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Failure stories usually end at the failure. This one is about the six years after.
Jung Hong Kim is a Korean serial founder who started his journey in Hong Kong, where he built and sold two companies making machine-vision retail analytics for shopping malls and government properties. His third startup - also retail-focused - collapsed violently when COVID wiped out the entire retail solution market overnight. The crash left him in serious debt, and he spent roughly six years digging out as a management consultant specializing in large-scale infrastructure and enterprise architecture.
Those six years turned out to be the research phase. Working alongside the people who became his cofounders, he watched the same patterns of enterprise software failure repeat across projects - and one pattern in particular became the seed of his next company.
That company is Klipy, an AI Chief Revenue Officer that automates the back-office operations of enterprise and consultative sales, aiming to turn every seller into a ten-person sales team. He hand-coded the MVP in three months. It launched as an automatic CRM in November 2024, and today it serves around 4,000 companies worldwide - mainly in North America and Australia - at five-figure MRR, with a target of $1.5M ARR by the end of 2026.
Here is how three bootstrapped founders got there, including one of the most detailed growth playbooks this newsletter has featured.
The Gap Between Humans and Spreadsheets
Jung's core thesis comes straight from those consulting years: most business information system failures stem from the gap between how humans think and how data gets saved. Not everyone can think in spreadsheets. What changed recently is that LLMs bridge this gap effectively - which opened the door to eliminating sales data collection entirely.
The founding insight was also a classic dogfooding case. Jung had been a loyal HubSpot customer throughout his career, but found it painful to enforce CRM usage when scaling sales teams. The tension is structural: CRMs are crucial for forecasting, planning, and centralized customer records, yet salespeople have no motivation to do data entry. The tool the business depends on is the tool the users resent feeding.
So Klipy launched with exactly one feature: a simple sales CRM that automatically logs communications from email, LinkedIn, and meetings using AI. The sellers focus on clients. The AI agents handle the mundane processes. The product has pivoted and improved continuously since, but that single-feature clarity is what got it off the ground.
A Stack Chosen to Skip DevOps Entirely
Jung built the first MVP alone in about three months, learning the frontend as he went - he did not know what Next.js was when he started. The stack:
Next.js and Convex as the backbone. Convex - which he describes as Supabase for NoSQL - handles the entire infrastructure provisioning and workload orchestration through a JavaScript SDK, which saved significant DevOps cost and let him focus purely on business logic
Go and Rust for the side systems the AI agents use for scraping and document generation
Google Cloud hosting the integration layer and subsystems
His approach to the frontend learning curve was the engineer's approach to everything: build, test, set up good observability so problems surface faster than users find them, then debug rapidly. Nothing exotic - just a tight loop run with discipline.
Charging From Day One, on Purpose
Klipy has been bootstrapped since day one, with all three founders full-time. Jung is both a developer and a seller, which kept costs unusually low. Funding came from government grants and personal savings until the business turned profitable, with fixed costs held down deliberately throughout.
The pricing decision that shaped everything else: they charged from the very beginning. Jung's reasoning is one of the sharpest statements of the principle we have run in this newsletter - he did not want to test or build features based on feedback from people unwilling to pay, because that feedback is mostly nice-to-haves.
"Burning needs from real customers are more important and should take up 80% of your time. In B2B, people ultimately pay for a sense of security, not features."
The current model is freemium: a free tier with 200 monthly tokens, a single user, and two channel integrations, with paid tiers running $39 to $149 per seat per month, varying by token volume and enterprise security features. They tested many models along the way - channel-based add-on fees, token pricing, lifetime deals - before settling on results-based pricing, because it makes closing deals easier. The product is then engineered backward to keep margins intact, and free tokens for specific in-product actions now fuel meaningful product-led growth.
The team is still just the three founders. They are currently raising capital to scale, with one pre-seed investor on the cap table. His advice on the model: charge first, then make sure customers feel sufficiently supported. Features create a sense of security. So does good support - while you learn what to build.
Lifetime Deals That Lose Money on Purpose
The launch strategy started with homework. The team researched the previous month's top performers on Product Hunt, Microlaunch, Reddit, and AppSumo to understand exactly what each audience responded to, then built a genuinely attractive offer for each platform.
The offers often centered on lifetime deals - and Jung's framing of LTDs cuts against the usual complaint. Most people criticizing lifetime promotions expect them to be profitable, and making an LTD profitable is very difficult, especially with the gross margins of LLM-based products. That was never the point. Lifetime users expect lifetime access, which means they become lifetime testers. The goal was 100 core users whose feedback would continuously improve the product and whose referrals would grow revenue.
The launch platforms carried a second, less obvious benefit: their member bases are full of freelancers and small agencies. Klipy converted those users into affiliates and subsidized their referrals - turning a one-time launch audience into a standing distribution channel.
The Nine-Step Growth Playbook
After launch, cold direct sales carried the early revenue - content inbound is a wide net, but it takes time to fill. Jung's full system, in the order he recommends building it:
Set up ad pixels first, before anything else
Properly track funnel events with them
For B2B, build a well-matched audience on LinkedIn Ads
Build in public to prove you are a real person — with AI flops and scams multiplying online, this credibility signal matters more than ever
Collect testimonials at all costs: emails, pop-ups, gating. Testimonials are the key content at the bottom of the funnel
Bundle lead magnets with an explainer video and upload it to YouTube, which doubles as AI discovery
Drive SEO and AEO through support articles — they help activation, retention, and AI discovery simultaneously
Scrape competitor LinkedIn page followers and reach out directly, explaining what you offer differently. They get curious faster than a cold audience
Once inbound and outbound are producing steady growth, use the pixel database to scale with ads. Hire a performance marketer for this, and monitor CAC against LTV
The next phase is already in motion: a headless CRM strategy. In Jung's read, Claude is pushing the boundaries of go-to-market point solutions, but teams larger than five people still need a robust single source of truth underneath. Klipy is positioning as that layer - enabling strong PLG and integration partnership campaigns, with the upgrade going live within two weeks of this writing. He is explicitly looking to work with agencies and freelancers building solutions around the Claude ecosystem.
The Mistake He Names Without Flinching
Asked about his biggest challenge, Jung does not point at the market or the technology. He points at his own caution.
Bootstrapping with three people significantly constrained growth. The team overfocused on staying lean and using AI for everything - and in retrospect, he wishes they had brought in good agencies and freelancers much earlier, as soon as the product-market fit signals appeared. Now that the company is in growth motion, the stakes of hiring the wrong agency have grown considerably.
His summary is unusually direct for a founder assessing his own play: they did not take enough risk on scaling operations, and he would not make that mistake again. It is a useful counterweight to the stay-lean orthodoxy - lean is a phase, not an identity.
Three Pieces of Advice
Stop solving your own problem. Do not spend too much time developing solutions — you are not your customer. Many people suffer because they do not know what you already know. Find them, solve their problem, and the business grows as you repeat this.
Go to more events. Roughly 2% of the people you meet can hand you a completely new perspective. Find them. Staying in the office gives you a 0% chance of doing so.
Maintain health at all costs. Stated without elaboration, from a founder who spent six years recovering from a collapse. The brevity is the emphasis.
Building Beyond a Lifespan
Jung's stated ambition from here is longer-range than a revenue target: to keep building solutions that benefit people for years beyond his own lifespan. The nearer milestone is $1.5M ARR by the end of 2026, with the headless CRM strategy and the capital raise as the engines.
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