Is Auger AI the Future of Supply Chain Tech - Or Just a $100M PowerPoint?
A critical look at Auger, hype-fueled funding, and why most supply chain veterans aren’t buying the dream
If raising $100 million with no product demo was a sport, Auger would have just won gold. But in supply chain, real value isn’t measured in fundraising rounds. It’s measured in systems that work, teams that benefit, and ROI that’s crystal clear. On that front, Auger hasn’t delivered anything - yet.
Anthony Miller’s recent post on LinkedIn asked the question everyone in supply chain tech should be asking: What is Auger actually building? And why should we care?
The response from supply chain professionals? A mix of sarcasm, skepticism, and cautious interest. But mostly doubt.
So let’s take a serious look at the conversation - and the company.
What Has Auger Promised?
So far, not much beyond buzzwords.
According to Dave Clark, the former Amazon exec now at the helm of Auger, the platform will “integrate data from multiple sources and use advanced AI and machine learning to generate automated, dynamic insights in real time.”
Sound familiar? It should. We’ve been hearing this from enterprise software vendors for 20 years.
The promise of a “single pane of glass” over supply chain planning, forecasting, and finance is not new. The reality of fragmented systems, bad data, and organizational inertia makes this promise a lot harder to keep than many investors realize.
The Timothy Marsh Reality Check
One of the most grounded and hard-hitting comments came from Timothy Marsh. His view cuts through the marketing fluff and asks the tough questions Auger needs to answer:
“What makes Auger any better? Is a former Amazon big-shot all that's needed to grab market share and raise $100MM?”
That question hits at the heart of the issue. Is Dave Clark’s CV enough to justify a valuation and round of that size? Without a product or proven market traction?
As Marsh points out, this isn't just about tech. It’s about enterprise integration pain, ROI clarity, and whether organizations can justify ripping out existing systems or overlaying yet another “solution” on top of a pile of broken data pipelines.
“Hee hee! Yeah let's use AI to make sense of all the garbage data currently in our disconnected systems... that don't currently talk to each other... and train it on that!”
That comment isn’t cynical. It’s honest. And it reflects what thousands of supply chain leaders face daily - AI can’t work miracles if the foundations are unstable.
The Bigger Problem: AI Gimmicks Are Wearing Thin
There’s a growing fatigue in the industry. We’ve had “AI-powered everything” thrown at us. Most of it hasn’t worked. Most of it doesn’t even make it to implementation.
Anthony Miller was blunt: “Maybe it is time they stop the cheesy AI-first communication style… and start building some real hype about what they are doing.”
That sentiment echoes across the comments. Grant Sernick joked that he had written a nearly identical post but hadn’t hit publish yet. Raffaele Turturro summed it up this way: "Have a shiny deck, buzzwords, and an ex-big tech exec? Voilà, $100 million."
This isn’t progress. It’s déjà vu.
The Flexport Shadow
Let’s not forget Dave Clark’s last high-profile role - CEO of Flexport. It was short, messy, and ultimately didn’t end well. Some argue Clark was blocked from making real changes. Others suggest he struggled to adapt to an environment very different from Amazon.
Either way, the legacy of Flexport’s disarray now trails behind him. And launching another “stealth” startup with no visible product only compounds the doubt.
As one commenter put it: “You can look brilliant at Amazon. But recreating that success on your own? That’s a different game.”
What Supply Chain Leaders Actually Want
They don’t want jargon. They want clarity.
What problem are you solving?
How long does implementation take?
How much does it cost?
What is the measurable ROI?
These are the questions real operators are asking. Not, “How cool is your AI?”
As Marsh also points out, the comparison to big ERP deployments like SAP and Oracle is relevant:
“Sold in to top management with all sorts of promises… in reality it takes twice as long to integrate and is twice as expensive to run.”
That’s the risk with Auger. Big vision, big promise… followed by costly disruption, delays, and very little return.
Are VCs the Enablers?
Some blame belongs with the investors. There’s a pattern here: back companies with bold visions but no tech, let them hire a few “famous” execs, and hope the branding does the rest.
But in supply chain - where execution is everything - that strategy rarely works.
Auger might be a warning shot. Or worse, it might be proof that VCs still don’t understand how difficult supply chain transformation really is.
Can Auger Still Turn It Around?
Yes. But they’re running out of time.
If Clark and team want to salvage this narrative, they need to start sharing something - anything - that shows traction. A pilot. A customer. A case study. A real-world workflow.
Until then, the longer they stay in stealth mode, the more the market will assume they’ve got nothing to show.
And in a world moving faster every quarter, being silent for too long is the same as falling behind.
Final Thoughts: From Flash to Substance
Auger may yet surprise us. But if they don’t pivot soon toward substance, transparency, and real customer engagement, they’ll become the case study no one wants to write.
Raising $100 million is not the finish line. It’s the starting gun.
And in supply chain, that’s when the real work begins.
What do you think?
Has Auger already lost the trust of the supply chain community, or is there still time to prove everyone wrong? Share your view in the comments.
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