These are not aspirations. They are product standards.
This page is less about company values and more about how the product handles source material, verification, and uncertainty.
Four standards behind the data
Source Accuracy
The aim is to keep extracted information aligned with the original document and make it easier to check when needed.
Clear Sourcing
Where possible, records link back to their source documents so users can review the original context themselves.
Stated Limits
Coverage gaps, unclear disclosures, and extraction limits should be visible instead of hidden behind overly confident presentation.
Practical Review
Automation helps organize the material, but review and judgment still matter when the source documents are complex or ambiguous.
Why the workflow matters
Mining disclosures often contain important details in formats that are hard to compare quickly. A useful product needs to make those details easier to reach without losing the source.
If the product is going to be used for research, the sourcing, structure, and limits of the data need to be obvious.
The point is not to sound definitive. The point is to make the material easier to work with.
The product should make it easier to reach the original source, not further away from it.
Primary documents only
The product is mainly built from regulatory filings, technical reports, and official corporate disclosures rather than summaries written elsewhere.
The aim is to keep a direct path from organized data back to the underlying document whenever that is possible.
- Filings, technical reports, and official disclosures are used as the main inputs
- Organized records stay connected to the underlying source material
- Structured output is used to make comparison easier
- Human review is still useful for difficult cases
- Uncertainty should be labeled instead of hidden
How the product presents information
Documented Methods
How resource data gets aggregated, how grades are calculated, and how records are normalized is documented where it matters. The goal is for users to understand what the data represents.
Stated Assumptions
When the product applies assumptions like metal prices, exchange rates, or cutoff grades, those should be visible so users can form their own view.
Known Gaps
Coverage is not complete. Some jurisdictions, document types, and extraction categories have gaps, and those are noted rather than hidden.
How AI is used
The product uses AI to extract and structure data from mining filings and technical reports. That is how it handles large volumes of documents that would be impractical to process manually.
Automated extraction works well for most standard documents, but some cases are ambiguous or complex enough to need human review. The product is designed around that reality.
Where automation is involved, the aim is to keep that visible rather than presenting everything as if it were manually verified.
Operating standards
These are basic operating standards for how the product and company handle data, clients, and compliance.
Independence
The company does not trade on the information it processes, and commercial relationships do not shape product output.
Confidentiality
Client data is not shared or sold. Usage data stays private.
Compliance
The product operates within securities regulations and data protection laws in the jurisdictions it covers.
Professionalism
The product should stay clear, reliable, and usable rather than overpromising what it can do.
Explore the product
Browse the product pages or see how the platform handles mining filings, reports, and source links.