Twelve storage lockers full of shoes ought to be a promising beginning. In Phoenix in 2021, a purchase of $40,500 brought HAMMOQ a quantity of name-brand footwear and an immediate complication: some of the right shoes needed their left partners. There were Air Jordans, Nikes, and Jimmy Choos. There was also the less fashionable business of making pairs.
Sid Lunawat appeared in the television coverage explaining the software side of the operation. His co-founder, Ty Blunt, discussed the footwear. Blunt expected the lot to yield more than a million dollars, a prediction rather than a completed result. Jared Visser had helped match 350 pairs. Before anyone could count the profits, somebody had to count to two.
The episode is a useful introduction to Siddharth “Sid” Lunawat, the Orlando-based co-founder and CEO of HAMMOQ. His business lives in the space between a physical object and a saleable online record. A shoe can be desirable, valuable, and entirely invisible to an internet shopper. Until the work is done, its commercial career is largely confined to a shelf.
An engineer’s route to the resale rack
Lunawat’s education combined a bachelor’s degree in industrial engineering at Georgia Tech with an MBA at Duke’s Fuqua School of Business. His professional record includes technology work at GE, a product-manager role at IBM, and product work at Boston Consulting Group. These are useful coordinates for understanding the founder who later chose to work on used merchandise: engineering, products, and the economics of getting something done.
He also co-founded DataPure. Its work has included preparing data for machine-learning applications; its present public description emphasizes retail intelligence. Lunawat describes teams photographing shelf tags in stores in the United States and Europe, then turning what the cameras see into structured information. A printed price becomes something a system can search, compare, and use.
There is a connection between that work and HAMMOQ. Physical retail supplies plenty of information, but it rarely arrives arranged to please software. A shelf label, a receipt, and a worn garment each present a small translation problem. His companies work on different versions of that problem. The point of the photograph is what can happen after it.
A partner who knew the shelves
Blunt brought an intimate knowledge of resale to their partnership. He searched marketplaces, stores, estate sales, and garage sales for goods he could sell at a premium. His business approached $2 million in annual revenue, and he lived in the warehouse containing the inventory. Nintendo games and antiques were among the quarry. Finding overlooked value had become a livelihood.
Growth made the office work more demanding. Listings had to go up, stock had to be tracked, and sold goods had to come off the relevant marketplaces. Those jobs consumed time he could otherwise spend sourcing. Lunawat and Blunt founded HAMMOQ to reduce that burden. Their early financing announcement paired Lunawat’s machine-vision experience with Blunt’s resale knowledge.
That pairing gave the company a concrete brief. Help someone who already knows how to find merchandise get more of it into circulation. It is easy to admire a successful bargain hunter; it takes closer attention to notice the forms waiting when the hunt is over.
“the more you list, the more you sell”
Sid Lunawat · June 2021
The money followed the paperwork
On June 29, 2021, HAMMOQ announced a $3 million seed round led by Origin Ventures, with Sierra Ventures, SaaS Ventures, and Silicon Road Ventures participating. The company described hundreds of reseller customers and a platform for repetitive tasks around online selling. The intended beneficiary was recognizable: a seller spending too much time administering the business and too little time finding its next sale.
Lunawat’s own announcement said the team had grown to more than 200 people across the United States, India, Ukraine, the Netherlands, and Egypt. That was the team he described at the time. Even early in the company’s public life, the work extended across borders while serving a trade often conducted one distinctive object at a time.
In June 2022, HAMMOQ announced another $24 million in financing, led by Sierra Ventures with Origin participating. That package combined equity and debt. The announcement put total financing to date at $27 million and reported more than 600,000 products listed. These were dated company milestones, with a practical purpose attached: develop the technology and support further commercial expansion.
His comparison for the business was Shopify: give smaller merchants useful infrastructure and let them pursue their own customers. In discussing resale, he extended that idea to tools for sourcing merchandise and financing inventory. The ambition reached beyond writing a description, toward supporting the working life of a reseller.
A second life needs a workable bill
Lunawat has tied the commercial project to keeping usable goods in circulation. In his account, retailers can hesitate over resale because processing returns appears more expensive than setting them aside. The opportunity depends on reducing that cost. Environmental intention, however sincere, still encounters wages, handling, and the amount a customer will pay.
The HAMMOQ name adds a little leisure to this industrious proposition. Lunawat has explained it as a reference to sellers being able to relax while the heavy work of processing no longer holds them back. It is an agreeable promise for a company concerned with cataloguing. Few people enter commerce dreaming of a longer evening with a product-description form.
He has also joked about learning through “YouTube University.” It is a small detail, but a welcome one in discussions of artificial intelligence: the founder points prospective resellers toward the familiar business of watching, learning, and trying. The trade still requires people willing to begin.
One item. Several jobs.
- 01PhotographMake the object visible
- 02Identify & describeTurn details into usable fields
- 03Price & listPut an offer before a buyer
In 2023, Google for Startups included HAMMOQ in its inaugural Circular Economy accelerator cohort. That placed the company alongside businesses working on reuse, recycling, and related problems. For Lunawat, it was another setting for a longstanding proposition: goods need an affordable route back to buyers. A second life becomes more plausible when the first few steps are manageable.
The camera needs charging
By April 2026, his personal writing had moved into the mechanics of gathering data for robotics. The subject changes from resale listings to warehouse footage, yet his attention stays close to operations. In an essay on collection logistics, he discusses distributing equipment, training people to wear cameras, and getting the resulting files back out of busy facilities.
The details are almost defiantly ordinary. Batteries run out. Storage fills. A smudged lens spoils footage. A building suited to moving inventory may be poorly equipped to upload large video files. These are examples in his argument about why data collection requires infrastructure. An impressive algorithm remains dependent on an unimpressive charging routine.
Another essay questions the wisdom of training a robot in one immaculate warehouse and expecting it to work everywhere. Lunawat points to differences in lighting, floors, shelving, dust, and the movements of people and vehicles. His argument favors representative experience over a large collection of similar footage. A machine may have seen a great deal while having seen too little variety.
He also writes about gathering data in the environment where a system will eventually operate. The warehouse has its own visual context and routines; moving between settings can expose gaps in what a model learned. These essays reveal his current interests without requiring a grand prediction about robotics. The questions are concrete enough: where was the footage made, what does it contain, and will it help with the actual job?
The price of lunch, and a lesson for children
Closer to home, Lunawat maintains the Orlando Fast Food Price Index, an open dataset following pickup prices at specific restaurant locations. Its documentation names Taco Bell, Wendy’s, and Burger King. The chosen areas include the tourist strip, the airport, the university area, and residential districts. The collection method uses the chains’ own ordering sites.
The interesting feature is the care given to context. Observations include the store, the item, the date, and the local time. Missing prices are recorded as missing, with a reason, rather than supplied by guesswork. That makes the project a small public example of his broader concern with useful data. A number improves considerably when you know what it describes.
His author profiles add another undertaking: How to Teach AI to a Five-Year-Old, a six-week course described as screen-free, with lessons for children aged four to seven. The GitHub profile explains that lesson lengths vary for pre-K, kindergarten, and first grade. It is a different audience from a resale warehouse, with rather different patience for jargon.
Taken together, these projects make Lunawat’s interests more tangible than a list of executive titles could. There are objects to describe, places to understand, prices to record, and ideas to explain. Each requires attention to the thing in front of you. Even the shoes from those Phoenix lockers offered an elementary lesson: first establish what you actually have. Then find its partner.