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- 🤯 How Sourcy is building the world’s first Prompt-to-Product AI platform to solve a "boring" problem
🤯 How Sourcy is building the world’s first Prompt-to-Product AI platform to solve a "boring" problem
From maxed-out credit cards to $5M raised from global VCs
Hey Founders,
👋🏻 Welcome to The Runway Ventures (🎙️Podcast Edition) — where I interview founders and deep dive into their stories to help you become the top 1% founder by learning from their startup journey and mistakes with actionable insights.
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Today at a Glance:
🫡 1 Founder → Karl Chan (Founder of Sourcy)
⚠️ 2 Mistakes → Copy-pasting Silicon Valley’s playbook
🧠 3 Lessons Learned → Do things that don’t scale to validate your hypothesis
🔗 The Runway Insights → YC: Startup ideas you can now build with AI
💰 Southeast Asia Funding Radar → Unbound raises $4M (Seed) to help helps enterprises adopt Generative AI tools securely and responsibly
🫡 1 Founder: Karl Chan (Founder of Sourcy)
🌟 The Highlights
Karl started his career in consulting, crunching numbers for big names like McDonald’s and Estée Lauder. But after an MBA at Wharton and a stint at the World Bank’s IFC, he spotted a massive gap in the sourcing world.
The Problem — 😮💨 Brands and retailers were drowning in spreadsheets, back-and-forth communication, factory specs, and logistics just to launch a single product without leveraging the right tech, data, and AI.
The process was messy, slow, and super outdated.
The Solution — ⚡️ Sourcy uses AI to help brands streamline the entire process, from identifying the right product to manufacturing and shipping.
✨ Here’s how Sourcy works:
Brands would type in a product idea — say, a Gen-Z–friendly water tumbler.
Sourcy’s AI agent would scrape TikTok trends, Amazon reviews, and factory catalogues, together with its proprietary knowledge graph, and spit back a ready-to-manufacture spec sheet.
Then, behind the scenes, Sourcy’s AI would negotiate MOQs, lock in pricing, and ship finished samples in record time.
And boom! First-mover advantage achieved, and revenue keeps coming in.
🤖 In short, Sourcy is like ChatGPT for B2B sourcing.
🤯 I was blown away when I tried Sourcy’s AI sourcing platform with some product ideas that I had. Try it out here and you’ll know what I mean.
While B2B sourcing might seem like a boring idea, deep down, Karl knew this space was broken and ripe for disruption. And he was right. D2C brands and retailers in SE Asia and the US now use Sourcy to turn ideas into products in weeks, not months. |
💰 Sourcy got backing from global VCs across the US, Europe, Japan and SE Asia, landed on Forbes’ “Asia 100 to Watch” list, and BCG named it a top AI startup in Asia.
🏄🏻♂️🇺🇸 But the real validation came when Trump’s tariffs hit. Suddenly, every drop-shipper needed unique products fast — and Sourcy’s leads spiked 300%. While many companies were struggling after the US tariffs were announced, it was a tailwind for Sourcy to expand to the US market.
At its peak, Sourcy turned a “boring” B2B sourcing problem into a tech revolution — and proving VCs wrong along the way.
🌋 The Lowlights
I literally used my credit card for payroll and borrowed money from my wife and my mother just to keep the lights on.
But the journey wasn’t smooth.
🌏 Karl’s first big mistake? Copy-pasting a U.S. startup’s model (Faire) into Asia. He spent 6 months building a B2B marketplace for small retailers… only to realise Southeast Asian buyers didn’t care. The model “made total sense on a PowerPoint deck” but flopped in real markets.
💸 Then came the fundraising crunch of late 2022. Karl had turned down an early term sheet in Q1 2022, confident he’d close at a higher valuation — only for markets to crash and capital to vanish. Cash burned fast and he was maxing out credit cards to pay salaries.
As the financial pressure mounted and investor phones went silent, Karl thought about giving up.
But he persisted.
🚢 Then came the logistics nightmares. An Indonesian sock brand’s launch almost flopped when shipments got delayed — the product arrived hours before the event. In Mexico, a coffee chain’s cups were stuck in customs, risking a store opening with no inventory. Karl learned the hard way: “Never trust third-party partners blindly. Always have a Plan B… or C.”
🎢 The emotional toll? Brutal. Investors called Sourcy “boring.” One VC even mocked the idea to his face, calling it an idea only our grandparents generations would find interesting. But those sleepless nights taught him to ignore the noise and cling to customer feedback like a lifeline.
🚀 The Comeback
I needed to be empirical, do things that don’t scale.
💪🏻 So how did Karl turn it around? Grit.
He threw out his VC-theory hat, ditched the fancy PowerPoints and got his hands dirty.
🫡 In fact, what I loved the most is how Karl validated the problem by doing things that don’t scale:
Instead of immediately worrying about scalability and optimising for fundraising, he manually scraped Amazon reviews, negotiated with factories, and built trust one product at a time.
Karl’d then spend hours of Excel-driven scraping, margin-built recommendations at +$1 over cost, just to see if brands would pay.
Guess what? Brands paid for his solution!
That proof of product-market fit reignited investor interest, successfully raising funds from top investors.
Not just that, he automated everything — integrating AI and knowledge graphs RAG for smart retrieval, building a supply-communication tool for real-time catalogue updates — and watched traction explode. He also hired slower, focusing on culture-fit over resumes.
🇺🇸 Today, Sourcy isn’t just surviving. It’s expanding into the US, leveraging those deep Asian supplier ties and its AI edge to help American brands facing tariff woes.
📈 Proven results? Customers report a 60× faster go-to-market cycle and the confidence to launch thousands of SKUs like Shein — minus the guesswork.
📌 Here’s the TLDR of Sourcy:
Sep 2021 — Karl founded Sourcy in Singapore after identifying inefficiencies in the sourcing-to-manufacturing process.
Launched the initial "Faire for Asia" marketplace model but struggled to gain market traction.
Early 2022 — 🧪 Pivoted after failing to gain traction and started manual sourcing experiments to validate the B2B sourcing problem.
😬 Declined an early term sheet, anticipating a higher valuation.
Late 2022 — Faced a challenging fundraising environment and Karl bootstrapped the company using personal resources.
Almost ran out of cash and maxed out his credit cards to pay salaries.
H1 2023 — 🥳 Validated the problem and saw early signals of product-market fit with a manual MVP.
Secured pre-seed funding.
2023–24 — Automated platform with AI and knowledge graphs.
Recognised by Forbes and BCG and backed by prominent investors like Kapital Ventures and Foxmont.
Mar 2025 — 💰 Closed Seed round by investors across US, Europe and Asia, with $5M in total fund raised.
Started US expansion after experiencing a surge in leads post-tariff announcements.
Karl built Sourcy by combining a hands-on, empirical approach with cutting-edge AI technology. After navigating early setbacks, he transformed Sourcy into a comprehensive prompt-to-product AI sourcing platform that empowers brands worldwide to source smarter and sell better.
Today, Karl has turned a “boring” sourcing problem into a tech revolution. From nearly giving up to Forbes recognition and $5M raised, Sourcy now helps 300+ brands launch products faster, cheaper, and smarter — proving that even the dullest industries hide billion-dollar opportunities.
🧠 The next time you are hesitant about solving a “boring” problem, think twice. Because that’s where the gold mine is.
Want to learn more about Sourcy?
⚠️ 2 Mistakes
Mistake 1: Copy-pasting Silicon Valley’s playbook
I was stubbornly pushing a solution that only made sense on a PowerPoint deck.
When Sourcy was started, Karl spent 6 months trying to replicate Faire’s US B2B marketplace model in Southeast Asia.
It flopped. Why?
Because Southeast Asian buyers didn’t care about curated boutique brands — they wanted to build their own brands with speed and cost control.
He had banked on theory, not real customer pain.
Mistake 2: Settled for the best candidate available
I realised I was hiring for the best available, not the right fit.
Desperate to fill roles, Karl would interview just 3 or 4 candidates, pick the “best of the bunch” and call it a day — even if they may not be the right skill and culture fit. Inevitably, those hires underperformed, cost time, and dragged morale.
And he wasted months fixing the hiring mistakes.
His wake-up call? “I’d rather hire a hungry rookie who fits our need than a candidate with the best resume who doesn't”.
🧠 3 Lessons Learned
Lesson 1: Do things that don’t scale to validate your hypothesis
Theory ≠ Reality
🫡 Karl’s journey with Sourcy is a masterclass in why grunt work beats grand theories when validating a startup idea.
The only way to know you’re solving a real problem is to get paying customers on a bare-bones MVP.
🌮 Key Takeaways:
🎯 Define your core hypothesis
Before you build anything, nail down the ONE assumption you need to prove.
Start by asking: What problem am I solving, and for whom?
Write down your hypothesis in one sentence. Example:
“Restaurants will pay for a service that sources locally grown ingredients faster than their current supplier.”
🧱 Build a simple & cheap MVP quickly
Forget automation. Be the “human API” for your service.
For example, if you’re building a SaaS tool for B2B, manually create reports for users using Excel, then email them.
The goal here is to build the solution to see if it solves customers’ problems.
🤑 Charge real money (even $1)
If people pay for your manual service, you’ve got a business. If not, pivot.
Offer a stripped-down version of your service for a small fee.
Example: If you’re building a meal-plan app, manually create custom plans for 10 users at $10 each.
♻️ Listen to feedback and iterate
After delivering your manual service, ask users: “What would make this 10x better?”
Track how they use your product, and bake those features into your product.
Lesson 2: Hire slow, fire fast
Early hires set your company’s DNA. A mis-hire doesn’t just cost salary — it kills momentum, wastes time, and takes a long time to correct — just like what happened to Sourcy.
Hiring is the most expensive thing a startup does — so do it deliberately.
🌮 Key Takeaways:
🐢 Hire slow
Do the role yourself first to understand every task, every bottleneck, and the exact skill needed. This is to ensure what “good” looks like.
Prioritise cultural fit over credentials.
Test drive candidates by doing paid trial projects and watch how they problem-solve.
⚡️ Fire fast (without being a jerk)
New hires got a 90-day plan with 3 clear milestones.
Weekly check-ins to give feedback and catch issues early.
Don’t forget to communicate feedback early so firing isn’t a shock (if it happens).
If it’s not working, be honest but kind. And cut ties immediately.
Lesson 3: Always have Plan B
Sourcy nearly lost a footwear brand’s launch when logistics partners delayed shipments hours before the event. Another client’s coffee cups got stuck in Mexican customs.
Moral of the story?
Always have Plan B.
🌮 Key Takeaways:
Diversify suppliers
Assume everything will break because hope isn’t a strategy.
Always have a Plan B for each order.
For every critical supplier, find 2 backups. Test them with small orders first.
💨 Smoke-test your providers
Before going live, run a “shake-out” shipment: send a low-value SKU through both carriers, track timing, customs clearances, and customer updates.
🚨 Negotiate contingency SLAs
Your contract should guarantee expedited fallback support.
For example, if the primary forwarder misses ETA by 24 hours, the backup must dispatch within 12 hrs at no extra cost.
🔗 The Runway Insights
💰 Southeast Asia Funding Radar
Unbound raises $4M (Seed) to help helps enterprises adopt Generative AI tools securely and responsibly (Link)
GridCARE raises $13.5M to deliver power solutions to AI data centers (Link)
Remind raises $1.3M to supercharge e-waste revolution in Indonesia (Link)
Snabbit bags $19M to offer hyperlocal, on-demand home services at scale (Link)
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