Hypergram - Emerging Technologies Series
From Lab to Line: How Hypergram is Making Hyperspectral Imaging an Industrial Workhorse
For decades, manufacturers have known a hidden truth: countless defects and material inconsistencies are invisible to the human eye and conventional cameras. While hyperspectral imaging—a technology that captures light across hundreds of narrow wavelengths—holds the key to revealing these flaws, it has remained locked away in labs. Too slow, too bulky, and far too expensive for real-world production lines, its industrial promise has been largely unfulfilled.
Enter Hypergram and its groundbreaking first product, the HG VNIR Pro. This isn't just another incremental improvement; it's a fundamental reimagining of hyperspectral technology for industry. We sat down with the creator, Min H. Kim, to understand the vision turning a powerful scientific tool into a practical industrial asset.
Identifying the Unworkable Gap
Q: What fundamental market gap are you addressing with Hypergram?
Min H. Kim: "The core frustration we identified was that hyperspectral imaging, while extremely powerful, has been effectively unusable in real industrial environments. Existing systems are slow, bulky, expensive, and require scanning or controlled lab conditions. Manufacturers know critical defects are invisible to RGB cameras, but hyperspectral solutions have been impractical for real-time inspection."
"We built Hypergram to close this gap. Our key insight was that hyperspectral imaging only becomes valuable at scale when it is fast, scan-free, and tightly integrated with AI, just like modern machine vision systems. Our approach is uniquely capable because we capture full-frame hyperspectral data without mechanical scanning and pair it with GPU-based AI software that runs on standard industrial PCs. This makes hyperspectral inspection usable on real production lines for the first time."
The "Aha" Moment of Early Traction
Q: What early signal proved you were on the right track?
Kim: "A strong signal came from early Proof-of-Concept deployments where customers discovered defects they had never been able to detect before. In one case, a partner separated visually identical materials that had caused persistent yield loss for years—something their existing vision system completely failed to address."
"What surprised us was the swift shift in mindset. It wasn't just that the system worked; it was how quickly customers moved from curiosity to asking, 'When can we deploy this on the line?' That transition from R&D interest to operational urgency was a clear indicator we were solving a real and painful problem."
The Engine: A Team Built to Bridge the Gap
Q: What makes your team uniquely suited to tackle this challenge?
Kim: "Our core team combines deep academic expertise in computational imaging and computer vision with hands-on experience in building real systems. I am a professor at KAIST, with a background in graphics, vision, and hyperspectral imaging. Our senior engineers are KAIST PhD-level researchers who have worked with me for years, translating theory into working hardware and software."
"The personal 'why' is simple: we were frustrated seeing powerful imaging technologies remain trapped in papers and labs while industry relied on decades-old inspection methods. Hypergram exists to bridge that gap—to turn advanced imaging into something that actually improves real-world manufacturing."
The 24-Month Vision: From Novelty to Standard
Q: What does success look like 18-24 months from now?
Kim: "Success means Hypergram's hyperspectral camera and AI software are no longer viewed as experimental tools, but as a standard option for high-value industrial inspection. Concretely, this includes stable commercial deployments, repeat customers, and expansion from pilot use cases into broader production workflows."
"Technologically, success means demonstrating reliable, high-speed hyperspectral inspection under real factory conditions, proving that scan-free hyperspectral imaging can operate at industrial scale. Our roadmap is focused on product robustness, system integration, and relentless customer validation to get us there."
Strategic Talent: The Keystone Hire
Q: What kind of talent do you need next to accelerate?
Kim: "Our strategy is focused, not fast. We prioritize people who can bridge domains—hardware, optics, and AI software. The most critical next hire is an engineer who can own system-level integration; someone who understands how optics, electronics, software, and manufacturing constraints converge into a production-ready product."
"This role is pivotal now because moving from successful PoCs to scalable deployment requires engineering discipline and cross-functional execution. It's the difference between a brilliant prototype and a reliable industrial tool."
The Broader Impact: Seeing the Invisible
Q: If Hypergram is wildly successful, what impact are you most excited to create?
Kim: "If we succeed, hyperspectral inspection will become a routine part of industrial workflows, not a niche tool. Quality checks that are currently manual, destructive, or simply impossible will become automated, non-contact, and data-driven."
"The impact we are most excited about is enabling manufacturers to see what was previously invisible—reducing waste, improving safety, and increasing trust in automation. Ultimately, we believe this will shift machine vision from 'seeing surfaces' to truly understanding materials."
The Bottom Line:
Hypergram's HG VNIR Pro represents more than a new product; it signals a shift in accessibility. By tackling the core barriers of speed, complexity, and cost, Min H. Kim and his team are not just selling a camera—they are opening a new sensory dimension for industry. The journey from lab curiosity to line-side essential is underway, and it’s being built on a foundation of practical, scalable, and integrated engineering.