventory data as they drive through the facility. As Iyengar explained, “Just by driving past an aisle as you normally would, doing your routine work like picking or putting away, not changing the way that you do anything, we are not trying to disrupt your aisle. WAM will continuously and fully passively audit and cycle count all of your inventory.”

This approach has delivered measurable results for customers. One operation uses WAM to track pallet locations and eliminate time spent searching for inventory. Another uses the system to audit inventory in very narrow aisles where traditional solutions struggle to operate. According to Iyengar, “we’ve saved them hundreds of thousands to even potentially, you know, million plus dollars in lost inventory.” Looking ahead, Retina Robotics is expanding its capabilities into case-level inventory management, an area the company believes remains underserved across the industry.

Continuous Drive By Auditing with WAM™

Key Takeaways from Retina Robotics

• More than 80% of U.S. warehouses remain largely manual.
• Retina Robotics developed WAM after interviewing warehouse operators about automation challenges.
• WAM mounts directly onto existing forklifts, reach trucks, order pickers, and other MHE.
• The system scans, counts, dimensions, tracks, and validates inventory using computer vision.
• All processing occurs on-device, reducing dependence on warehouse Wi-Fi connectivity.
• WAM helps prevent fulfillment errors before inventory leaves the facility.