AI Turns Warehouse Cameras Into Throughput Machines—Without New Hardware
Seeteria’s platform uses existing cameras to slash idle dock time and boost capacity by hours per shift
Warehouses are leaving hours of capacity on the table every shift, hidden in plain sight.
Seeteria’s system connects to a facility’s current camera infrastructure via Wi-Fi, analysing activity across the floor and sending live alerts to supervisors when bottlenecks emerge. The pitch is straightforward: identify disruptions that appear minor in isolation, 7 minutes of idle dock time here, 12 minutes of forklift rerouting there, but compound into hours of lost capacity per shift. “Our goal all the time is to get the warehouse more capacity from the resources that they are already paying for,” said Sarit Tamir, founder and CEO of Seeteria.
How AI Spots the Invisible Losses: Warehouse
The platform targets what Tamir calls “incremental capacity losses”, delays that warehouse managers often dismiss as routine. A staging area congested for 15 minutes, a dock door left idle for 7 minutes, or a forklift forced to reroute around a blocked aisle for 12 minutes might seem negligible on their own. But when multiplied across dozens of doors, forklifts, and shifts, these disruptions accumulate into significant throughput losses.
Seeteria’s approach is rooted in a decade of expertise. Tamir brings more than a decade of experience building AI and computer vision solutions for logistics, warehousing, and manufacturing.
The system’s ability to analyse real-time data without additional sensors is a key differentiator.
Seeteria’s platform is also designed with privacy in mind. “The system is completely blind to people,” Tamir emphasised, addressing concerns that often arise with AI surveillance in workplace settings.
Real-Time Alerts and Financial Impact for Executives
The platform serves three distinct user tiers, each with tailored visibility. Floor supervisors receive live push alerts on mobile or tablet apps, with a colour-coded status (green, yellow, or red) for each dock door and zone. This allows them to respond immediately to disruptions, reducing the need for the 8 miles they typically walk per shift.
Warehouse managers receive post-shift summaries of bottlenecks, enabling them to refine workflows over time. Executives, meanwhile, see a financial-impact dashboard tied to metrics such as detention fees and missed throughput targets, turning operational data into tangible cost savings.
The financial-impact view is particularly critical for decision-makers. By quantifying the cost of inefficiencies, such as detention fees or missed delivery windows, Seeteria’s platform provides executives with a clear business case for operational improvements.
For warehouses considering Seeteria’s platform, the minimum facility requirement is eight active dock doors and a meaningful forklift fleet. The company is currently recruiting U.S. pilot partners, with a focus on facilities that meet these criteria. Interested warehouses can explore pilot opportunities through Seeteria’s official channels or by engaging with the CoLab accelerator, where the startup recently completed a development programme.
Seeteria’s recent participation in the CoLab accelerator in Chattanooga, Tennessee, has positioned the company for rapid growth. CoLab, known for supporting early-stage startups in logistics and supply chain innovation, provided Seeteria with mentorship, networking opportunities, and access to potential pilot partners.
The accelerator’s location in Chattanooga, a hub for freight and logistics technology, offers strategic advantages, including proximity to major distribution centres and industry events. The upcoming pilot launch in the region will serve as a critical test for the platform’s scalability and effectiveness.
The origins of Seeteria’s name reflect its mission. Derived from Soteria, the Greek goddess of safety, the name underscores the platform’s focus on operational security and efficiency. The tweaked spelling, replacing the “o” with an “e”, highlights the company’s computer vision foundation, a nod to its technical roots. This blend of mythology and modernity encapsulates Seeteria’s ambition: to merge cutting-edge technology with practical solutions for the logistics sector.
For warehouse operators, Seeteria’s platform represents a low-risk opportunity to unlock hidden capacity. By leveraging existing camera networks, the system eliminates the need for costly hardware upgrades or complex integrations. This plug-and-play approach reduces both financial and operational barriers to adoption, making it accessible to a wide range of facilities. The platform’s real-time alerts and post-shift summaries provide actionable insights that can lead to immediate improvements in workflow efficiency.
Warehouses that adopt Seeteria’s solution can expect to see measurable gains in throughput, reduced congestion, and lower operational costs. The platform’s ability to quantify the financial impact of inefficiencies, such as detention fees or missed delivery windows, provides executives with a clear business case for investment. For facilities struggling with idle dock doors, blocked aisles, or forklift congestion, Seeteria offers a data-driven path to optimisation without the need for disruptive overhauls.
Looking ahead, Seeteria’s expansion will depend on the success of its pilot programmes. The company is actively seeking partnerships with U.S. warehouses that meet its minimum facility requirements. Operators interested in exploring the platform can engage directly with Seeteria or through industry events such as the Home Delivery World conference in Nashville, where the startup first connected with the CoLab accelerator. As the logistics sector continues to embrace AI and automation, solutions like Seeteria’s are poised to play a pivotal role in shaping the future of warehouse management.
The implications for the logistics sector are clear. By leveraging existing infrastructure, Seeteria’s platform offers a low-friction way to unlock hidden capacity, reduce operational inefficiencies, and improve throughput, all without the need for costly hardware upgrades. For warehouses struggling with congestion and idle time, the question is no longer whether they can afford to adopt AI, but whether they can afford not to.
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