At Stormlands Mining, we have been modelling TSX-listed mining technical reports as part of our broader work to build structured valuation models for global mining assets and projects. One thing stands out:

A significant percentage of technical reports do not include a project-level economic analysis.

In our current review, approximately 40% of the reports modelled do not provide an economic analysis. That raises an important question:

Why?

There are two obvious explanations.

First: some reports relate to assets already in production. In those cases, companies are often not required to publish a fresh economic analysis in the same way as a development-stage project.

Second: some reports are earlier-stage mineral resource reports, exploration updates or technical updates where no formal project economics are provided.

That may explain part of the gap but it does not explain all of it. In our review, a meaningful number of reports with no economic analysis relate to pre-production projects with mineral resource estimates. That is where the question becomes much more important:

Why is this extremely important task not being completed?

The absence of economic analysis creates a major gap between geological disclosure and investment decision-making. A technical report may give us tonnes, grade, contained metal, cut-off grade, resource classification, mining method, processing assumptions and recovery assumptions. The cut-off grade is not just a technical number, it is an economic boundary. It already contains a series of economic assumptions, including metal price, recovery, operating cost, royalties, payability, dilution, mining recovery and exchange rates. Sometimes these assumptions are visible. Sometimes they are buried in tables. Sometimes they are only partially explained. But if the report is already using economic assumptions to define what is potentially economic, why does the analysis often stop there?

Why do we get a cut-off grade, but not a valuation model?
Why do we get contained metal, but not project-level economics?
Why do we get a resource statement, but not an estimate of capital intensity?
Why do we get tonnes and grade, but not an estimate of future government revenues?

For investors, this matters. A copper project with excellent grade may still struggle if capital intensity is too high. A gold project with strong contained ounces may still produce weak returns if sustaining capital is underestimated. A polymetallic project may look attractive on a copper equivalent basis, but the revenue mix, payability, penalties, recovery assumptions and concentrate terms can completely change the economics.

For economic geologists, this matters too. A deposit is not just a collection of tonnes and grade. It is a potential business. Resource geometry, grade distribution, strip ratio, recovery, mining selectivity and metallurgical performance all flow directly into economic outcomes.

For junior explorers and project promoters, this may matter most of all. If a project is being presented to investors, strategic partners, governments, lenders or potential acquirers, the missing question is not only:

“Is there a resource?”

It is:

Could this project be economically viable?
Will it provide an acceptable return for investors?
Will it be financially sustainable?
The answer to these questions requires structured thinking.
What is the likely scale of capital expenditure?
What level of sustaining capital might be required?
What operating margin is implied?
What fiscal regime applies?
What government revenue might be generated?
What commodity price is needed to justify development?
What happens if recoveries are lower?
What happens if capex is 30% higher?
What happens if royalties or taxes change?

These are not academic questions. They are the questions that determine whether a mineral asset can attract capital.

At Stormlands, we believe this gap is becoming increasingly important. The industry has made enormous progress in technical disclosure. Resource reporting is more structured. Technical reports are highly detailed. But economic interpretation remains inconsistent. That creates a problem. Investors are left trying to translate technical reports into financial models manually. Junior explorers and project promoters are left trying to explain value using static presentations. Governments are left trying to understand future tax, royalty and state revenue without a consistent project-level model, and economic geologists are often left with their work being judged through overly simplified metrics.

The real question is:

What does the asset actually support economically?

This is the question Stormlands is answering. We are building structured, auditable valuation models from public technical reports, including reports that do not contain formal economic analysis. That means taking the technical information already disclosed and using it to create scenario-ready models that can estimate or benchmark:

  • capex
  • sustaining capital
  • operating cost structure
  • revenue by commodity
  • royalties and taxes
  • government take
  • NPV and IRR sensitivity
  • payback
  • valuation impact of commodity prices, recoveries, costs and fiscal terms

But the bigger opportunity is not only to model individual reports, it is to build a structured, algorithmic and predictive valuation system for mining assets. Every technical report modelled adds to the dataset. Late-stage exploration projects, PEAs, pre-feasibility studies and definitive feasibility studies all contain useful information about tonnes, grade, recoveries, mining methods, processing routes, capital intensity, operating costs, sustaining capital, fiscal terms and valuation outcomes. Producing mines add another layer. Where actual capex, sustaining capital, operating costs and production performance can be observed, inferred, benchmarked or validated from producing assets, they help improve the logic for estimating missing economic information.

That matters because the industry has a major data problem. A pre-production project may disclose a mineral resource, a cut-off grade and some technical assumptions, but not a full economic model. A producing mine may disclose production and operating results, but not a fresh project-level valuation. A DFS may contain detailed economics, but those assumptions are often locked inside static documents and are difficult to compare systematically with other assets.

Stormlands connects those dots. By structuring this information across many assets, commodities, jurisdictions and development stages, we can start to benchmark and estimate the missing economic pieces more intelligently. The objective is not to pretend that incomplete information is complete. The objective is to make the uncertainty visible, testable and comparable. That is the real opportunity: to move from static technical disclosure to dynamic economic interpretation, and, over time, to build predictive tools that help investors, project promoters, governments and technical teams understand what a project could reasonably support economically.

This does not replace formal technical studies. It does not replace the role of the Qualified Person. It does not turn every mineral resource into a mineral reserve. But it does make the economic question visible much earlier. The mining sector does not lack technical information – it lacks consistent economic interpretation of that information.

So the questions we keep asking are:

Why should economic analysis only appear at certain formal study stages?

Why should investors wait until late in the process to understand a project’s potential value?

Why should governments wait to understand future revenue potential?

Why should project promoters leave value unexplained?

If a technical report contains enough information to define a cut-off grade, then it already contains the beginning of an economic story. At Stormlands, we think that story should be modelled, tested and made visible. Because in mining, the real question is not only what is in the ground.

It is whether what is in the ground can become a mine worth building.

Stormlands Mining publishes independent Whistler Gold-Copper Project case study showing major leverage to current gold and copper prices Illustrative scenario shows how project economics respond to March 2026 average commodity prices

Dublin, Ireland — 18 May 2026 — Stormlands Mining has published a new independent case study on the Whistler Gold-Copper Project in Alaska, using its AI-first mining valuation platform to model the project economics from publicly available technical information.

Stormlands independent modelling using March 2026 commodity prices for gold, copper, and silver as an illustrative scenario, shows that project Net Present Value (NPV) more than doubles in this scenario from US$2bn (base case) to US$4.71bn, while IRR rises from 32% to 61% and payback improves from around 30 months to 19 months. Life-of-mine (LOM) revenue increases from US$10.9 billion to US$16.1 billion, while LOM EBITDA rises from US$5.9 billion to US$11.0 billion. Estimated corporate income tax also increases materially, from approximately US$1.03 billion to US$2.18 billion.

This price scenario uses copper at US$12,498.98/t, gold at US$4,877.40/oz, and silver at US$74.92/oz, compared with the base case assumptions used in the NI 43-101 of copper at US$9,920.79/t, gold at US$3,200/oz, and silver at US$37.50/oz.

The Whistler case study is the latest release from the Stormlands Library, a growing repository of interactive mining asset valuation models designed to help users to understand the key drivers of mining project economics.

The base case analysis is based on the NI 43-101 Technical Report and Preliminary Economic Assessment dated March 2026, together with independent modelling by Stormlands Mining.

Stormlands’ base case model, using the technical-report and PEA assumptions, produces a post-tax project NPV of approximately US$2.02 billion at a 5% discount rate, with an IRR of 32% and payback of around 30 months after the start of production.

The model shows that Whistler is highly sensitive to commodity-price assumptions, particularly gold and copper. A 10% reduction in the overall price factor reduces project NPV to approximately US$1.44 billion, while a 10% increase raises NPV to approximately US$2.59 billion.

Stormlands’ sensitivity analysis shows that gold and copper are the key external value drivers. A 10% increase in gold price lifts NPV to approximately US$2.16 billion, while a 10% increase in copper price lifts NPV to approximately US$2.12 billion. Operating cost and capital cost are also material drivers, with operating-cost discipline particularly important in protecting value under lower-price scenarios.

Stormlands’ heatmap analysis shows that Whistler remains meaningfully positive across a broad range of price and operating-cost scenarios, while stronger commodity prices and lower operating costs move the project into a materially higher-value range.

Phil O’Connell, Chief Product Officer of Stormlands Mining, said: “Whistler is a good example of why mining valuation needs to move beyond static PDF reporting. The base case already shows a substantial gold-copper development project, but the real insight comes from being able to test how value changes as assumptions move. Under stronger gold and copper prices, the Whistler model shows a very significant uplift in NPV, IRR, payback and government tax outcomes.”

The Whistler case study follows Stormlands’ earlier Rovina Valley Project analysis and forms part of the company’s plan to build a global library of mining asset valuation models. The Stormlands Library is intended to provide a structured source of mining project models, enabling users to screen assets, benchmark projects and test assumptions.

The full case study is available through the Stormlands Library at https://www.stormlandsmining.com/library/whistler/

The analysis is based on the NI 43-101 Technical Report and Preliminary Economic Assessment dated March 2026, together with independent modelling by Stormlands Mining.

Stormlands Mining illustrative scenario with updated Commodity Price uses commodity prices from March 2026:

Gold:  4,877.40 USD/Oz
Copper: 12,498.98 USD/ton
Stormlands Library: https://www.stormlandsmining.com/library/
Whistler Gold-Copper case study: https://www.stormlandsmining.com/library/whistler/
Download PDF of case study: https://tinyurl.com/Whistler-Gold-Copper-Project

This publication has been prepared by Stormlands Mining Ltd. for informational, educational and illustrative purposes only. It is based on publicly available information, including the NI 43-101 Technical Report and Preliminary Economic Assessment March 2026, together with independent modelling undertaken by Stormlands Mining. Stormlands Mining has not been engaged by US Gold Mining Inc. or its affiliates to prepare this analysis. This publication has not been reviewed, approved or endorsed by US Gold Mining Inc., its advisers, or any Qualified Person associated with the Project. The analysis presented is not a technical report, mineral resource estimate, mineral reserve estimate, valuation opinion, fairness opinion, investment research report, securities recommendation, offer to sell, solicitation to buy, or investment advice. Stormlands Mining is not acting as a broker, dealer, investment adviser, corporate finance adviser, Qualified Person, or securities research provider in connection with this publication. All model outputs are scenario-based and depend on the assumptions used, including commodity prices, exchange rates, discount rates, capital costs, operating costs, taxes, royalties, production schedules, payability, recoveries, treatment and refining charges, timing assumptions and other inputs. Actual results may differ materially from the scenarios presented. Commodity prices, costs, financing conditions, permitting timelines and project development outcomes are uncertain and subject to change. Stormlands Mining does not represent or warrant that the information or model outputs are complete, accurate or suitable for any particular purpose. Readers should treat this publication as one source of information only and should conduct their own independent technical, financial, legal, tax and investment due diligence before making any decision. Neither Stormlands Mining nor any of its directors, officers, employees or advisers accepts any liability for any loss arising from reliance on this publication or the information contained in it.

11 MAY 2026 – STORMLANDS MINING LTD

Stormlands Mining publishes Rovina Valley case study showing sensitivity to stronger gold and copper prices

Independent Stormlands model closely aligns with Updated Definitive Feasibility Study (Dec 2025) project valuation

Illustrative scenario shows how project economics may respond to March 2026 average commodity prices

Dublin, Ireland, 11 May 2026. Stormlands Mining has published a new independent case study on the Rovina Valley Project in Romania, information from the NI 43-101 (Updated Definitive Feasibility Study (DFS) effective date December 2025), and Stormlands’ proprietary mining valuation platform (see notes to editors).

The Rovina Valley analysis is one of the first in a planned series of case studies to be produced from the Stormlands Library, a new repository of mining asset valuation models and illustrative scenarios. The Library will contain illustrative scenarios to help users to understand the key drivers of mining asset valuations.

Stormlands’ base case aligns with the NI 43-101 (DFS Dec 2025) valuation. The DFS reports an after-tax project NPV of US$1.469 billion and an IRR of 35.6%, with the project breaking even on a cash basis approximately 2.6 years after the start of production. Stormlands’ base case, built from the NI 43-101 technical assumptions, produces a comparable post-tax project NPV of US$1.443 billion, a difference of less than 1%.

The case study then uses the Stormlands platform to examine how project valuation would respond to different assumptions. The most significant insight is the project’s sensitivity to stronger gold and copper prices. Using the NI 43-101 base case assumptions of US$3,300/oz gold and US$9,920/t copper, Rovina Valley shows a robust project-level valuation. In a separate illustrative scenario, Stormlands applies March 2026 average prices of US$4,877/oz gold and US$12,499/t copper. Under that scenario, modelled project NPV increases from approximately US$1.44 billion to US$2.82 billion, while IRR rises from approximately 31% to 50%.

The illustrative price scenario also materially improves key project metrics. Life-of-mine revenue increases from approximately US$6.4 billion to US$9.1 billion, while life-of-mine EBITDA rises from approximately US$3.7 billion to US$6.3 billion.

This is not merely an accounting uplift. In the Stormlands scenario, higher commodity prices materially change the modelled risk-reward profile. Payback improves from 37 months to 26 months, reducing the period of capital exposure. Net smelter return increases from approximately US$52/t ore to US$74/t ore, and operating margin improves meaningfully. Government also benefits: corporate income tax rises from about US$483 million to US$891 million, while government royalties increase from about US$385 million to US$548 million.

Stormlands’ sensitivity analysis identifies gold price as the dominant value driver for Rovina Valley. A 10% reduction in gold price reduces modelled NPV (based on DFS commodity prices) to approximately US$1.2 billion, while a 10% increase raises NPV to approximately US$1.7 billion. Copper price is also positive but less influential, with a 10% copper price increase lifting NPV to approximately US$1.5 billion. Operating cost is the second most important value driver, while treatment and refining charges have a smaller valuation impact.

“Rovina Valley is a useful example of why mining valuation needs to be dynamic,” said Róisín O’Connell, CEO and Co-Founder of Stormlands Mining. “A technical report provides the foundation, but investors and other stakeholders also need to understand how project economics change when value drivers change such as metal prices. The Stormlands Library is designed to make that type of analysis faster and easier to compare across projects. It makes valuation models accessible over any platform to all users, putting the data directly in the hand of the decision maker.”

The Rovina Valley case study is a clear example of Stormlands Mining’s broader ambition: to build a global repository of interactive valuation models for mining assets. By turning technical reports into dynamic, comparable models, Stormlands aims to make project economics easier to interrogate, helping users move beyond static disclosures and understand how value changes as market conditions, geology, costs evolve.

Notes

The Rovina valley base case model was based on the NI 43-101 Updated Technical Report on Rovina Valley Project in Romania – Updated Definitive Feasibility Study prepared for Euro Sun Mining Inc prepared by Adar Consulting Corp, effective date 23 December 2025.
Stormlands Mining illustrative scenario with updated Commodity Price uses commodity prices from March 2026:
Gold USD/oz  4,877.40 USD/Oz
Copper USD per ton  12,498.98 USD/ton

Stormlands Library: https://www.stormlandsmining.com/library/

Rovina Valley case study: https://www.stormlandsmining.com/library/library-rovina-valley/

Download PDF of case study: https://tinyurl.com/Rovina-Valley-case-study

Important notice

This publication is for informational, educational and illustrative purposes only. It is based on publicly available information, including the Rovina Valley NI 43-101 technical report and related public disclosures, together with independent modelling undertaken by Stormlands Mining.

The analysis is not a technical report, updated technical report, mineral resource estimate, mineral reserve estimate, valuation opinion, investment research report, securities recommendation, offer to sell, solicitation to buy, or investment advice. The March 2026 commodity-price case is an illustrative scenario only and should not be interpreted as company guidance or an updated valuation prepared by or for Euro Sun Mining Inc.

Stormlands Mining has not been engaged by Euro Sun Mining Inc. or its affiliates to prepare this analysis. This publication has not been reviewed, approved or endorsed by Euro Sun Mining Inc., its advisers, or any Qualified Person associated with the Rovina Valley Project. Stormlands Mining has not received material non-public information from Euro Sun Mining Inc. in connection with this analysis.

Model outputs are scenario-based and depend on assumptions, including commodity prices, exchange rates, discount rates, capital costs, operating costs, taxes, royalties, production schedules, payability, recoveries, treatment and refining charges, timing assumptions and other inputs. Actual results may differ materially.

In mining streaming agreements, the answer depends on the terms you negotiate and the metrics you keep tracking. Streaming can be a powerful source of non-dilutive capital for mining companies.

But it can also transfer a significant share of future upside to the streamer.

The challenge is that too many negotiations are framed around headline terms: upfront payment, streamed metal percentage, ongoing purchase price and duration.

Those terms matter. But they do not tell whether the deal is good or bad.

To understand the real economics, both sides need to quantify the value trade-off. A stream may provide upfront capital today, but the cost is embedded in future revenue. The key metrics are:

  • NPV cost to the operator – How much project value is given up after discounting the future stream cost?
  • Payment / NPV cost ratio – For every $1 of discounted future value transferred, how much does the mining company receive upfront?
  • Effective stream financing rate – If the stream is treated like a financing instrument, what is the implied cost of capital?
  • Streamer’s NPV and IRR – What return does the streamer earn from the upfront payment and future margin?
  • Cash-on-cash multiple – How many times is the initial investment recovered over the life of the stream?
  • Effective realised metal price after the stream – A project may use a particular market price, but the blended realised price after the stream can be materially lower.
  • Cumulative stream margin – How much total future margin is transferred from the operator to the streamer?

These metrics are not only useful at signing. They are just as important during the life of the agreement. As metal prices move, mine plans change, production forecasts are updated, and development timelines shift, the economics of the stream also change. That creates a need for ongoing mark-to-market analysis. A streaming agreement should not be viewed as a static document sitting in a data room. It is a live economic instrument.

For operators, this means understanding the true cost of capital and the upside value being transferred.

For streamers, it means understanding return, payback, downside risk and portfolio value.

For investors, boards and lenders, it means having a transparent framework to assess whether the agreement is value-accretive, neutral or destructive.

At Stormlands Mining, we have built streaming and royalty functionality directly into our mining valuation platform. The objective is simple: Turn streaming terms into measurable economics. So users can negotiate with data, compare scenarios, and mark-to-market agreements across the life of a mine. Because in mining finance, a good deal is not defined by the headline payment. It is defined by the value exchanged. What metrics do you use to determine if the deal is good or bad? To learn more about how Stormlands Mining is creating a modern operating system for mining investment, get in touch or follow us for further updates.

Highlights

  • Manual mining valuation workflows break at scale. Teams reviewing a few assets per month cannot efficiently evaluate hundreds of opportunities without redesigning the process.
  • Mining PE teams may spend tens of thousands annually rebuilding inconsistent Excel models from technical reports.
  • High-performing investment teams are shifting toward centralized data, automated valuation workflows, dynamic scenario analysis, and portfolio-level benchmarking.
  • Execution capability not just capital is becoming the competitive differentiator in mining investment.

Crack the mining evaluation bottleneck
There’s a limit to how many mining opportunities a team can realistically evaluate using traditional workflows.
Eventually, every investment team hits the same constraint too many technical reports, too many disconnected spreadsheets, too many assumptions buried inside analyst models.

The result is a capacity bottleneck. When teams attempt to scale deal flow using manual processes, the problems compound quickly:

  • inconsistent valuation methodologies
  • slow turnaround times * fragmented technical and financial data
  • reduced comparability across assets
  • key-person dependency on individual analysts
  • difficulty updating views as commodity prices or assumptions change

And yet the pressure to move faster keeps increasing.

Mining private equity teams are now expected to screen more opportunities, compare more projects globally, and react faster to changing market conditions with the same internal resources. The challenge is not simply finding opportunities. It is building an operating system capable of evaluating them at scale.

At Stormlands Mining, we believe the next generation of mining investment workflows will be built around:

  • AI extraction of technical and economic data from NI 43-101 and JORC
  • automated generation of auditable DCF valuation models
  • centralized repositories of comparable mining asset models
  • dynamic scenario analysis and benchmarking
  • portfolio-level visibility across commodities, jurisdictions and development stages
  • faster iteration as prices, mine plans, recoveries or fiscal assumptions change

The competitive advantage is no longer just identifying good assets. It is the ability to evaluate more opportunities, more consistently, with greater speed and confidence than competing teams.

To learn more about how Stormlands Mining is creating a modern operating system for mining investment, get in touch or follow us for further updates on LinkedIn or subscribe to our YouTube channel

Mining asset valuation has traditionally focused on the technical fundamentals. But in real-world transactions, the value of a mining asset is often shaped by the commercial agreements. Commercial royalties, streaming agreements and offtake terms determine how realised value is allocated between stakeholders.

At Stormlands Mining, we have built these commercial structures directly into our valuation platform so users can understand the actual economic impact of transaction terms. Royalties are a familiar feature of mining finance, but they are not always modelled with enough commercial precision. The valuation impact depends on how the royalty is calculated. Royalties can provide non-dilutive capital for mining companies and long-term commodity exposure for royalty holders. But they also directly affect cash flow, NPV and the distribution of value.

Streaming is now a major financing tool, particularly for precious metals produced as by-products of base metal mines. In a typical stream, a mining company receives an upfront payment and agrees to deliver a percentage of future production to the streaming company. This can be attractive because capital can be raised without taking on debt or equity. A stream may look attractive, however, it can transfer substantial upside to the streamer, especially where commodity prices rise or production exceeds expectations.

That is why Stormlands has added dedicated streaming functionality to allow users to model the economic effect of a stream directly inside the project valuation. Offtake agreements can have a direct valuation impact. In some cases, the impact may be modest. In others, offtake terms can create material revenue leakage or shift value from the producer to the buyer. For analysts, management teams and investors, the key question is not simply “What is the expected revenue?” It is “What is the expected revenue after the commercial contract is applied?”

Small differences in commercial assumptions can have large effects on value. A project can look technically robust but produce a very different outcome once royalties, streams and offtake terms are modelled properly. The industry is becoming more sophisticated in valuation modelling, but commercial term modelling often remains fragmented, manual and spreadsheet-driven. That creates a gap.

Stormlands Mining has built an AI-first valuation and analytics platform for mining assets. Commercial royalty, streaming and offtake modelling is an important step in expanding the platform from technical valuation into transaction-aware economic analysis. Because in mining, value is not just mined it is commercially negotiated. It is created and often transferred through the commercial contracts that determine how realised value is allocated.

To learn more about how Stormlands Mining is modelling commercial royalties, streaming and offtake terms, get in touch or follow us on LinkedIn for further updates.

Unlike market capitalization, which only shows equity value, EV includes debt, potential dilutive instruments, and cash reserves. This gives a complete picture.

Junior miners often carry significant financial leverage because mining projects are capital-intensive. EV accounts for market capitalization, debt, and cash, providing a fuller view of a company’s financial health.

Market capitalization is like the tip of an iceberg—visible but not the whole story. EV reveals the entire iceberg, including what’s hidden beneath the surface. This is how investors can understand a company’s true value. It involves looking beyond equity. Debt obligations, cash reserves — data that’s important in the mining operations.

Comparing junior mining companies using EV is insightful. These companies might have similar market caps but very different financial structures, with varying levels of debt and cash. EV levels the playing field, offering a consistent standard for comparison.

For instance, a junior miner with significant debt might have an EV much greater than its market cap. It could signal potential leverage. It might be a warning or an indicator of growth potential, depending on the company’s assets and efficiency. A mining company with substantial cash reserves (from partnerships or pre-production revenue), could have a lower EV than its market cap. It means it’s undervalued.

Traditional mining valuation multiples, like price-to-earnings ratios, often misleading. Market shocks cause earnings to fluctuate wildly, making these multiples unreliable. EV cleans up these distortions by including debt and cash. Think about a mining company investing in new technology. Its short-term earnings might drop, making it look less profitable if you only consider traditional multiples. However, EV captures the full financial impact, showing the potential future benefits of this investment.

Mining is cyclical. Earnings rise and fall, causing multiples to fluctuate. EV remains stable through these cycles, considering long-term debt and cash. This offers a more reliable valuation over time. During mergers and acquisitions, the market cap alone can deceive. EV includes debt and synergies from the deal, providing a more accurate measure of the new entity’s value. When a company changes its strategy, for example diversifying into new commodities, it can affect its valuation. EV is better equipped to account for these changes. It reflects the company’s long-term value.

EV is a critical component in the due diligence of companies listed on TSX, TSX.V, and AIM stock markets.

AI and Excel. Both tools are powerful in their own right.

The trick?

Knowing which to use and when.

In mining asset valuations, AI is starting to edge out Excel.

Why?

It’s all about real-time scenario analysis, swift data processing, predictive modeling, and seamless collaboration. These are areas where Excel simply can’t keep up.

Complex financial data analysis? Calculating EV of the corporation? — Choose AI.

Straightforward data tasks? — Better use Excel.

Valuing mining assets isn’t getting any easier. With commodity prices all over the place and ESG trends gaining momentum, things are only getting more complicated. Sure, asset values in the mining sector are expected to rise, but don’t be surprised by the volatility along the way.

This is where the right mix of AI and Excel becomes important.
Mining companies need to brace themselves for independent valuations. Commodity-price assumptions are a major driver of asset-price swings. Some companies are betting on spot prices, while others are banking on long-term forecasts. Which one’s right? Time will tell.

Then there’s ESG. It’s not just a buzzword anymore. Companies are increasingly factoring in ESG trends when valuing assets. Metals linked to clean energy are getting a lot of attention, as are traditional safe havens like gold. Some players in the market have been slow to adapt, but that’s changing as the focus on clean energy intensifies.

So, what about AI’s role in all this?

AI has already made waves in exploration and production. Valuation? It’s only a matter of time. The demand for real-time, reliable, and cost-effective data is pushing AI to the forefront. Imagine cutting costs, speeding up the valuation process, and gaining deeper insights into an asset’s worth—all with the help of AI. The future of asset valuation is looking more and more digital.

Mining companies can do a lot to help valuers.

1️⃣ Context matters. Understand why the valuation is happening. Is it for internal use or to share with the market? Who are the intended users of the valuation: domestic or international investors, banks, other mining companies?

2️⃣ Set realistic expectations with respect to value. There is a tendency to seek value aligned with inflated expectations. However, stakeholders might not see things the same way. Some balance is required. And using AI alongside Excel can provide a more grounded view of the asset’s true value.

3️⃣ Close collaboration with the valuers is key. The valuation of a mining asset is an iterative process. Break it down into steps. Figure out where you disagree on the technical and economic details. The aim is to close those gaps and get on the same page.

In the end, mining companies need a structured valuation process.

By combining the strengths of AI and Excel, companies can ensure they’re getting the most accurate, actionable valuations possible.

February 2026

Africa is increasingly positioned as a critical source of the raw materials needed for the energy transition. But alongside the opportunity sits a harder question:

𝗛𝗼𝘄 𝗱𝗼 𝗴𝗼𝘃𝗲𝗿𝗻𝗺𝗲𝗻𝘁𝘀, 𝗶𝗻𝘃𝗲𝘀𝘁𝗼𝗿𝘀, 𝗮𝗻𝗱 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝗶𝗲𝘀 𝗸𝗻𝗼𝘄 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝗮 𝗺𝗶𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝘄𝗶𝗹𝗹 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗲 𝗶𝗻𝘁𝗼 𝗿𝗲𝗮𝗹, 𝘁𝗮𝘅𝗮𝗯𝗹𝗲 𝗹𝗼𝗰𝗮𝗹 𝘃𝗮𝗹𝘂𝗲… 𝗼𝗿 𝗶𝗻𝘁𝗼 𝘄𝗲𝗮𝗹𝘁𝗵 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗹𝗲𝗮𝗸𝗮𝗴𝗲?

In practice, “revenue leakage” rarely shows up as one obvious problem. It can be embedded in:
• terms that look reasonable on paper but perform poorly under price/cost volatility
• poorly modelled valuations
• transfer pricing and related-party service arrangements
• offtake and payability terms that quietly shift value out of the jurisdiction
• misalignment between what’s disclosed, what’s modelled, and what’s audited

The challenge is that risk is often invisible without a model that ties together the full value chain and then tests how outcomes change under realistic scenarios that stress-test production, pricing, costs, financing, fiscal rules, commercial and contract terms.

𝘛𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘱𝘳𝘰𝘣𝘭𝘦𝘮 𝘚𝘵𝘰𝘳𝘮𝘭𝘢𝘯𝘥𝘴 𝘔𝘪𝘯𝘪𝘯𝘨 𝘸𝘢𝘴 𝘣𝘶𝘪𝘭𝘵 𝘵𝘰 𝘢𝘥𝘥𝘳𝘦𝘴𝘴.

Stormlands helps teams identify taxable revenue and quantify expected government take by combining:
• structured data extraction from technical reports and project documentation (LLM-powered ETL)
• a standardised fiscal/valuation framework to calculate royalties, CIT and other fiscal flows
• dynamic scenario planning so stakeholders can see how risk shifts under different prices, costs, grades, recoveries, and timelines
• transparent outputs that can support disclosure, negotiation, and oversight

The result is not just “a valuation”, it is a way to ask better questions sooner:
• What revenue is actually taxable, and when?
• Which assumptions drive the biggest swings in government take?
• Where are the biggest risks of revenue leakage under downside scenarios?
• What would change if contract terms were structured differently?

If Africa is to capture long-term value from critical minerals, we need tooling that makes fiscal outcomes clear, comparable, and accessible, not trapped in brittle spreadsheets.

𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻: 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗯𝗮𝗿𝗿𝗶𝗲𝗿 𝘆𝗼𝘂’𝘃𝗲 𝘀𝗲𝗲𝗻 𝘁𝗼 𝗽𝗿𝗲𝘃𝗲𝗻𝘁𝗶𝗻𝗴 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗹𝗲𝗮𝗸𝗮𝗴𝗲? 𝗗𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆? 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝗼𝗽𝗮𝗰𝗶𝘁𝘆? 𝗠𝗼𝗱𝗲𝗹𝗹𝗶𝗻𝗴 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆?

https://miningdigital.com/news/how-african-mining-holds-the-key-to-global-economic-security

February 2026

The UK and the US have signed a memorandum of understanding to strengthen cooperation on critical mineral supply chains.

The MoU aims to boost investment and coordination across mining, separation and processing—supporting sectors like automotive, defence, clean energy and electronics. It aligns with the UK’s Critical Minerals Strategy, including a goal to limit reliance on any single country to no more than 60% of imports of a given mineral by 2035. The UK is backing the initiative with up to £50m in new funding, with both countries also seeking to streamline permitting and counter non-market pricing practices.

The UK–US MoU on critical minerals is a meaningful signal: governments are moving way from diversifying supply to coordinating policy tools and investment to do it.

A few things stand out:

1) Despite clear targets, execution is hard.
The UK’s ambition to avoid sourcing more than 60% of any single critical mineral from one country by 2035 is a strong north star. But targets only become reality when there’s a steady flow of permitted, financially viable projects and that’s where bottlenecks appear.

2) The real competition is for investable projects, not just minerals.
If the aim is to catalyse private capital into mining, processing and separation, then investors and lenders need decision-grade economics early: repeatable models, transparent assumptions, downside cases, and comparability across projects.

3) Preventing non-market pricing practices will increase the need for robust scenario planning.
As policy tools, permitting timelines, and pricing dynamics evolve, the industry will need to stress-test project value across realistic scenarios (capex inflation, price cycles, recoveries, fiscal terms). That’s how you avoid being caught out when the policy environment shifts.

4) £50m is a start — but the multiplier is how fast capital can underwrite decisions.
Public funding helps de-risk the early steps, but the scale-up depends on how quickly teams can move from studies and disclosures to bankable investment cases.

At Stormlands, we’re building analytics + AI tooling that turns technical reports into interactive valuation models so teams can evaluate assets consistently, run scenarios faster, and compare opportunities across the mining lifecycle — from early-stage project screening through to financing and operations.

Because in critical minerals, resilience isn’t just about geology.
It’s about being able to interrogate the data easily and having confidence in both the financial and environmental sustainability of the asset—so supply chains are secured responsibly, not just quickly.

https://www.gov.uk/government/news/uk-and-us-sign-memorandum-of-understanding-on-critical-minerals