Dave Clark wants to eliminate meetings. At least, the kind of meetings that waste time—the ones where supply chain managers gather around conference tables to debate whether to expedite a shipment or reroute inventory, decisions that software could make in milliseconds if only it had the right context and authority.
Clark, who spent 23 years at Amazon rising to CEO of Worldwide Consumer before a turbulent nine-month stint running Flexport, thinks he's found the answer. His startup, Auger, just closed a $50 million Series B led by Eclipse on July 9, with participation from Oak HC/FT, the firm that led and entirely funded the $100 million Series A announced on October 8, 2024. That brings total funding for the Bellevue, Washington-based company to $150 million—a war chest that reflects both investor confidence in Clark's pedigree and the market's appetite for anything labeled "agentic AI."
The round comes with validation that matters more than the capital: Meta Reality Labs, Fanatics, and Kimberly-Clark have all deployed Auger's platform. Fanatics, the sports merchandise giant, reports it's now making roughly 85% of supply chain decisions autonomously through Auger, with ambitions to push that into the mid-90s. For a startup barely 18 months old and hovering around 130 employees, that's the kind of traction that turns heads.
A Deliberate Timeline
Clark says the company raised "early"—not because it needed the cash, but to sidestep fundraising distractions during what he expects will be a hectic fall of customer onboarding. It's a calculated move, perhaps more disciplined than you'd expect from a founder sitting on nine figures of venture backing. The Series B valued Auger at roughly double its Series A price, according to Clark's comments to GeekWire, though precise figures remain closely held.
Eclipse partner Jiten Behl joined the board alongside Clark, co-founder Alex Ceballos (who serves as president and CFO), and Oak HC/FT's Matt Streisfeld. The investor lineup suggests confidence, but also something else: the pressure to prove that agentic AI in supply chains isn't just another enterprise software buzzword destined to underwhelm.
What Auger Actually Does
Here's where things get technical, but stick with it—the details matter.
Auger doesn't rip out your existing enterprise software. Instead, it sits on top of the alphabet soup of systems most large companies already use: ERP, WMS, TMS, planning platforms. Think of it as a control layer that vacuums up data from those systems, makes routine decisions autonomously, then writes the plans back into the legacy tools. When a decision exceeds its programmed constraints—say, a supplier suddenly can't deliver, or a weather event disrupts logistics—the system escalates to humans, but with full context rather than fragmented alerts.
Clark calls this the "glass box of autonomy," a phrase that sounds like consultant-speak but gestures at something real: transparency into how decisions get made, using what the company describes as domain ontology, constraint optimization, and agentic AI. The goal is eliminating what Clark terms the "Coordination Tax"—the endless meetings, emails, and manual spreadsheet wrangling that gums up modern supply chains.
Built natively on Microsoft Fabric and running on Azure, Auger became Microsoft's "premier supply chain partner" on the Fabric platform in March. That's more than a technical detail; Microsoft sellers can now earn commissions on Auger deals, giving the startup enterprise distribution it couldn't afford to build on its own. Smart.
The Amazon Mafia Rides Again
If Auger's executive roster feels like an Amazon supply chain reunion, that's because it is.
Russell Allgor, Amazon's former chief scientist for worldwide operations across 24 years, now holds the title of chief supply chain scientist at Auger. Sanjay Dash, who led Amazon's Just Walk Out and pay-by-palm initiatives, serves as CTO. Gopi Prashanth, with stints at Salesforce AI and Amazon Go's computer vision teams, is chief AI and agentic scientist. And then there's Leigh Anne Clark, Dave's wife, who runs the company's fashion and beauty vertical as president.
Ceballos, the co-founder, led the Amazon team that acquired Kiva Systems (now Amazon Robotics), bringing M&A experience that could prove useful if Auger decides to buy rather than build as it scales. Whether that's in the cards remains unclear, but having someone who's orchestrated a nine-figure acquisition on the team doesn't hurt.
A Crowded, Lucrative Market
Auger isn't alone in chasing enterprise supply chain budgets. The company competes with visibility platforms like Altana, Everstream, and Pando, as well as incumbent giants including SAP, Oracle, Blue Yonder, Manhattan Associates, o9, and Kinaxis. The market, though, appears large enough to accommodate multiple winners. Gartner forecast in April that supply chain management software with agentic AI capabilities would balloon from under $2 billion in 2025 to $53 billion by 2030.
Those are the kind of numbers that make venture capitalists pay attention—and that create space for well-funded challengers to carve out territory before the incumbents fully wake up. Whether Auger can execute quickly enough to claim a defensible position is the open question.
The Real Test Ahead
For now, the company is taking an almost austere approach to capital deployment. It subleased former Microsoft office space in Bellevue to keep real estate costs low, an unusual move for a startup sitting on $150 million. Clark's comments suggest the capital is meant to buy runway for execution, not fuel aggressive hiring or geographic expansion. Customer deployments and fall onboarding are the priorities.
The Meta Reality Labs deal, announced on February 4, 2026, will be a proving ground. Manufacturing and logistics for cutting-edge hardware is a different beast than sports merchandise or consumer goods—more complexity, tighter tolerances, less room for error. If Auger can push decision autonomy into the 90s there, the platform's credibility broadens considerably.
And if it can't? Well, enterprise software graveyards are littered with startups that had pedigreed founders, marquee logos, and compelling demos but couldn't translate proof-of-concept into repeatable, scalable performance. Clark's challenge now is avoiding that fate—and proving that his second act can deliver the kind of operational transformation he helped pioneer at Amazon, this time from the outside looking in.
