Most brands spend a lot of time trying to figure out how to sell more product. Far fewer build a smart system for what happens when product does not sell. That is where Amrita Bhasin has carved out a very practical lane with Sotira, the San Francisco-based company she co-founded with Gary Kwong. Sotira is built to help retailers and brands discreetly offload and monetize unsold or short-dated inventory while protecting brand value, and the company positions AI as a core part of how that process gets faster and more useful.
The real cost of unsold inventory for modern brands
Unsold inventory is easy to underestimate because it often looks like a warehousing problem on the surface. In reality, it is a margin problem, a cash flow problem, and sometimes a brand problem too. The longer excess stock sits, the more it eats into storage budgets, ties up working capital, and pushes teams toward perpetual discounting that can weaken long-term pricing power. Sotira’s own positioning speaks directly to these pain points, calling out high storage costs, capital tied up in inventory, landfill fees, and brand dilution as the hidden costs of surplus stock.
That framing matters because it changes the conversation. Instead of treating overstock as a messy clean-up task at the end of a selling cycle, Amrita Bhasin’s approach treats it as an operational category that deserves better infrastructure. When brands think about excess inventory this way, inventory recovery stops looking like a desperate last move and starts looking like a smarter part of inventory management, reverse logistics, and supply chain decision-making.
Who Amrita Bhasin is and what Sotira is building
Amrita Bhasin describes Sotira as a tech-powered solution for retailers and brands to offload and monetize overstock and unsold inventory. On the company side, Sotira describes itself as an integrated platform created to modernize the old-school process of selling into the secondary market. That background is important because it explains why the company’s focus is not only on selling excess stock, but on doing it discreetly, quickly, and with more control than traditional liquidation channels usually offer.
Sotira’s story also feels grounded in firsthand operational frustration rather than generic startup language. According to the company, Bhasin and Kwong built Sotira after years of running liquidation operations for D2C and brick-and-mortar businesses. That experience shows up in the way the platform is positioned. It is not framed as abstract AI for commerce. It is framed as workflow and compliance software for surplus inventory offloading, transacting, and logistics. That difference makes the value proposition sharper.
Why traditional liquidation has not worked well for brands
Traditional liquidation has always had a trust problem. Brands worry about where product will end up, how fast it will move, how much value they will recover, and whether discount channels will undercut their main business. On top of that, the process is often manual, slow, and fragmented. Inventory lists get passed around, buyers are inconsistent, negotiations drag on, and logistics paperwork adds friction at exactly the moment brands want speed and clarity. Sotira’s own language suggests it was built in response to that outdated process.
That is why Amrita Bhasin’s thesis lands. The issue is not just that brands have too much stock. It is that the systems around surplus inventory are often too clunky to preserve margin. If you are stuck waiting weeks or months to move product that is aging, seasonal, or nearing expiry, the economics get worse almost by the day. That makes a better resale channel more than a convenience. It becomes a real business need.
Where AI fits into the inventory recovery process
The interesting part of Sotira is not that it uses AI as a buzzword. It is that the AI is tied to very specific operational steps. Sotira says sellers can sync inventory through a WMS API or upload spreadsheets, and the platform’s AI instantly matches that inventory with qualified buyers. For a category that has traditionally relied on slow email chains, scattered broker relationships, and manual review, that kind of matching can remove a lot of dead time.
This is where AI actually feels useful in retail operations. It can help classify lots faster, connect products with the right buyer profiles, surface competitive bids, and cut down on the back-and-forth that usually slows the secondary market. Sotira also says its software helps businesses cut the time spent negotiating and reviewing inventory by more than half. That matters because in surplus inventory management, speed is not just a nice feature. Speed often determines recovery value.
How Sotira helps brands recover more value from unsold goods
Sotira’s pitch to sellers is straightforward. It says brands can turn expired or unsellable items into cash through a private network of buyers, recover up to 50 percent of costs on short-dated or dead stock, and maintain control over offloading restrictions to protect larger accounts. That combination is important because it addresses both sides of the problem. Brands want better recovery, but they also want brand-safe resale channels.
The company also says its seller network connects brands to more than 2,000 verified buyers. That is a meaningful detail because value recovery depends on liquidity. The better the buyer network, the better the chance of finding demand for surplus inventory that would otherwise sit in a warehouse or head toward landfill. In that sense, Amrita Bhasin is not just building software. She is building a more structured marketplace for excess stock, where inventory visibility, pricing, negotiation, and transaction flow all live in one process.
Why brand protection matters in the secondary market
One of the hardest parts of surplus resale is brand protection. A lot of companies would rather hold stock too long than risk losing control over where it gets sold. That fear is not irrational. If excess inventory shows up in the wrong channels, it can upset retail partners, weaken pricing integrity, and train customers to wait for discounts. Sotira clearly leans into this concern by emphasizing discreet offloading, vetted buyers, and the ability for sellers to control where products cannot be sold.
That makes Amrita Bhasin’s model especially relevant for consumer brands, CPG brands, and retailers that care about both recovery and reputation. The goal is not simply to liquidate inventory at any cost. The goal is to recover value without creating new downstream problems. That is a much more mature way to think about dead stock, short shelf life inventory, and overstock monetization.
How speed changes the economics of surplus inventory
Sotira says most inventory is moved within two to five days, and that suppliers may be able to have orders picked up directly from the warehouse as soon as the next day. Those are not minor workflow details. They go straight to the financial logic of the platform. If a business can offload inventory in days instead of weeks, it can reduce storage fees, free warehouse capacity, recover working capital faster, and avoid the deeper value erosion that comes from delay.
This is where a lot of legacy surplus systems fall short. They may eventually move product, but they do not move with enough speed to preserve margin. Amrita Bhasin’s framing suggests that surplus inventory should be handled more like a time-sensitive operational event than a background issue. That is especially true for categories like food and beverage, health and wellness, and other products where shelf life, packaging changes, or market timing can quickly reduce resale options.
Why compliance and logistics matter more than people think
A surplus inventory sale is not finished when a buyer says yes. Someone still has to handle the purchase orders, shipping documents, compliance requirements, freight coordination, and pickup timelines. Sotira makes a point of saying those steps are streamlined inside the platform, which helps explain why the company talks about itself as workflow and compliance automation software, not only as a marketplace.
That distinction matters because operational friction is often what kills resale value. A brand may have buyer interest, but if the documentation, compliance rules, or logistics coordination become too messy, the deal slows down or disappears. By treating paperwork, freight, and transactional flow as part of the product, Sotira is aiming at the real bottleneck. That is a more practical application of AI and automation than the usual marketing claims around retail technology.
What this means for retail waste and circular commerce
There is also a broader environmental angle here, though it works best when described in operational terms instead of vague sustainability language. Sotira says it has rerouted millions of pounds of unsold inventory from landfills. That turns surplus management into more than a balance-sheet issue. It becomes part of a circular commerce model where products still have downstream value if brands can access the right buyers quickly and safely.
That may be one reason Amrita Bhasin’s work gets attention beyond startup circles. Her public profile consistently connects retail, supply chain, circular economy, and waste reduction. The bigger idea is simple: a lot of retail waste is not caused by products having zero value. It is caused by bad matching, poor timing, weak systems, and too much friction in the secondary market. Fix those gaps, and brands can recover costs while reducing shrink, landfill volume, and unnecessary waste.
What other retail and e-commerce operators can learn from Amrita Bhasin
The biggest takeaway from Amrita Bhasin’s approach is that unsold inventory should not be treated like an afterthought. Brands need a surplus strategy before inventory becomes a full-blown financial problem. That means building cleaner inventory visibility, faster response systems, stronger resale policies, and better off-price or secondary market relationships before the pressure hits. Sotira’s model is built around that exact shift from reactive liquidation to more proactive inventory recovery.
There is also a useful lesson here about AI in commerce. The most valuable AI applications are often not the flashy customer-facing ones. Sometimes the better use case is buried in operations, where small gains in matching, timing, pricing, and workflow can unlock real margin. In that sense, Sotira feels less like a trendy AI startup and more like infrastructure for an overlooked part of retail. That is what makes Amrita Bhasin’s work with Sotira worth watching.
