5 Inflection Points in Critical Minerals Startups
A retrospective look at the milestones and dynamics that changed the trajectories of nine critical minerals companies.
Whether it is Deep Tech or SaaS, a startup’s journey is, by definition, never linear.
It unfolds over time and reaches specific points along its roadmap tied to the achievement of an important event which, once reached, becomes a key pillar in the pursuit of the vision laid out by the CEO.
Accordingly, these positive data points shift the trajectory toward success through inflection points: moments when the company moves past certain stages that tangibly reduce a specific category of risk. This continues up to the launch of the first product. And then comes scale, when the cost curve declines and margins rise.
However, “it’s a long way to the top…”
Still, obvious as it may sound, some milestones or dynamics are hit repeatedly over time.
In some cases, they are sector-specific, tracing similar successful paths and paving the way for those who come after. Quite literally.
I remember a conversation I had with one of the world’s top Deep Tech VCs, who said how challenging it had been for a startup that was truly the first of its kind to chart a course with no comparable precedents.
That is part of the game for companies that are the first to enter a value chain with radical innovation.
On the other hand, if they manage to reach the market first, they have the opportunity to capture the greatest margin first as well—rewarding the bet made by those who believed in them, took risks alongside them, and provided them with the capital and support needed to reach that ambitious goal quickly.
Fortunately, not every Deep Tech startup journey is entirely unique. Some trajectories do repeat themselves, and over time certain points can become patterns.
Of course, in Deep Tech this means climbing the TRL ladder, reaching the market with a first product, and scaling production.
That is, unless a compelling conversation with a potential acquirer comes along first...
However, Deep Tech companies are also defined by other characteristics.
For example, each sector and each trajectory interacts with a more or less intricate ecosystem of regulation, procurement, and public and private strategic positioning, which may be far from straightforward and may prove distinctive for specific categories.
Moreover, while TRLs provide a common framework, advancing along that scale looks very different for a quantum computer than it does for a construction material, with major implications for timelines, capex, and opex.
So, given the market’s growing interest (and my own) in new solutions on the critical minerals front, I decided to map the journey of a few interesting companies—mostly startups and scale-ups, plus a small number of more mature benchmarks where useful—operating in this sector and tell their story through a narrative lens.
The idea is to offer you meaningful food for thought, hard-earned insights, and a broader perspective grounded in the experience of those who have already walked this path before.
My aim is to explore which milestones have come up most often, how companies have reached them, and how I think about them through the venture-building lens I’ve developed along the way—whether you’re shaping a business plan, exchanging ideas within an angel group, or simply looking to bring a few sharper angles into the room.
The logic behind this discussion
The idea for writing this piece came to me while thinking about a chart well known in the pharmaceutical industry—one that maps a company’s path across successive stages, capital raises, and the probabilistic progression toward product launch.
In the chart, the x-axis represents time, while the y-axis indicates the probability that this path will ultimately lead to a product launch.
The curve follows a stepwise pattern, with each step corresponding to a specific milestone (e.g., drug discovery > preclinical studies > clinical studies, and so on).
This logic is not exclusive to the pharmaceutical sector; it is simply more clearly mapped and validated there, after years of comparable journeys.
At each step, the probability of launch increases because an important element of the roadmap has been de-risked, with a corresponding increase in the company’s valuation.
Still, there is no reason why we cannot apply the same concept to Deep Tech, where, although there are fewer data points, it can still offer interesting conceptual insights.
After all, across energy, materials, manufacturing, robotics, semiconductors, mining, and even recycling, startups must demonstrate in sequence that their technology is not only promising, but also technically feasible, commercially adoptable, and industrially scalable.
Below is a rough conceptual sketch of what I have in mind: