7 Go-to-Market Lessons From Commercializing a $15.5M Deep Tech Platform

In a recent episode of Category Visionaries, Patrick Heissler, CEO of Scrona, a high-resolution printing platform, shared something most deep tech founders won’t admit: “I think first you need a lot of luck. You need a lot of luck and you need to be at the right spot at the right time, having the right contacts to make it work. It’s not so much about your technology, maybe then just having the right contacts, being in the right place at the right time.”

Patrick joined Scrona to transform academic research into industrial-scale products that manufacturers could actually use. His journey from consultant to CEO to investor reveals a playbook for commercializing platform technologies that contradicts conventional startup wisdom. Here are the seven most tactical lessons from that journey.

Lesson 1: Find Your End Market Champion, Not Your First Customer

Supply chains resist change. Patrick learned this quickly: “Converting a supply chain with a new technology, you’re seeing a lot of resistance. You will face a lot of, say, mindset problems where people will have some kind of transition costs, they might bear it. They would need to take some risks to get your technology into production lines, into their product.”

The solution isn’t convincing every link in the chain. It’s finding the hero customer at the end who benefits most from your innovation. “You need to have a compelling package that you can put on a table where, let’s say a hero customer, like an end market champion, can directly jump onto it, understands the opportunity he has there, and helps you to pull it through the whole supply chain,” Patrick explained.

The tactical implementation: identify the company at the end of the supply chain whose product performance improves most from your technology. Convince them first. Their purchasing power and market influence will pull you through upstream suppliers who would otherwise resist adoption.

“But if you have an end market champion, if you can convince, really one of these big corporates at the very end that they will have a value out of your technology, they will pull you through,” Patrick said.

Lesson 2: Package Before Perfecting

Patrick’s first priority as CEO wasn’t improving the technology. It was packaging what already existed into something industrial customers could evaluate. “The first thing we did is we clearly defined a product roadmap,” he said.

The timeline was aggressive. Patrick joined full-time in June. By July, they had launched at Semicon West: “We had the rollout of our generation 3 gen 3 8, which we call it, which is an 8 nozzle printhead, an off the shelf version of this product. We had it available in July and we rolled it out at Semicon west in San Francisco with a data sheet with something that people can take, have a look at, see the facts and can start implementing it.”

The datasheet mattered more than another technical breakthrough. Industrial customers don’t evaluate potential. They evaluate specifications, integration requirements, and scaling timelines. Patrick understood that moving from “research driven development, scale, feasibility, type of studies and products into an industrial scale product that can really be used by let’s say operators, non PhD operators in a fabric” required packaging, not perfection.

Lesson 3: Build Pipeline Selectivity Into Your Strategy

Most startups celebrate pipeline growth. Patrick actively limited it. “With a very small team like ours, a marketing strategy like a full blown up marketing strategy with multiplatform advertisement of your product doesn’t necessarily make sense,” he explained.

The reasoning: “I don’t necessarily need a huge project pipeline. Like it’s great if I have a lot of interest, it’s great if I have a lot of people coming in. But I want to be very selective on what we’re working on to have the highest impact on a company.”

Deep tech commercialization consumes engineering resources on every customer engagement. Customization, qualification support, and integration assistance all drain capacity. A huge pipeline doesn’t accelerate growth when each opportunity fragments focus and prevents the high-impact work that actually moves markets.

Patrick identified what he called “value inflection points or value inflecting projects” – the specific engagements that would fundamentally change how the market perceived the technology. Everything else became a distraction worth avoiding.

Lesson 4: Use Ecosystem Partners as Pipeline Filters

Limiting pipeline creates a new problem: what do you do with interested customers who don’t fit your criteria? Patrick’s solution was ecosystem design rather than rejection.

“What is important for me is also to use that and build up an ecosystem so that I can say, okay, I have these huge projects. We’re working on customized print heads, we’re working on customized optimize product for our customers, for the big customers. But then I don’t want to like send people away if they’re interested in the technology,” he explained.

The partnership with Notion Systems became the release valve: “We have a strong partner with notion system that enables like smaller scale systems directly for customers that might not require this kind of immense R and D work. So I’m freeing up time at my team to really focus on value creation for our company and at the same time enable an ecosystem partner to also generate growth and value on their side.”

This accomplishes multiple objectives: captures market interest, builds ecosystem validation, creates reference customers in adjacent markets, and positions for future expansion without premature team scaling.

Lesson 5: Select Markets Based on Team DNA, Not TAM

Patrick inverted typical market selection methodology. Instead of starting with addressable market size and working backward to team capabilities, he started with existing advantages.

“For us, it was quite clear that this technology enables a lot of value for customers in the semiconductor space, also in the display space, which are maybe the two markets and industries that we’re closest to, because we are coming out of this kind of semiconductor, like we as a team are coming out of this semiconductor ecosystem,” he said.

The logic: “So we know these companies, we know these supply chains, we have a lot of contacts, and this makes it quite easy for us to Attract it.”

This approach dramatically reduces customer acquisition cost and time to first revenue. You’re not cold calling into unfamiliar industries. You’re activating existing relationships with people who already understand the problem you’re solving.

Lesson 6: Reframe Your Competition

When asked about competitive landscape, Patrick acknowledged direct competitors but immediately shifted perspective: “I think for a company like us which really wants to change the way that manufacturing is done on a micrometer scale, we are competing more against incumbent technologies like lithography, direct laser writing, screen printing, inkjet technology.”

This reframing changes everything about sales strategy. Your real competition isn’t other startups with similar innovations. It’s the established technologies with decades of inertia, qualified suppliers, and risk-averse engineers who trust what they know.

Your challenge isn’t proving your technology is better. It’s proving the switching costs, qualification risks, and organizational change are worth bearing. This perspective shapes messaging, sales enablement, and how you position value propositions.

Lesson 7: Build Timeline Expectations Into Fundraising and Operations

Patrick’s three to five year vision included a detail that affects everything from runway planning to investor selection: “With the typical qualification timelines in the semiconductor industry, we’re looking at two year qualification timelines. That means starting late 2026, early 2027, we will see mass adoption of that technology in various applications in various production lines.”

Two-year qualification timelines mean your sales cycle isn’t months, it’s years. Early customers aren’t buying finished products. They’re committing to multi-year qualification partnerships. Your runway needs to accommodate these realities, not SaaS metrics.

This understanding shaped Patrick’s 2025 objectives: launch the Generation 3 platform with 100+ nozzles in Q1, move large projects into qualification phases, and close a funding round that would accelerate development of the next generation platform requiring AI capabilities.

The sequencing revealed sophisticated thinking: prove technology in core markets where the team has advantages, achieve adoption in those markets, then leverage credibility to internationalize and diversify. As Patrick put it: “We will see a much larger platform company, a real platform company. On the way up still.”

The Platform Technology Paradox

Patrick articulated the fundamental challenge that shaped all these lessons: “For a startup to push a technology into a market is pretty difficult, especially if it’s a platform technology, because you can do everything and nothing at the same time.”

When your technology has legitimate applications across six different industries, the promise of endless opportunity becomes the reality of fragmented execution. The solution isn’t pursuing every opportunity. It’s having the discipline to identify the single path that creates the most leverage, then focusing exclusively on making that path successful.

These seven lessons reveal that commercializing deep tech requires fundamentally different thinking than building software companies. Success comes from understanding that luck and timing matter, that supply chains need champions to overcome resistance, that packaging beats perfection, that saying no matters more than saying yes, and that industry timelines determine strategy more than venture capital expectations.