The Last Analog Frontier: Inside the Dirty, Brilliant, Overdue Reinvention of the Manufacturing Supply Chain

The machines and manufacturing systems that built the modern world are still being run by fax machines and prayer. One Canadian founder is done waiting for someone else to fix it.

Let's get something straight before we talk about AI, disruption, or any of the other words that have been laundered of all meaning by ten thousand pitch decks: the packaging supply chain — the unsexy infrastructure that puts product in every bottle, bag, tube, and carton you touched today — has been operating, by and large, on the same basic logic it used in 1987. Phone calls. Trade show handshakes. Spreadsheets emailed back and forth like love letters no one reads. A supplier website with a fax number in the footer. This is a $200 billion industry. It has a fax number.

The Man Who Lived Both Sides

Jamie Lo knows this because he was inside it. As head of sales for Unilever and Revlon Canada, he was the guy who had to launch unique SKUs for the Canadian market — different language regs, different ingredient concentrations, different everything — and then figure out where to actually make the packaging. The process was, in his words, a nightmare. Not because the talent wasn't there. Not because the will was absent. But because the tools didn't exist, and the bigger the company, the less likely anyone was going to build them.

That's the paradox that nobody in legacy industry wants to admit: scale should mean sophistication. Often it means the opposite. Enterprise companies ossify around whatever system got them to enterprise scale, even when that system is Word documents and approval chains buried in email threads from 2011.

Lo left that world, went through a SaaS sales stint selling into every industry you can name — watches, travel, technology — and watched the same story repeat everywhere. Then he went to Antler, the Toronto accelerator, sat through a mentor session where five quiet questions were projected on a screen with nothing else on the slide, and had the moment. The realization: very few people have stood on both sides of this equation. He had. And nobody had built the bridge.

What Laibl Actually Is (and Why the Timing Is Not an Accident)

Laibl is an automated sourcing platform for the packaging industry. It matches mid-to-large CPG and beauty brands — and increasingly food, pet, and healthcare — with vetted, trusted North American suppliers. AI handles the matching, the RFPs, the filtering, the comparative intelligence. What used to take weeks of cold outreach and trade show luck now takes seconds from a homepage search bar. That's the product. But the story is in the timing.

The reshoring wave was already building. Brands have been quietly de-risking their dependence on overseas supply chains — the pandemic taught expensive lessons about single points of failure, and tariff volatility is writing new ones every quarter. But there was no infrastructure to support the shift. The North American suppliers who could absorb that demand were invisible. Some don't have websites. Some have websites that look like they were built the year Napster launched and never touched again. A sales person, a contact form, and a fax number. That's the discovery process for a billion-dollar industry.

Laibl puts those suppliers on the map — literally discoverable, vetted, categorized, matched algorithmically — and gives brands the kind of competitive sourcing intelligence that previously required either a massive internal procurement team or a lot of guesswork.

The Moat Nobody Else Can Buy

Here is where it gets genuinely interesting. The moat is the data. Legal AI platforms can train on millions of contracts. Accounting AI can train on centuries of financial records. But the data that lives inside a brand's packaging sourcing process — the designs, the formulations, the launch timelines, the supplier relationships — has never been in any model. It's too proprietary, too competitive, too closely held. Coca-Cola's next product launch is in there. The next Revlon SKU is in there. Nobody gave that to OpenAI.

Every brand that runs a sourcing request through Laibl, every supplier that lists their capabilities, every deal that closes — it all becomes proprietary training data that no competitor can replicate by writing a check. The network effect compounds on both sides of the marketplace simultaneously. More suppliers means better matches. Better matches means more brand demand. More brand demand means suppliers see real ROI. Real ROI means longer retention and richer data. This is not a feature. This is a structural advantage that takes years to build and can't be purchased once it exists.

The 2% That Changes Everything

Laibl doesn't charge suppliers a $60,000 annual subscription to participate in RFPs they might never win. That model, which other marketplace platforms have tried, produces one outcome with reliable consistency: suppliers pay, get no deals, leave after a year, and tell everyone the platform doesn't work. Laibl charges 2% when the deal closes. Not when you sign up. Not when you respond to an RFP. When the deal closes. You win, they win, everyone wins.

The downstream effects of this model are worth examining. Suppliers are incentivized to respond quickly, represent their capabilities honestly, and treat every brand inquiry as a real sales opportunity rather than a qualification exercise. Brands get real competitive quotes and make better decisions faster. Lowe's team just helped one brand save 30% on a project — from a North American supplier they were already using, simply because competitive data surfaced a better arrangement. That 30% might keep someone's job. Probably does.

A Word About the Jobs

It would be incomplete, and maybe dishonest, to write about an AI sourcing platform without addressing the elephant. Lo doesn't dodge it. He's sat across from procurement professionals who clock, mid-demo, that the platform is doing what they do. He acknowledges that in five years, it might do more of it without them.

But he makes a distinction worth sitting with. The jobs that Laibl compresses are the mechanical ones — the hours spent chasing suppliers by phone, building RFP spreadsheets, manually comparing quotes, coordinating approval chains. The jobs it creates are the strategic ones: the people who understand what the market actually needs, who connect brand values to real human communities, who make the judgment calls that no algorithm will ever make well because judgment requires skin in the game.

Procurement teams have already been hollowed out by COVID headcounts that never came back. They're being asked to manage $30 million books alone. The tool that gives them back their time isn't the threat — it's the lifeline.

The Canadian Factor, the American Ambition

Lo is building a cross-border company with deliberate purpose. Operations in Canada — Halifax and Kitchener-Waterloo — where exceptional talent will work for 60 to 70 cents on the American dollar and can afford to own a home and live a life. Revenue traction and investment conversations in the US, where the risk appetite exists and the check sizes follow.

It's not arbitrage. It's architecture. Canada gives Laibl the talent density and the grant support — ACOA came through for them in Atlantic Canada, a signal the establishment is taking notice. The US gives them the market scale and the venture ecosystem to match it. They're not choosing between the two. They're building something that needs both.

The Next Chapter

Laibl is in its first serious fundraise. The team is looking for strategic investors — supply chain tech thesis, sustainability angle, or portfolio companies that become immediate customers. They want partners who answer texts, not just quarterly reports. They're in conversations that feel like the right ones.

The bigger play — brand subscriptions to proprietary market intelligence, predictive demand signals, knowing what's being manufactured and why nine to fifteen months out before anyone else does — is coming by Q2. The transaction volume that unlocks it is coming faster now that brands can run sourcing requests directly from the homepage without signing up first. A 60 million unit order for rotisserie chicken bags came through recently. Suppliers noticed. There's a company that built this model for food ingredients and crossed $1.6 billion in platform transactions within two years after landing one corporate partner with 34 portfolio brands.

Laibl is looking for its version of that partner.

The infrastructure of modern commerce has been running on duct tape and institutional memory for decades. Someone was going to fix it. The person who fixed it was always going to be someone who'd lived it from both sides, couldn't unsee the gap, and was stubborn enough to build the bridge anyway. Jamie Lo is that person. Laibl is that bridge.

The fax machines are on borrowed time.

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Jamie Lo is the co-founder and CEO of Laibl, an AI-driven supply chain platform transforming how brands source packaging and materials. With a background leading sales for global brands like Unilever and Revlon, Jamie brings firsthand experience navigating the inefficiencies of legacy manufacturing systems. He is focused on bridging traditional supply chains with modern AI to create faster, more transparent, and resilient sourcing networks.

Laibl.co | jamie@laibl.co | LinkedIn