Welcome to the 107th edition of Deep Tech Catalyst, the educational channel from The Scenarionist where science meets venture!
This week, we stay firmly in the mining and critical minerals universe, but flip the lens. Instead of asking how to build a mining tech company, we ask what makes one investable.
I sat down with Jun Qu, Principal at Main Sequence, to unpack how a Deep Tech investor looks at mining and critical minerals: where the real upside sits, which risks matter at each stage, and how non-dilutive capital and business model design change what’s possible.
Key takeaways from the episode:
🔌 Why Mining is Finally Venture-Backable
Structural demand from the energy transition and AI, looming supply gaps, more open incumbents, and new non-dilutive capital are turning parts of mining into genuinely VC-compatible markets.
⛏️ Where the Big Opportunities Sit in the Value Chain
Three areas stand out: exploration tech that finds better projects faster, processing and refining that make stranded resources economic, and operational tech that boosts output from existing mines.
💰 Business Models That Capture Value
From subscriptions and hardware-as-a-service to licensing, royalties, and tech-enabled operators, the core question is how much of the resource upside the technology provider chooses—and manages—to capture.
🧩 Cracking Adoption in a “First to Be Second” Industry
Industry insiders on the team, aligned strategic investors, and a focus on agile tier-two and tier-three operators create a realistic path from first pilots to credible references and, eventually, major miners.
📈 How Investors Assess Companies Across Stages
Pre-seed and seed are mostly about the team and showing the core technology works; Series A and beyond focus on unit economics, repeatable deployments, and scale, while the market is still maturing on growth capital and exit pathways in mining tech.
BEYOND THE CONVERSATION — STRATEGIC INSIGHTS FROM THE EPISODE
Why Mining Tech Companies Have Become Venture-Backable
For a long time, mining sat firmly outside the mental map of most venture investors. On paper, it had all the wrong characteristics:
It was slow-moving, built around multi-decade project cycles, and long permitting timelines.
It was deeply risk-averse, shaped by safety, regulation, and a culture that rewards reliability over experimentation.
It was capital-intensive in a way that did not fit the classic VC model: large upfront checks, long payback periods, and assets that looked more like infrastructure than software.
Venture capital, in contrast, is built around fast growth and disruptive adoption curves.
The ideal customer in that world buys quickly, iterates quickly, and, if things go well, scales quickly.
The traditional mining customer has been the opposite of that.
Even when there was technical interest in innovation, the combination of internal processes, competing priorities, and perceived risk meant that adoption tended to move at a glacial pace.
Given that mismatch, it is not surprising that mining and critical minerals have rarely been seen as a natural home for early-stage venture money.
The industry could support large balance sheets, long-term private capital, and listed companies, but not the kind of rapid value creation that venture funds are designed to underwrite.
That was the baseline from which things started to shift.
3 Tailwinds Changing the Equation: Demand, Adoption, and Non-Dilutive Capital
What has changed is not the fundamental nature of mining as a physical, capital-heavy industry, but the context in which it operates. 3 reinforcing forces have started to reshape the opportunity set and make parts of the value chain genuinely venture-backable.
The first is on the market side.
Demand for many critical minerals is now driven by structural trends, not just cyclical swings. The energy transition is the dominant driver: as power systems are electrified and electric vehicles scale, the volume of copper, lithium, and other critical inputs required by 2040 and 2050 looks dramatically higher than historical baselines.
On top of that, the build-out of AI infrastructure, especially data centers, is creating additional load on power systems and materials supply, adding to the pressure on certain commodities.
In a number of cases, this translates into markets with a scale and growth profile that can support venture-scale outcomes, provided companies can actually bring new supply to market.
The second tailwind is behavioral.
A growing number of incumbents are acknowledging that they cannot meet projected demand with today’s toolkits. Existing technologies, processes, and cost structures do not add up to the volumes implied by energy transition scenarios.
That realization is pushing both major players and tier-2 and tier-3 operators to engage more seriously with new technologies.
The posture is shifting from “we will wait until something is fully proven” to “we need to play an active role in developing and scaling what comes next.”
That does not erase the complexity of selling into large mining organizations, but it does change the willingness to run pilots, co-develop technology, and act as early customers.
The third force is the emergence of significant pools of non-dilutive capital aimed explicitly at critical minerals and enabling technologies.
Governments see supply security and diversification as strategic priorities, especially in a world of rising geopolitical tension.
The result is a wave of grant programs, debt, and other instruments that sit alongside equity rather than diluting it.
For Deep Tech companies in mining and processing, this does not just feel nice to have. It directly alters the economics of their development pathways.
Taken together, these 3 elements—structural demand, a more open customer base, and strategically motivated non-dilutive capital—are what start to make mining and critical minerals look like a domain where venture capital can sensibly play.
How Strategic Grants and Debt Actually Change the Capital Stack
For a deep tech company building hardware, manufacturing processes, or new forms of industrial infrastructure, the capital stack is often the difference between “interesting technology” and “investable business.”
If the only route to building a first-of-a-kind plant is to raise the entire amount as equity, the numbers frequently stop working.
A billion dollars of equity to build a facility is very hard to justify on a venture timescale, even if the underlying technology is compelling.
Strategic grants and concessional debt do not change the physics of the plant, but they do change who pays for what and on what terms.
If half of the capital stack required for a pilot or first commercial facility can be covered by non-dilutive funding, the amount of equity needed drops sharply.
That immediately makes the opportunity more attractive for early investors and creates a clearer path to venture returns.
Where the Venture-Scale Opportunities Sit in the Mining Value Chain
The starting point for thinking about opportunity in mining is simple but easy to overlook: everything ultimately comes back to bringing more critical resources into production.
The value chain is long, the technologies are diverse, and each commodity behaves differently. Moreover, bottlenecks do not show up in the same place for every mineral.
For instance:
Some commodities are constrained at the discovery stage.
Others are constrained because known resources are not economically viable to process with current technology.
In still other cases, the constraint lies in how effectively existing mines extract value from ore bodies already in operation.
So any serious view of where venture-scale opportunities sit has to be specific: both about the segment of the value chain and about the commodity in question.
With that caveat, three broad domains stand out as particularly relevant for venture-backed companies:
Exploration technologies at the top of the funnel.
Downstream processing and refining.
Technologies that improve operations and extraction at mines that are already producing.
1. Exploration Technologies: Filling the Top of the Funnel with Better Targets
At the very top of the value chain is exploration—the activity that determines what projects will even exist in around fifteen years’ time.
For certain commodities, copper being a clear example, exploration activity has lagged what would be needed to keep future supply in line with projected demand. For more than a decade in some cases, the level of exploration activity simply has not matched the scale of the challenge.
In that context, venture-scale opportunities emerge around tools that can accelerate and improve discovery.
This is not just about doing “more exploration” in a brute-force sense, but about using data and computation to make exploration programs more targeted, more efficient, and more discriminating.
One direction of interest is combining multiple datasets and applying AI to help identify high-potential assets—including the kind of tier-one opportunities that can materially impact future supply.
The other is more subtractive but just as valuable: identifying low-potential or “bad” projects earlier, so teams can avoid spending time and capital drilling out assets that are unlikely to be economic.
For miners and others focused on discovery, that distinction matters. Being able to eliminate dead ends sooner can make exploration programs more efficient and improve how scarce capital is allocated.
2. Processing and Refining: Making Previously Uneconomic Assets Economic
Moving downstream, another cluster of opportunities sits in processing and refining. Here, the problem is often not the absence of resources, but the fact that many known deposits are not economic with today’s technologies.
Impurities, complex mineralogy, and other characteristics can make projects difficult or expensive to produce—effectively trapping resources behind constraints that only new processing approaches can address.
Technologies that shift those constraints—by lowering costs, handling impurities, or unlocking new process routes—can have an outsized impact.
In lithium, for example, there has been significant interest in direct lithium extraction approaches that can reduce the cost of production and, in some cases, make resources viable that otherwise would not be.
The compelling aspect of these technologies is that they do not just improve operating performance for a project that would have been built anyway. In many cases, they can change the binary question of whether a project is economic at all.
That is a very different value proposition: instead of incremental optimization, processing innovation can make an asset viable.
The same logic applies to tailings reprocessing and other forms of value extraction from materials that are currently underutilized or discarded.
Recycling approaches can also fall within this broader category, where chemistry and engineering innovation changes what is considered feasible or economic to produce.
Across these examples, the unifying theme is the same: taking assets that the market undervalues because they are difficult to process, and using technology to unlock that value.
3. Operations and Extraction: Getting More from Existing Mines
The third domain focuses on mines that are already operating today.
These assets are on stream, producing ore and generating revenue—but there is still a significant question: “Are they extracting as much value as they could from the ore bodies they control?”
Given how long it takes to bring a new mine into production—often on the order of fifteen years—this question is not academic.
When supply shortfalls loom, one of the most immediate levers is improving the performance of assets that are already producing today.
This is where technologies around data, sensing, and precision mining come into play.
By capturing better information about the ore body and the flow of material through the system, operators can adjust how they mine and process in ways that increase recovery or reduce losses.
Data fusion plays a role here as well: combining different streams of sensor data to provide a more accurate and actionable picture of what is happening.
The common thread across these operational technologies is that they aim to maximize output and recovery from resources that are already committed to production.
For companies worried about meeting demand, that is a powerful lever.
For technology providers, it creates a clear link between their solutions and measurable improvements in recovery and yield.
Designing Business Models that Really Capture Value in Mining
At the heart of business model design in mining technology is a simple question:
“If you are the company bringing a new solution into the industry, how do you capture as much of the value you create as possible?”
The answer depends heavily on where in the value chain you operate, and on how responsibilities are split between you and your customer.
The further downstream you sit, the more familiar the models tend to look.
The further upstream you go—especially into processing and exploration—the more business models start to incorporate commodity exposure alongside technology economics.
There is no single “correct” playbook. Instead, there is a spectrum of options—subscription, licensing, royalties, joint ventures, and full asset ownership—that can be combined in different ways.
In practice, the craft is choosing a configuration that fits your technology, your capital requirements, and the kind of upside (and exposure) you want to take on.
1. Subscription and “Hardware-as-a-Service” Models
Closer to the operating mine site, many of the models will feel familiar to anyone working in enterprise software or industrial IoT.
If you are providing a software product to support mine operations, an analytics platform, or a data product built around sensor networks or robotics, a straightforward subscription or annual recurring revenue model is often a natural starting point.
In some cases, this extends to Hardware-as-a-Service arrangements.
The provider may install sensor units, autonomous platforms, or other devices at the mine, but instead of selling them outright, charges an ongoing service fee.
That fee can bundle together access to the software and data, as well as ongoing services such as maintenance and support, into a recurring commercial structure.
From an investor’s perspective, these models are relatively straightforward to evaluate because they resemble familiar enterprise and industrial technology revenue structures.
They typically scale with the number of sites, users, or units deployed, and can become repeatable as adoption expands—provided the solution becomes embedded in the customer’s operations.
The trade-off is that, in many cases, the upside is primarily linked to commercial reach (how broadly the solution is deployed) and fee levels, rather than direct participation in commodity economics.
2. Licensing, Tolling, and JVs for Processing and Refining Technologies
The business model equation starts to look different in the processing and refining part of the value chain, especially when you are bringing a novel flowsheet or a fundamentally new way of treating a particular ore or brine.
At the simplest end of the spectrum is classic technology licensing.
A company develops a new process for copper, lithium, or another critical mineral.
An engineering, procurement, and construction firm may handle the design and build of the plant.
The customer takes responsibility for building and operating the facility.
The technology provider licenses the flowsheet and receives a fee, but does not participate in operations or put capital into the asset.
The appeal of this model is that it is “low-touch” and comparatively light on capital for the technology company.
There is no requirement to finance plant construction, take operational responsibility, or manage the day-to-day realities of running a production facility.
The downside is that the upside is capped.
Even if the technology is central to making the project economic, the technology provider’s share of the value is limited to the licensing terms they can negotiate.
That is why venture investors often approach pure licensing with caution: if the total number of plants you can license to is limited, the key question becomes whether that stream of fees can support venture-scale outcomes.
Further along the spectrum are tolling models.
Here, the technology provider’s economics are tied more directly to what passes through the plant.
The fee might be linked to tonnage processed, units of production, or some other measure of throughput.
In return, the provider may offer ongoing operational support and maintenance, and supply proprietary components, reagents, or catalysts that are essential to the process.
This structure can allow the technology company to capture more of the value it creates.
As production scales, revenue can scale too. There is also room to blend fixed and variable components so that the provider can choose how much commodity exposure it is comfortable with.
If the provider takes on more operational involvement or puts some capital into the project, commercial terms can reflect that.
Joint ventures are a natural extension of this logic.
In some cases, the technology company will not just provide the process and operational know-how, but will also contribute equity and capital to fund the plant. The project becomes a shared asset, with a tolling or processing arrangement layered on top.
This gives the technology company a deeper claim on the economics of the facility, but it also ties up more capital and increases exposure to project execution.
3. Royalties, Commodity Exposure, and Technology-Enabled Mining Companies
In exploration and early-stage resource development, business models can shift away from selling technology alone and towards becoming, in effect, a technology-enabled mining company.
One way to do this is through royalties.
A technology company uses its tools to help identify, de-risk, or advance assets owned by others. In return, it negotiates a slice of the upside—often framed as a percentage of net smelter returns or similar.
Over time, this can build into a portfolio of royalty interests across multiple projects, each tied to the role the technology played in enabling progress on the asset.
Joint ventures are common here as well.
The technology provider and the asset owner can agree to co-develop a project, combining the technology with the mineral rights and capital. The precise split of responsibilities and economics varies from case to case, but the essence is that the technology company steps closer to being a co-owner of the resource.
Some teams go further and eventually choose to acquire assets outright and become operators themselves.
The logic is straightforward: if your technology helps you identify undervalued assets—and you believe you can operate them effectively—ownership provides the most direct exposure to the commodity upside your approach unlocks.
That shift, however, comes with a corresponding increase in operational and capital intensity. It pushes the company into a different type of business with materially different execution demands.
4. Hybrid Approaches
Across all of these examples, one pattern stands out: most companies do not live at a single point on the spectrum forever.
They experiment with hybrids.
Some processing technology companies combine licensing with elements of tolling, or pair a tolling model with selective equity participation in specific projects.
Some exploration-focused companies combine royalties on certain projects with joint ventures on others, and in a smaller set of cases may choose to pursue ownership where the opportunity justifies the additional exposure.
The important point is that there is no universal answer that applies across all technologies, commodities, and stages.
In practice, the right business model is the one that matches the characteristics of the technology, the structure of the segment it serves, the willingness of customers to engage, and the capital that is realistically available.
What is clear is that mining technology companies have more tools at their disposal than a simple choice between selling software licenses and building and owning entire plants.
Much of the strategic flexibility sits in the middle ground—where business models are designed to reflect not just the technology being delivered, but also the responsibilities taken on, the capital committed, and the level of commodity exposure a company chooses to accept.
Cracking Adoption in an Industry That Wants to Be “First to Be Second”
One of the defining characteristics of mining as an industry is its relationship with risk.
There is a well-known saying that captures it neatly: everyone wants to be first to be second.
In practice, many operators are willing to adopt a new approach once it has been proven elsewhere—but far fewer want to be the first to validate it on their own operations in a serious commercial way.
That stance is understandable. Mining organizations are often large and complex, and bringing a new technology into an operating environment can create real disruption risk—especially when production outcomes and reliability matter.
Yet this cultural reality makes life difficult for early-stage companies that need their first pilots, first field deployments, and first commercial references to prove their technologies in the real world.
Despite this tension, there are clear, repeatable ways teams can break through the “first to be second” barrier.
They tend to start with who is around the table, extend to which customers are targeted first, and culminate in how the company sequences its own de-risking milestones.
Why Industry Experience, Advisors, and Strategic Investors Matter
Selling into mining and metallurgical companies is rarely just a matter of having a better product. It is often about navigating a buying process that requires buy-in from multiple stakeholders—sometimes across different sites and functions.
This is why industry experience on the team can matter so much.
When founders, executives, or senior team members have worked inside the industry, they bring more than credibility. They tend to understand how decisions actually get made, where the friction points are, and what evidence different stakeholders need to see before supporting a pilot.
That experience does not have to sit exclusively within the founding team. It can come from board members, advisors, or senior hires brought in early.
What matters is having people around the table who have seen the industry from the inside and can help shape a go-to-market approach that reflects how mining customers actually adopt technology.
Strategic investors can play a similar role.
As more mining-focused corporate venture arms become active, it is increasingly common to see operators take minority equity positions in technology companies.
When that happens, it can do more than validate a solution. It can help streamline early piloting, reduce friction in adoption pathways, and accelerate de-risking.
Tier-2 and Tier-3: The Practical Path to First Commercial Proof
Even with the right people and the right relationships, not all customers are equally suitable for a first deployment.
Large miners have said this openly: for an early-stage company looking for its first serious pilot, they may not be the best place to start. Their internal processes can simply be too slow and too complex for the pace a young company needs.
This is where tier-2 and tier-3 miners—and other smaller operators—can become critical first partners.
Their organizations are often able to move faster. In some cases, a pilot can be approved with only one or two key signatures rather than a long, multi-step internal process.
That alone can make it much easier to get an initial reference and build momentum.
Smaller players can also be more willing to explore new technologies because the economics of their projects can make improvement opportunities more urgent—and because they may have more flexibility to work with new commercial structures.
Arrangements involving royalties or shared upside can be difficult to negotiate with a tier-1 major, particularly on flagship projects.
With tier-2 and tier-3 companies, there is often more room to experiment with structures that align incentives and help a technology provider share in the upside.
The result is that working with smaller operators can provide a faster, more flexible path to proof.
A technology that demonstrates its value across a handful of sites—at increasing levels of scale—becomes much easier to present to larger players later.
The majors may still want to be “first to be second,” but if “second” means following credible references from real operating environments, the conversation changes dramatically.
How VCs Evaluate Mining and Critical Mineral Startups Across Stages
When investors look at mining and critical minerals startups, they are not applying an entirely different playbook from the rest of deep tech—but they are applying it with a sharper focus on where the risk really sits at each stage.
Science risk, engineering risk, commercial risk, and capital intensity show up in different proportions as a company moves from pre-seed to growth.
Understanding how those pieces shift is essential both for founders planning their fundraises and for investors deciding when and how to lean in.
Pre-Seed and Seed Rounds
At the very earliest stages—pre-seed in particular—the center of gravity is almost entirely around the founding team.
That is true across ventures in general, but it is especially pronounced in complex, industrial sectors like mining and minerals, where the path to market is long, and the operating environment is unforgiving.
At this point, most teams do not yet have a product. There is usually no revenue.
The “company” may be no more than a founder or a small group of co-founders with a clear idea of the problem they want to solve and a first view on how their technology will address it.
Investors underwriting pre-seed rounds are therefore asking questions about people more than anything else.
Do the founders understand the technical domain deeply enough to push the science or engineering forward?
Do they understand the industry well enough to navigate customers and partners?
Can they build a team, absorb feedback, and adapt as they learn more about where their technology fits in the value chain?
By the time a company reaches seed, the picture becomes more concrete.
This is the point where investors are looking for early signals of product–market fit, even if those signals are still rough.
Some teams will have started to generate revenue, others may not, but in both cases, there should be more than just a concept. The technology needs to have moved beyond the realm of pure science.
A key shift at seed is that science risk should largely be behind the company.
The core physics, chemistry, or algorithmic approach should have been demonstrated to work under relevant conditions.
The remaining work is now primarily around engineering execution—building systems that are robust, scalable, and deployable in the environments where customers operate.
Investors at this stage will often look for early techno-economic analysis.
Even if it is still based on lab-scale or small-scale tests, it should offer a plausible view of how the technology will perform at commercial scale and how it stacks up against incumbent approaches.
The numbers do not need to be perfect, but they do need to point toward a cost and performance profile that could be genuinely competitive.
Seed is also usually where the first in-field pilots and demonstrations begin.
These may be limited in scope, but they provide the first real test of how the technology behaves outside the lab and how customers respond to it.
For investors, these pilots are about more than technical validation.
They are also about seeing early signs of how the team executes in the field and how it starts to build relationships with real operators.
Series A and Beyond: From Science Risk to Execution, Scale, and Repeatability
By the time a company is raising a Series A, the questions shift decisively away from “does this work at all?” toward “can this be scaled and repeated?”
This is where investors want to see clear evidence that the company has found a specific problem, for a specific type of customer, that its technology can solve reliably.
In other words, product–market fit should no longer be a hypothesis—it should be something the company can point to with confidence.
At this stage:
Pilots and early deployments should have moved beyond one-off experiments.
There should be a pattern: a defined customer profile, a repeatable use case, and a consistent set of outcomes.
The company should be able to articulate, with some precision, what value it delivers—whether that is in improved recovery, lower cost per ton, faster discovery, or some other metric that matters in the context of mining and minerals.
Series A is also when unit economics come into sharp focus.
Investors want to understand not just that the technology works, but what it costs to deliver, what customers are willing to pay, and how long it takes to recover the cost of a deployment.
Payback periods, contribution margins, and lifetime value become central to the conversation. These metrics are the bridge between a compelling technical story and a scalable commercial business.
Alongside that, the company needs to show that it is beginning to build a repeatable sales and deployment playbook.
Selling into mining is complex, but by Series A, the team should be able to describe how they win customers: who the decision-makers are, how long the cycle takes, what evidence is needed at each step, and how deployments are executed with acceptable risk and reliability.
As companies move beyond Series A—into Series B and later—the focus intensifies on scaling what already works.
At that point, the central questions become: “Can the company expand into new geographies, replicate its success across multiple sites or projects, and strengthen its margins as it grows?”
Organizational scale also becomes part of the equation.
Teams may reach one or two hundred people, and investors will look closely at whether the company has the leadership, processes, and systems needed to operate at that level.
Growth Stage
Across this progression, one emerging issue stands out: the relative scarcity of growth-stage capital dedicated to industrial deep tech in mining and critical minerals.
There is a growing ecosystem of investors willing to back pre-seed, seed, and, to some extent, Series A rounds in this space.
But when companies need larger checks—often in the 10M+ range—to fund scale-up, plants, or global expansion, the options become thinner.
This creates a genuine gap in the market.
Exit Strategy
The uncertainty at the growth stage feeds directly into another unresolved topic: exits.
Unlike in some more mature segments of enterprise software or consumer tech, there is not yet a long list of clear precedents for how mining technology companies, particularly those with meaningful ties to physical assets, ultimately return capital to their investors.
There are not many examples yet of mining tech companies following a well-trodden path: building a certain type of business, reaching a certain scale, and then being predictably acquired by a major miner, an industrial conglomerate, or another strategic buyer.
That does not mean such exits will not happen, but it does mean they cannot yet be treated as a given.
As the mining technology sector matures, and as more companies reach later stages and begin to test different exit routes—acquisitions, IPOs, or other structures—the market will start to reveal which combinations of technology, business model, and capital structure are most attractive.
