Mining intelligence.
All in one place.
White papers, research briefs, case studies, and events — structured and searchable. Built from Pulse data and field research.
16
Research assets
2
White papers
3
Case studies
2
Events
Latest
Getting decision-grade answers from AI on mining data: what works, what breaks, and how to verify.
Every capital decision in mining rests on a few derived numbers — a grade, a reserve, an AISC, a recovery. The layer underneath those numbers was never industrialised. Will Coetzer and Paul Cronin examine why generic AI returns confidently wrong answers on mining data, what the token cost curve means for teams who are building on it, and what decision-grade actually requires. Includes a live demo: vanilla AI versus Pulse-connected AI on the same question, same data.
Dead Data, Live Decisions: Why mining's AI future starts with normalisation.
The geological edition. For exploration geologists and technical practitioners — what AI-native data extraction means for drill logs, resource models, and legacy archives. Will Coetzer and Scott North examine the five normalisation problems no one warns you about, and what a working geological intelligence layer actually requires. Details to follow.
The Trust Layer
From co-pilot to autopilot in mining finance. A Pulse Intelligence white paper for capital allocators in mining.
AI Readiness Diagnostic
Where does your team’s data infrastructure sit today?
Answer 10 questions. Get a private diagnostic on your AI readiness — in minutes.
Browse all
The Trust Layer
From co-pilot to autopilot in mining finance. A Pulse Intelligence white paper for capital allocators in mining.
The Next 12 Months of ASX Miner Dividends, in One Chart
Coal cuts. Gold mixed. Iron ore steady. Forward dividend yields across 20 of the biggest ASX miners — and what they signal about free cash flow conviction.
Chaos to Clarity, Two Years On
In 2024 we asked 120+ mining executives how much of their week disappears finding data. AI solved the searching half. The trust half is still the problem.
Why a Coverage Foundation Is the Prerequisite for Mass AI Automation
An AI agent can draft a comp, monitor a portfolio, flag what moved — but only if the data is complete, structured, and verified across the full mining universe.
Three Critical-Minerals Deals, One Playbook
$2.9bn, $2.8bn, $35m. Three critical-minerals deals, one move: stop buying deposits, start underwriting the conversion and the offtake.
From Systems of Record to Systems of Action
Enterprise software is moving from storing what happened to moving the work forward. For mining finance, the action layer is the only one that matters.
The Model Was Never the Bottleneck. The Data Is.
Billions are flowing into agentic AI for finance. But if the underlying data is not structured, sourced, and validated, the agents will be confidently wrong.
Why Mining Finance Can't Afford Generic AI
The UiPath 2026 trends report confirms the agentic era demands vertical intelligence and trusted data. Here is what that means for mining finance.
The Four Faces of One Number
The same producer's quarterly output appears in four documents and disagrees in all four. The data is not wrong — the lineage is missing. Here is what that costs.
Stone Age to Space Age
The hidden discipline of mining-grade data normalisation. A Pulse Intelligence white paper for geological practitioners.
Why Should Anyone Trust AI Built for Mining Finance?
Every AI in mining will claim to be built by people. The only question worth asking is which people, which clients, which problems.
Stone Age to Space Age: The Hidden Discipline of Mining-Grade Data Normalisation
Why geological data infrastructure is the most underestimated bottleneck in mining — and what AI-native extraction changes for exploration teams.
The Trust Layer: From Co-Pilot to Autopilot in Mining Finance
Written for capital allocators. Covers the five stages of the mining investment workflow and why source-line traceability is the infrastructure the industry has been missing.
Getting decision-grade answers from AI on mining data: what works, what breaks, and how to verify.
Every capital decision in mining rests on a few derived numbers — a grade, a reserve, an AISC, a recovery. The layer underneath those numbers was never industrialised. Will Coetzer and Paul Cronin examine why generic AI returns confidently wrong answers on mining data, what the token cost curve means for teams who are building on it, and what decision-grade actually requires. Includes a live demo: vanilla AI versus Pulse-connected AI on the same question, same data.
Dead Data, Live Decisions: Why mining's AI future starts with normalisation.
The geological edition. For exploration geologists and technical practitioners — what AI-native data extraction means for drill logs, resource models, and legacy archives. Will Coetzer and Scott North examine the five normalisation problems no one warns you about, and what a working geological intelligence layer actually requires. Details to follow.
Automated portfolio monitoring across a global asset base
A precious-metals royalty and streaming company with 230+ assets replaced thousands of hours of annual manual filing review with automated workflows. Risk is now tracked in real time, with every figure traceable to source.
8–10 hours saved per day on market intelligence
A mining-focused investment bank replaced a manual news workflow — with an analyst starting at 3am to keep up — with a daily AI-generated digest. Timeliness and consistency improved; the firm is now a Year-2 client.
Every figure traceable to source — every provider tested
A metals royalty investor who had used nearly every mining data service consolidated sourcing into one platform with instant source traceability on every data point. Rated leagues ahead of every other provider used over a long career.
Get our research before everyone else.
One email a month — new research, field notes, and unpublished commentary from the Pulse team.