From robotics to artificial intelligence, here's how Amazon gets its products to Houstonians in record time. Photo by Natalie Harms/InnovationMap

How Amazon's Houston fulfillment center uses AI technology and robotics to move millions of products

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Last summer, Amazon opened the doors to its North Houston distribution center — one of the company's 50 centers worldwide that uses automation and robotics to fulfill online orders.

The Pinto Business Park facility has millions of products in inventory across four floors. Products that are 25 pounds or less (nothing heavier is stocked at this location) pass through 20 miles of conveyor belts, 1,500 employees, and hundreds of robots.

The center also has daily tours open to the public. We recently visited to see for ourselves the process a product goes through at this Houston plant. From stowing to shipping, here's how packages go from your shopping cart to your front porch.

Starting with stowing 

Natalie Harms/InnovationMap

A product's first step in an Amazon facility is stowing. There's no categorization of the products — it's not like there's one floor for one type of item or anything.

"It's completely randomly stowed," says Donna Beadle, PR specialist for Amazon. "She could be stowing cat food on this floor, and so could somebody on floor two."

An Amazon employee would scan an item and stow it into an empty bin of her choosing — sort of. To prevent confusion, a light projected indicates bins that are off limits to stow the item. The light identifies bins that have similar products. Keeping similar products apart helps prevents mistakes for the employee who later pulls those items once its ordered.

The system also sees where the employee is putting each item, rather than having to scan each item and the bin as well. This is a newer feature — the facility originally opened with hand-held scanners.

"Our next generation workstation is that they don't have to hold that scanner — they have hands free," says Brenda Alford, regional communications manager at Amazon.

Robots on the move

Once the bins are fully stocked, the robot — which is the orange device on the bottom of the yellow bins — moves about the facility by scanning QR codes on the floor.

Should a product fall out, an employee wearing a special vest can enter to retrieve it. That vest will send off a signal to the robots, which will then decrease their speeds and come to a stop when the employee comes close.

"It's an extra measure of safety so that people can interact with the robots and feel safe," says Beadle.

Picking before packing

Natalie Harms/InnovationMap

Once an item is ordered, the bin with that item appears in the pick process at the center. The system tells the Amazon employee which item to grab and which bin to put it in. The bins will have products for multiple different orders — another employee later will separate it out later.

"Often we describe it as a symphony — our technology and our associates working together," Alford says, noting that sometimes the company might receive criticism about using robots over humans. "We can't do this without these humans.

Amazon employees receive their benefits from day one on the job, Beadle says, and they work four, 10-hour days a week.

"We feel like that way they have more time with their families — they get three days off versus two days off. And that gives them time to heal and rest up," she says.

Bin to bin and back again

Natalie Harms/InnovationMap

Once full, the Amazon associate will push the bin onto a series of conveyor belts. The whole facility has 20 miles of conveyor belts — much of which happens overhead.

The bins then zigzag toward the pack process, which is separated to different stations. There are single-product stations and multiple package stations. The system determines where the bin should go, and some stations pack products that are determined to need packing materials, while others do not.

Single-product packaging

Natalie Harms/InnovationMap

At the packing process, the Amazon employee is told which size box to assemble — he or she can grab a bigger box, but they can't select a smaller one. The tape dispenser doles out the correct size of tape for that box automatically.

Once packaged up, a sticker with a barcode is placed on the box. This code will later be used to print the label for shipping. At this point in the process, no personal information has been revealed to anyone. In fact, most packages leave the facility without any personal information being viewed by employees.

In an effort to reduce packing materials, some products are shipped in the container they came in. In that instance, the packer would just place the barcode sticker on the package before sending it on the conveyor belt.

"If we don't need another box for that product, we don't use one," Beadle says. "We work with companies to make that happen, so we don't have to use more boxes if we don't have to."

SLAM 


While the robotics aren't slamming labels on packages, the SLAM process (short for scan, label, apply and manifest) is the first step in the process that includes a customer's personal information. During this process, the barcode is scanned, the package is weighed, and the label is printed and affixed to the package using a puff of air.

A package might be automatically pulled from the line if something seems to be off in the package's weight.

"Say you bought toothpaste, and it says that toothpaste weighs 20 pounds, we know something's wrong," Beadle says. "Like maybe that it was a pack that didn't get separated."

If the package is kicked off, an Amazon associate, called a problem solver, will assess the situation and make it right before returning it to the conveyor belt.

Kicked into gear

Once labeled, all the packages are sent on their final conveyor belt ride. Using a scanning process, the packages are kicked by an automated foot that sends them into a line to be loaded into an Amazon truck.

If a package misses its chute the first time around, it makes the loop again. The system can tell if a package is caught in the loop for whatever reason, and a problem solver might be called to assess the situation.

Down the slide

Natalie Harms/InnovationMap

After being kicked off the belt, the package then slides down a spiral chute that, despite looking like a playground slide, is off limits to any humans wanting to keep their job.

"People ask if you can go down the slide, and we always say that on your last day of work," Beadle jokes.

On to the shipping process

Natalie Harms/InnovationMap

The packages leave the facility in Amazon trucks and head to one more pit stop before making it to the customer.

"They don't go directly to your house after this process," Beadle says. "They go to a sortation center."

This could mean a USPS or UPS stop, but it depends on where the customer lives.

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Houston unicorn closes $421M to fuel first phase of flagship energy project

Heating Up

Houston geothermal unicorn Fervo Energy has closed $421 million in non-recourse debt financing for the first phase of its flagship Cape Station project in Beaver County, Utah.

Fervo believes Cape Station can meet the needs of surging power demand from data centers, domestic manufacturing and an energy market aiming to use clean and reliable power. According to the company, Cape Station will begin delivering its first power to the grid this year and is expected to reach approximately 100 megwatts of operating capacity by early 2027. Fervo added that it plans to scale to 500 megawatts.

The $421 million financing package includes a $309 million construction-to-term loan, a $61 million tax credit bridge loan, and a $51 million letter of credit facility. The facilities will fund the remaining construction costs for the first phase of Cape Station, and will also support the project’s counterparty credit support requirements.

Coordinating lead arrangers include Barclays, BBVA, HSBC, MUFG, RBC and Société Générale, with additional participation from Bank of America, J.P. Morgan and Sumitomo Mitsui Trust Bank, Limited, New York Branch.

“As demand for firm, clean, affordable power accelerates, EGS (Enhanced Geothermal Systems) is set to become a core energy asset class for infrastructure lenders,” Sean Pollock, managing director, project Finance at RBC Capital Markets, said in a news release. “Fervo is pioneering this step change with Cape Station, a vital contribution to American energy security that RBC is proud to support.”

The oversubscribed financing marks Cape Station’s shift from early-stage and bridge funding to a long-term, non-recourse capital structure, according to the news release.

“Non-recourse financing has historically been considered out of reach for first-of-a-kind projects,” David Ulrey, CFO of Fervo Energy, said in a news release. “Cape Station disrupts that narrative. With proven oil and gas technology paired with AI-enabled drilling and exploration, robust commercial offtake, operational consistency, and an unrelenting focus on health and safety, we have shown that EGS is a highly bankable asset class.”

Fervo continues to be one of the top-funded startups in the Houston area. The company has raised about $1.5 billion prior to the latest $421 million. It also closed a $462 million Series E in December.

According to Axios Pro, Fervo filed for an IPO that would value the company between $2 billion and $3 billion in January.

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This article first appeared on EnergyCapitalHTX.com.

Houston food giant Sysco to acquire competitor in $29 billion deal

Mergers & Acquisitions

Sysco, the nation's largest food distributor, will acquire supplier Restaurant Depot in a deal worth more than $29 billion.

The acquisition would create a closer link between Sysco and its customers that right now turn to Restaurant Depot for supplies needed quickly in an industry segment known as “cash-and-carry wholesale.”

Sysco, based in Houston, serves more than 700,000 restaurants, hospitals, schools, and hotels, supplying them with everything from butter and eggs to napkins. Those goods are typically acquired ahead of time based on how much traffic that restaurants typically see.

Restaurant Depot offers memberships to mom-and-pop restaurants and other businesses, giving them access to warehouses stocked with supplies for when they run short of what they've purchased from suppliers like Sysco.

It is a fast growing and high-margin segment that will likely mean thousands of restaurants will rely increasingly on Sysco for day-to-day needs.

Restaurant Depot shareholders will receive $21.6 billion in cash and 91.5 million Sysco shares. Based on Sysco’s closing share price of $81.80 as of March 27, 2026, the deal has an enterprise value of about $29.1 billion.

Restaurant Depot was founded in Brooklyn in 1976. The family-run business then known as Jetro Restaurant Depot, has become the nation's largest cash-and-carry wholesaler.

The boards of both companies have approved the acquisition, but it would still need regulatory approval.

Shares of Sysco Corp. tumbled 13% Monday to $71.26, an initial decline some industry analysts expected given the cost of the deal.

Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”